added workload image as scenario parameter (#854)

* added workload image as scenario parameter

Signed-off-by: Tullio Sebastiani <tsebasti@redhat.com>

* renamed workload_image to image

Signed-off-by: Tullio Sebastiani <tsebasti@redhat.com>

---------

Signed-off-by: Tullio Sebastiani <tsebasti@redhat.com>

.github/PULL_REQUEST_TEMPLATE.md

@@ -0,0 +1,10 @@
+## Description  
+<!-- Provide a brief description of the changes made in this PR. -->  
+
+## Documentation  
+- [ ] **Is documentation needed for this update?**
+
+If checked, a documentation PR must be created and merged in the [website repository](https://github.com/krkn-chaos/website/).
+
+## Related Documentation PR (if applicable)  
+<!-- Add the link to the corresponding documentation PR in the website repository -->  

.github/release-template.md

@@ -0,0 +1,7 @@
+## Release {VERSION}
+
+### Download Artifacts
+- 📦 Krkn sources (noarch): [krkn-{VERSION}-src.tar.gz](https://krkn-chaos.gateway.scarf.sh/krkn-src-{VERSION}.tar.gz)
+
+### Changes
+{CHANGES}

.github/workflows/docker-image.yml

@@ -13,6 +13,7 @@ jobs:
     - name: Build the Docker images
       if: startsWith(github.ref, 'refs/tags')
       run:  |
+        ./containers/compile_dockerfile.sh
         docker build --no-cache -t quay.io/krkn-chaos/krkn containers/ --build-arg TAG=${GITHUB_REF#refs/tags/}
         docker tag quay.io/krkn-chaos/krkn quay.io/redhat-chaos/krkn
         docker tag quay.io/krkn-chaos/krkn quay.io/krkn-chaos/krkn:${GITHUB_REF#refs/tags/}
@@ -21,6 +22,7 @@ jobs:
     - name: Test Build the Docker images
       if: ${{ github.event_name == 'pull_request' }}
       run: |
+        ./containers/compile_dockerfile.sh
         docker build --no-cache -t quay.io/krkn-chaos/krkn containers/ --build-arg PR_NUMBER=${{ github.event.pull_request.number }}
     - name: Login in quay
       if: startsWith(github.ref, 'refs/tags')

.github/workflows/release.yml

@@ -0,0 +1,47 @@
+name: Create Release
+on:
+  push:
+    tags:
+      - 'v*'
+jobs:
+  release:
+    permissions:
+      contents: write
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - name: calculate previous tag
+        run: |
+          git fetch --tags origin
+          PREVIOUS_TAG=$(git tag --sort=-creatordate | sed -n '2 p')
+          echo $PREVIOUS_TAG 
+          echo "PREVIOUS_TAG=$PREVIOUS_TAG" >> "$GITHUB_ENV"
+      - name: generate release notes from template
+        id: release-notes
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        run: |
+          NOTES=$(gh api \
+          --method POST \
+          -H "Accept: application/vnd.github+json" \
+          -H "X-GitHub-Api-Version: 2022-11-28" \
+          /repos/krkn-chaos/krkn/releases/generate-notes \
+          -f "tag_name=${{ github.ref_name }}" -f "target_commitish=main" -f "previous_tag_name=${{ env.PREVIOUS_TAG }}" | jq -r .body)
+          echo "NOTES<<EOF" >> $GITHUB_ENV
+          echo "$NOTES" >> $GITHUB_ENV
+          echo "EOF" >> $GITHUB_ENV
+
+      - name: replace placeholders in template
+        run: |
+          echo "${{ env.NOTES }}"
+          TEMPLATE=$(cat .github/release-template.md)
+          VERSION=${{ github.ref_name }}
+          NOTES="${{ env.NOTES }}"
+          OUTPUT=${TEMPLATE//\{VERSION\}/$VERSION}
+          OUTPUT=${OUTPUT//\{CHANGES\}/$NOTES}
+          echo "$OUTPUT" > release-notes.md
+      - name: create release
+        env:
+          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        run: |
+          gh release create ${{ github.ref_name }} --title "${{ github.ref_name }}"  -F release-notes.md

.github/workflows/require-docs.yml

@@ -0,0 +1,45 @@
+name: Require Documentation Update
+on:
+  pull_request:
+    types: [opened, edited, synchronize]
+    branches:
+        - main
+jobs:
+  check-docs:
+    name: Check Documentation Update
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v4
+
+      - name: Check if Documentation is Required
+        id: check_docs
+        run: |
+          echo "Checking PR body for documentation checkbox..."
+          # Read the PR body from the GitHub event payload
+          if echo "${{ github.event.pull_request.body }}" | grep -qi '\[x\].*documentation needed'; then
+            echo "Documentation required detected."
+            echo "docs_required=true" >> $GITHUB_OUTPUT
+          else
+            echo "Documentation not required."
+            echo "docs_required=false" >> $GITHUB_OUTPUT
+          fi
+
+      - name: Enforce Documentation Update (if required)
+        if: steps.check_docs.outputs.docs_required == 'true'
+        env:
+          GH_TOKEN: ${{ secrets.GITHUB_TOKEN }}
+        run: |
+          # Retrieve feature branch and repository owner from the GitHub context
+          FEATURE_BRANCH="${{ github.head_ref }}"
+          REPO_OWNER="${{ github.repository_owner }}"
+          WEBSITE_REPO="website"
+          echo "Searching for a merged documentation PR for feature branch: $FEATURE_BRANCH in $REPO_OWNER/$WEBSITE_REPO..."
+          MERGED_PR=$(gh pr list --repo "$REPO_OWNER/$WEBSITE_REPO" --state merged --json headRefName,title,url | jq -r \
+            --arg FEATURE_BRANCH "$FEATURE_BRANCH" '.[] | select(.title | contains($FEATURE_BRANCH)) | .url')
+          if [[ -z "$MERGED_PR" ]]; then
+            echo ":x: Documentation PR for branch '$FEATURE_BRANCH' is required and has not been merged."
+            exit 1
+          else
+            echo ":white_check_mark: Found merged documentation PR: $MERGED_PR"
+          fi

.github/workflows/tests.yml

@@ -35,7 +35,8 @@ jobs:
           --set alertmanager.service.nodePort=32000 \
           --set alertmanager.service.type=NodePort \
           --set prometheus-node-exporter.service.nodePort=32001 \
-          --set prometheus-node-exporter.service.type=NodePort
+          --set prometheus-node-exporter.service.type=NodePort \
+          --set prometheus.prometheusSpec.maximumStartupDurationSeconds=300
 
           SELECTOR=`kubectl -n prometheus-k8s get service kind-prometheus-kube-prome-prometheus -o wide --no-headers=true | awk '{ print $7 }'`
           POD_NAME=`kubectl -n prometheus-k8s get pods --selector="$SELECTOR" --no-headers=true | awk '{ print $1 }'`
@@ -84,9 +85,9 @@ jobs:
             echo "test_namespace"      >> ./CI/tests/functional_tests
             echo "test_net_chaos"      >> ./CI/tests/functional_tests
             echo "test_time"           >> ./CI/tests/functional_tests
-            echo "test_arca_cpu_hog" >> ./CI/tests/functional_tests
-            echo "test_arca_memory_hog" >> ./CI/tests/functional_tests
-            echo "test_arca_io_hog" >> ./CI/tests/functional_tests
+            echo "test_cpu_hog" >> ./CI/tests/functional_tests
+            echo "test_memory_hog" >> ./CI/tests/functional_tests
+            echo "test_io_hog" >> ./CI/tests/functional_tests
 
 
       # Push on main only steps + all other functional to collect coverage
@@ -113,9 +114,9 @@ jobs:
           echo "test_namespace"      >> ./CI/tests/functional_tests
           echo "test_net_chaos"      >> ./CI/tests/functional_tests
           echo "test_time"           >> ./CI/tests/functional_tests
-          echo "test_arca_cpu_hog" >> ./CI/tests/functional_tests
-          echo "test_arca_memory_hog" >> ./CI/tests/functional_tests
-          echo "test_arca_io_hog" >> ./CI/tests/functional_tests
+          echo "test_cpu_hog" >> ./CI/tests/functional_tests
+          echo "test_memory_hog" >> ./CI/tests/functional_tests
+          echo "test_io_hog" >> ./CI/tests/functional_tests
 
       # Final common steps
       - name: Run Functional tests
@@ -126,7 +127,7 @@ jobs:
           cat ./CI/results.markdown >> $GITHUB_STEP_SUMMARY
           echo >> $GITHUB_STEP_SUMMARY
       - name: Upload CI logs
-        uses: actions/upload-artifact@v3
+        uses: actions/upload-artifact@v4
         with:
           name: ci-logs
           path: CI/out
@@ -140,19 +141,20 @@ jobs:
           pip install html2text
           html2text --ignore-images --ignore-links -b 0 htmlcov/index.html >> $GITHUB_STEP_SUMMARY
       - name: Upload coverage data
-        uses: actions/upload-artifact@v3
+        uses: actions/upload-artifact@v4
         with:
           name: coverage
           path: htmlcov
           if-no-files-found: error
       - name: Upload json coverage
-        uses: actions/upload-artifact@v3
+        uses: actions/upload-artifact@v4
         with:
           name: coverage.json
           path: coverage.json
           if-no-files-found: error
       - name: Check CI results
-        run: grep Fail CI/results.markdown && false || true
+        run: "! grep Fail CI/results.markdown"
+
   badge:
     permissions:
       contents: write
@@ -169,7 +171,7 @@ jobs:
             path: krkn-lib-docs
             ssh-key: ${{ secrets.KRKN_LIB_DOCS_PRIV_KEY }}
         - name: Download json coverage
-          uses: actions/download-artifact@v3
+          uses: actions/download-artifact@v4
           with:
             name: coverage.json
         - name: Set up Python
@@ -192,7 +194,8 @@ jobs:
             cd krkn-lib-docs
             git add .
             git config user.name "krkn-chaos"
-            git config user.email "<>"
+            git config user.email "krkn-actions@users.noreply.github.com"
             git commit -m "[KRKN] Coverage Badge ${GITHUB_REF##*/}" || echo "no changes to commit"
             git push
       
+      

ADOPTERS.md

@@ -0,0 +1,8 @@
+# Krkn Adopters
+
+This is a list of organizations that have publicly acknowledged usage of Krkn and shared details of how they are leveraging it in their environment for chaos engineering use cases. Do you want to add yourself to this list? Please fork the repository and open a PR with the required change. 
+
+| Organization | Since | Website | Use-Case |
+|:-|:-|:-|:-|
+| MarketAxess | 2024 | https://www.marketaxess.com/ | Kraken enables us to achieve our goal of increasing the reliability of our cloud products on Kubernetes. The tool allows us to automatically run various chaos scenarios, identify resilience and performance bottlenecks, and seamlessly restore the system to its original state once scenarios finish. These chaos scenarios include pod disruptions, node (EC2) outages, simulating availability zone (AZ) outages, and filling up storage spaces like EBS and EFS. The community is highly responsive to requests and works on expanding the tool's capabilities. MarketAxess actively contributes to the project, adding features such as the ability to leverage existing network ACLs and proposing several feature improvements to enhance test coverage. |
+| Red Hat Openshift | 2020 | https://www.redhat.com/ | Kraken is a highly reliable chaos testing tool used to ensure the quality and resiliency of Red Hat Openshift. The engineering team runs all the test scenarios under Kraken on different cloud platforms on both self-managed and cloud services environments prior to the release of a new version of the product. The team also contributes to the Kraken project consistently which helps the test scenarios to keep up with the new features introduced to the product. Inclusion of this test coverage has contributed to gaining the trust of new and existing customers of the product.   |

CI/config/common_test_config.yaml

@@ -50,3 +50,23 @@ telemetry:
     oc_cli_path: /usr/bin/oc                                # optional, if not specified will be search in $PATH
     events_backup: True                                     # enables/disables cluster events collection
     telemetry_group: "funtests"
+elastic:
+    enable_elastic: False
+    collect_metrics: False
+    collect_alerts: False
+    verify_certs: False
+    elastic_url: "https://192.168.39.196"                                         # To track results in elasticsearch, give url to server here; will post telemetry details when url and index not blank
+    elastic_port: 32766
+    username: "elastic"
+    password: "test"
+    metrics_index: "krkn-metrics"
+    alerts_index: "krkn-alerts"
+    telemetry_index: "krkn-telemetry"
+
+health_checks:                                              # Utilizing health check endpoints to observe application behavior during chaos injection.
+    interval:                                               # Interval in seconds to perform health checks, default value is 2 seconds
+    config:                                                 # Provide list of health check configurations for applications
+        - url:                                              # Provide application endpoint
+          bearer_token:                                     # Bearer token for authentication if any
+          auth:                                             # Provide authentication credentials (username , password) in tuple format if any, ex:("admin","secretpassword")
+          exit_on_failure:                                  # If value is True exits when health check failed for application, values can be True/False

CI/tests/test_app_outages.sh

@@ -10,7 +10,7 @@ function functional_test_app_outage {
   yq -i '.application_outage.duration=10' scenarios/openshift/app_outage.yaml
   yq -i '.application_outage.pod_selector={"scenario":"outage"}' scenarios/openshift/app_outage.yaml
   yq -i '.application_outage.namespace="default"' scenarios/openshift/app_outage.yaml
-  export scenario_type="application_outages"
+  export scenario_type="application_outages_scenarios"
   export scenario_file="scenarios/openshift/app_outage.yaml"
   export post_config=""
   envsubst < CI/config/common_test_config.yaml > CI/config/app_outage.yaml

CI/tests/test_arca_cpu_hog.sh

@@ -1,19 +0,0 @@
-set -xeEo pipefail
-
-source CI/tests/common.sh
-
-trap error ERR
-trap finish EXIT
-
-
-function functional_test_arca_cpu_hog {
-  yq -i '.input_list[0].node_selector={"kubernetes.io/hostname":"kind-worker2"}' scenarios/arcaflow/cpu-hog/input.yaml
-  export scenario_type="arcaflow_scenarios"
-  export scenario_file="scenarios/arcaflow/cpu-hog/input.yaml"
-  export post_config=""
-  envsubst < CI/config/common_test_config.yaml > CI/config/arca_cpu_hog.yaml
-  python3 -m coverage run -a run_kraken.py -c CI/config/arca_cpu_hog.yaml
-  echo "Arcaflow CPU Hog: Success"
-}
-
-functional_test_arca_cpu_hog

CI/tests/test_arca_io_hog.sh

@@ -1,19 +0,0 @@
-set -xeEo pipefail
-
-source CI/tests/common.sh
-
-trap error ERR
-trap finish EXIT
-
-
-function functional_test_arca_io_hog {
-  yq -i '.input_list[0].node_selector={"kubernetes.io/hostname":"kind-worker2"}' scenarios/arcaflow/io-hog/input.yaml
-  export scenario_type="arcaflow_scenarios"
-  export scenario_file="scenarios/arcaflow/io-hog/input.yaml"
-  export post_config=""
-  envsubst < CI/config/common_test_config.yaml > CI/config/arca_io_hog.yaml
-  python3 -m coverage run -a run_kraken.py -c CI/config/arca_io_hog.yaml
-  echo "Arcaflow IO Hog: Success"
-}
-
-functional_test_arca_io_hog

CI/tests/test_arca_memory_hog.sh

@@ -1,19 +0,0 @@
-set -xeEo pipefail
-
-source CI/tests/common.sh
-
-trap error ERR
-trap finish EXIT
-
-
-function functional_test_arca_memory_hog {
-  yq -i '.input_list[0].node_selector={"kubernetes.io/hostname":"kind-worker2"}' scenarios/arcaflow/memory-hog/input.yaml
-  export scenario_type="arcaflow_scenarios"
-  export scenario_file="scenarios/arcaflow/memory-hog/input.yaml"
-  export post_config=""
-  envsubst < CI/config/common_test_config.yaml > CI/config/arca_memory_hog.yaml
-  python3 -m coverage run -a run_kraken.py -c CI/config/arca_memory_hog.yaml
-  echo "Arcaflow Memory Hog: Success"
-}
-
-functional_test_arca_memory_hog

CI/tests/test_container.sh

@@ -12,7 +12,7 @@ function functional_test_container_crash {
   yq -i '.scenarios[0].label_selector="scenario=container"' scenarios/openshift/container_etcd.yml
   yq -i '.scenarios[0].container_name="fedtools"' scenarios/openshift/container_etcd.yml
   export scenario_type="container_scenarios"
-  export scenario_file="- scenarios/openshift/container_etcd.yml"
+  export scenario_file="scenarios/openshift/container_etcd.yml"
   export post_config=""
   envsubst < CI/config/common_test_config.yaml > CI/config/container_config.yaml
 

CI/tests/test_cpu_hog.sh

@@ -0,0 +1,20 @@
+set -xeEo pipefail
+
+source CI/tests/common.sh
+
+trap error ERR
+trap finish EXIT
+
+
+function functional_test_cpu_hog {
+  yq -i '.node_selector="kubernetes.io/hostname=kind-worker2"' scenarios/kube/cpu-hog.yml
+
+  export scenario_type="hog_scenarios"
+  export scenario_file="scenarios/kube/cpu-hog.yml"
+  export post_config=""
+  envsubst < CI/config/common_test_config.yaml > CI/config/cpu_hog.yaml
+  python3 -m coverage run -a run_kraken.py -c CI/config/cpu_hog.yaml
+  echo "CPU Hog: Success"
+}
+
+functional_test_cpu_hog

CI/tests/test_io_hog.sh

@@ -0,0 +1,19 @@
+set -xeEo pipefail
+
+source CI/tests/common.sh
+
+trap error ERR
+trap finish EXIT
+
+
+function functional_test_io_hog {
+  yq -i '.node_selector="kubernetes.io/hostname=kind-worker2"' scenarios/kube/io-hog.yml
+  export scenario_type="hog_scenarios"
+  export scenario_file="scenarios/kube/io-hog.yml"
+  export post_config=""
+  envsubst < CI/config/common_test_config.yaml > CI/config/io_hog.yaml
+  python3 -m coverage run -a run_kraken.py -c CI/config/io_hog.yaml
+  echo "IO Hog: Success"
+}
+
+functional_test_io_hog

CI/tests/test_memory_hog.sh

@@ -0,0 +1,19 @@
+set -xeEo pipefail
+
+source CI/tests/common.sh
+
+trap error ERR
+trap finish EXIT
+
+
+function functional_test_memory_hog {
+  yq -i '.node_selector="kubernetes.io/hostname=kind-worker2"' scenarios/kube/memory-hog.yml
+  export scenario_type="hog_scenarios"
+  export scenario_file="scenarios/kube/memory-hog.yml"
+  export post_config=""
+  envsubst < CI/config/common_test_config.yaml > CI/config/memory_hog.yaml
+  python3 -m coverage run -a run_kraken.py -c CI/config/memory_hog.yaml
+  echo "Memory Hog: Success"
+}
+
+functional_test_memory_hog

CI/tests/test_namespace.sh

@@ -6,8 +6,8 @@ trap error ERR
 trap finish EXIT
 
 function funtional_test_namespace_deletion {
-  export scenario_type="namespace_scenarios"
-  export scenario_file="-  scenarios/openshift/ingress_namespace.yaml"
+  export scenario_type="service_disruption_scenarios"
+  export scenario_file="scenarios/openshift/ingress_namespace.yaml"
   export post_config=""
   yq '.scenarios[0].namespace="^namespace-scenario$"' -i scenarios/openshift/ingress_namespace.yaml
   yq '.scenarios[0].wait_time=30' -i scenarios/openshift/ingress_namespace.yaml

CI/tests/test_net_chaos.sh

@@ -15,7 +15,7 @@ function functional_test_network_chaos {
   yq -i 'del(.network_chaos.egress.latency)' scenarios/openshift/network_chaos.yaml
   yq -i 'del(.network_chaos.egress.loss)' scenarios/openshift/network_chaos.yaml
 
-  export scenario_type="network_chaos"
+  export scenario_type="network_chaos_scenarios"
   export scenario_file="scenarios/openshift/network_chaos.yaml"
   export post_config=""
   envsubst < CI/config/common_test_config.yaml > CI/config/network_chaos.yaml

CI/tests/test_service_hijacking.sh

@@ -35,14 +35,21 @@ TEXT_MIME="text/plain; charset=utf-8"
 
 function functional_test_service_hijacking {
 
-  export scenario_type="service_hijacking"
+  export scenario_type="service_hijacking_scenarios"
   export scenario_file="scenarios/kube/service_hijacking.yaml"
   export post_config=""
   envsubst < CI/config/common_test_config.yaml > CI/config/service_hijacking.yaml
   python3 -m coverage run -a run_kraken.py -c CI/config/service_hijacking.yaml  > /dev/null 2>&1 &
   PID=$!
   #Waiting the hijacking to have effect
-  while [ `curl -X GET -s -o /dev/null -I -w "%{http_code}" $SERVICE_URL/list/index.php` == 404 ]; do echo "waiting scenario to kick in."; sleep 1; done;
+  COUNTER=0
+  while [ `curl -X GET -s -o /dev/null -I -w "%{http_code}" $SERVICE_URL/list/index.php` == 404 ]
+   do
+    echo "waiting scenario to kick in."
+    sleep 1
+    COUNTER=$((COUNTER+1))
+    [ $COUNTER -eq "100" ] && echo "maximum number of retry reached, test failed" && exit 1
+  done
 
   #Checking Step 1 GET on /list/index.php
   OUT_GET="`curl -X GET -s $SERVICE_URL/list/index.php`"

CI/tests/test_telemetry.sh

@@ -18,15 +18,16 @@ function functional_test_telemetry {
   yq -i '.performance_monitoring.prometheus_url="http://localhost:9090"' CI/config/common_test_config.yaml
   yq -i '.telemetry.run_tag=env(RUN_TAG)' CI/config/common_test_config.yaml
 
-  export scenario_type="arcaflow_scenarios"
-  export scenario_file="scenarios/arcaflow/cpu-hog/input.yaml"
+  export scenario_type="hog_scenarios"
+
+  export scenario_file="scenarios/kube/cpu-hog.yml"
+
   export post_config=""
   envsubst < CI/config/common_test_config.yaml > CI/config/telemetry.yaml
   retval=$(python3 -m coverage run -a run_kraken.py -c CI/config/telemetry.yaml)
   RUN_FOLDER=`cat CI/out/test_telemetry.out | grep amazonaws.com | sed -rn "s#.*https:\/\/.*\/files/(.*)#\1#p"`
   $AWS_CLI s3 ls "s3://$AWS_BUCKET/$RUN_FOLDER/" | awk '{ print $4 }' > s3_remote_files
   echo "checking if telemetry files are uploaded on s3"
-  cat s3_remote_files | grep events-00.json || ( echo "FAILED: events-00.json not uploaded" && exit 1 )
   cat s3_remote_files | grep critical-alerts-00.log || ( echo "FAILED: critical-alerts-00.log not uploaded"  && exit 1 )
   cat s3_remote_files | grep prometheus-00.tar || ( echo "FAILED: prometheus backup not uploaded"  && exit 1 )
   cat s3_remote_files | grep telemetry.json || ( echo "FAILED: telemetry.json not uploaded"  && exit 1 )

README.md

@@ -2,6 +2,7 @@
 ![Workflow-Status](https://github.com/krkn-chaos/krkn/actions/workflows/docker-image.yml/badge.svg)
 ![coverage](https://krkn-chaos.github.io/krkn-lib-docs/coverage_badge_krkn.svg)
 ![action](https://github.com/krkn-chaos/krkn/actions/workflows/tests.yml/badge.svg)
+[![OpenSSF Best Practices](https://www.bestpractices.dev/projects/10548/badge)](https://www.bestpractices.dev/projects/10548)
 
 ![Krkn logo](media/logo.png)
 
@@ -10,91 +11,15 @@ Kraken injects deliberate failures into Kubernetes clusters to check if it is re
 
 
 ### Workflow
-![Kraken workflow](media/kraken-workflow.png)
-
-### Demo
-[![Kraken demo](media/KrakenStarting.png)](https://youtu.be/LN-fZywp_mo "Kraken Demo - Click to Watch!")
+![Kraken workflow](media/kraken-workflow.png) 
 
 
-### Chaos Testing Guide
-[Guide](docs/index.md) encapsulates:
-- Test methodology that needs to be embraced.
-- Best practices that an Kubernetes cluster, platform and applications running on top of it should take into account for best user experience, performance, resilience and reliability.
-- Tooling.
-- Scenarios supported.
-- Test environment recommendations as to how and where to run chaos tests.
-- Chaos testing in practice.
-
-The guide is hosted at https://krkn-chaos.github.io/krkn.
+<!-- ### Demo
+[![Kraken demo](media/KrakenStarting.png)](https://youtu.be/LN-fZywp_mo "Kraken Demo - Click to Watch!") -->
 
 
 ### How to Get Started
-Instructions on how to setup, configure and run Kraken can be found at [Installation](docs/installation.md).
-
-You may consider utilizing the chaos recommendation tool prior to initiating the chaos runs to profile the application service(s) under test. This tool discovers a list of Krkn scenarios with a high probability of causing failures or disruptions to your application service(s). The tool can be accessed at [Chaos-Recommender](utils/chaos_recommender/README.md).
-
-See the [getting started doc](docs/getting_started.md) on support on how to get started with your own custom scenario or editing current scenarios for your specific usage.
-
-After installation, refer back to the below sections for supported scenarios and how to tweak the kraken config to load them on your cluster.
-
-
-#### Running Kraken with minimal configuration tweaks
-For cases where you want to run Kraken with minimal configuration changes, refer to [krkn-hub](https://github.com/krkn-chaos/krkn-hub). One use case is CI integration where you do not want to carry around different configuration files for the scenarios.
-
-
-### Config
-Instructions on how to setup the config and the options supported can be found at [Config](docs/config.md).
-
-
-### Kubernetes chaos scenarios supported
-
-Scenario type               | Kubernetes    
---------------------------- | ------------- | 
-[Pod Scenarios](docs/pod_scenarios.md) | :heavy_check_mark: |
-[Pod Network Scenarios](docs/pod_network_scenarios.md) | :x: |
-[Container Scenarios](docs/container_scenarios.md) | :heavy_check_mark: |
-[Node Scenarios](docs/node_scenarios.md) | :heavy_check_mark: |
-[Time Scenarios](docs/time_scenarios.md) | :heavy_check_mark: |
-[Hog Scenarios: CPU, Memory](docs/arcaflow_scenarios.md) | :heavy_check_mark: |
-[Cluster Shut Down Scenarios](docs/cluster_shut_down_scenarios.md) | :heavy_check_mark: |
-[Service Disruption Scenarios](docs/service_disruption_scenarios.md.md) | :heavy_check_mark: |
-[Zone Outage Scenarios](docs/zone_outage.md) | :heavy_check_mark: |
-[Application_outages](docs/application_outages.md) | :heavy_check_mark: |
-[PVC scenario](docs/pvc_scenario.md) | :heavy_check_mark: |
-[Network_Chaos](docs/network_chaos.md) | :heavy_check_mark: |
-[ManagedCluster Scenarios](docs/managedcluster_scenarios.md) | :heavy_check_mark: |
-[Service Hijacking Scenarios](docs/service_hijacking_scenarios.md) | :heavy_check_mark: |
-[SYN Flood Scenarios](docs/syn_flood_scenarios.md) | :heavy_check_mark: |
-
-
-### Kraken scenario pass/fail criteria and report
-It is important to make sure to check if the targeted component recovered from the chaos injection and also if the Kubernetes cluster is healthy as failures in one component can have an adverse impact on other components. Kraken does this by:
-- Having built in checks for pod and node based scenarios to ensure the expected number of replicas and nodes are up. It also supports running custom scripts with the checks.
-- Leveraging [Cerberus](https://github.com/krkn-chaos/cerberus) to monitor the cluster under test and consuming the aggregated go/no-go signal to determine pass/fail post chaos. It is highly recommended to turn on the Cerberus health check feature available in Kraken. Instructions on installing and setting up Cerberus can be found [here](https://github.com/openshift-scale/cerberus#installation) or can be installed from Kraken using the [instructions](https://github.com/krkn-chaos/krkn#setting-up-infrastructure-dependencies). Once Cerberus is up and running, set cerberus_enabled to True and cerberus_url to the url where Cerberus publishes go/no-go signal in the Kraken config file. Cerberus can monitor [application routes](https://github.com/redhat-chaos/cerberus/blob/main/docs/config.md#watch-routes) during the chaos and fails the run if it encounters downtime as it is a potential downtime in a customers, or users environment as well. It is especially important during the control plane chaos scenarios including the API server, Etcd, Ingress etc. It can be enabled by setting `check_applicaton_routes: True` in the [Kraken config](https://github.com/redhat-chaos/krkn/blob/main/config/config.yaml) provided application routes are being monitored in the [cerberus config](https://github.com/redhat-chaos/krkn/blob/main/config/cerberus.yaml).
-- Leveraging built-in alert collection feature to fail the runs in case of critical alerts.
-
-### Signaling
-In CI runs or any external job it is useful to stop Kraken once a certain test or state gets reached. We created a way to signal to kraken to pause the chaos or stop it completely using a signal posted to a port of your choice.
-
-For example if we have a test run loading the cluster running and kraken separately running; we want to be able to know when to start/stop the kraken run based on when the test run completes or gets to a certain loaded state.
-
-More detailed information on enabling and leveraging this feature can be found [here](docs/signal.md).
-
-
-### Performance monitoring
-Monitoring the Kubernetes/OpenShift cluster to observe the impact of Kraken chaos scenarios on various components is key to find out the bottlenecks as it is important to make sure the cluster is healthy in terms if both recovery as well as performance during/after the failure has been injected. Instructions on enabling it can be found [here](docs/performance_dashboards.md).
-
-
-### SLOs validation during and post chaos
-- In addition to checking the recovery and health of the cluster and components under test, Kraken takes in a profile with the Prometheus expressions to validate and alerts, exits with a non-zero return code depending on the severity set. This feature can be used to determine pass/fail or alert on abnormalities observed in the cluster based on the metrics. 
-- Kraken also provides ability to check if any critical alerts are firing in the cluster post chaos and pass/fail's. 
-
-Information on enabling and leveraging this feature can be found [here](docs/SLOs_validation.md)
-
-
-### OCM / ACM integration
-
-Kraken supports injecting faults into [Open Cluster Management (OCM)](https://open-cluster-management.io/) and [Red Hat Advanced Cluster Management for Kubernetes (ACM)](https://www.krkn.com/en/technologies/management/advanced-cluster-management) managed clusters through [ManagedCluster Scenarios](docs/managedcluster_scenarios.md).
+Instructions on how to setup, configure and run Kraken can be found in the [documentation](https://krkn-chaos.dev/docs/).
 
 
 ### Blogs and other useful resources
@@ -106,6 +31,7 @@ Kraken supports injecting faults into [Open Cluster Management (OCM)](https://op
 - Blog post on supercharging chaos testing using AI integration in Krkn: https://www.redhat.com/en/blog/supercharging-chaos-testing-using-ai
 - Blog post announcing Krkn joining CNCF Sandbox: https://www.redhat.com/en/blog/krknchaos-joining-cncf-sandbox
 
+
 ### Roadmap
 Enhancements being planned can be found in the [roadmap](ROADMAP.md).
 
@@ -113,10 +39,7 @@ Enhancements being planned can be found in the [roadmap](ROADMAP.md).
 ### Contributions
 We are always looking for more enhancements, fixes to make it better, any contributions are most welcome. Feel free to report or work on the issues filed on github.
 
-[More information on how to Contribute](docs/contribute.md)
-
-If adding a new scenario or tweaking the main config, be sure to add in updates into the CI to be sure the CI is up to date.
-Please read [this file]((CI/README.md#adding-a-test-case)) for more information on updates.
+[More information on how to Contribute](https://krkn-chaos.dev/docs/contribution-guidelines/)
 
 
 ### Community

ROADMAP.md

@@ -6,10 +6,11 @@ Following are a list of enhancements that we are planning to work on adding supp
 - [x] [Centralized storage for chaos experiments artifacts](https://github.com/krkn-chaos/krkn/issues/423)
 - [ ] [Support for causing DNS outages](https://github.com/krkn-chaos/krkn/issues/394)
 - [x] [Chaos recommender](https://github.com/krkn-chaos/krkn/tree/main/utils/chaos-recommender) to suggest scenarios having probability of impacting the service under test using profiling results 
-- [ ] Chaos AI integration to improve and automate test coverage
+- [] Chaos AI integration to improve test coverage while reducing fault space to save costs and execution time
 - [x] [Support for pod level network traffic shaping](https://github.com/krkn-chaos/krkn/issues/393)
 - [ ] [Ability to visualize the metrics that are being captured by Kraken and stored in Elasticsearch](https://github.com/krkn-chaos/krkn/issues/124)
-- [ ] Support for running all the scenarios of Kraken on Kubernetes distribution - see https://github.com/krkn-chaos/krkn/issues/185, https://github.com/redhat-chaos/krkn/issues/186
-- [ ] Continue to improve [Chaos Testing Guide](https://krkn-chaos.github.io/krkn) in terms of adding best practices, test environment recommendations and scenarios to make sure the OpenShift platform, as well the applications running on top it, are resilient and performant under chaotic conditions.
-- [ ] [Switch documentation references to Kubernetes](https://github.com/krkn-chaos/krkn/issues/495)
-- [ ] [OCP and Kubernetes functionalities segregation](https://github.com/krkn-chaos/krkn/issues/497)
+- [x] Support for running all the scenarios of Kraken on Kubernetes distribution - see https://github.com/krkn-chaos/krkn/issues/185, https://github.com/redhat-chaos/krkn/issues/186
+- [x] Continue to improve [Chaos Testing Guide](https://krkn-chaos.github.io/krkn) in terms of adding best practices, test environment recommendations and scenarios to make sure the OpenShift platform, as well the applications running on top it, are resilient and performant under chaotic conditions.
+- [x] [Switch documentation references to Kubernetes](https://github.com/krkn-chaos/krkn/issues/495)
+- [x] [OCP and Kubernetes functionalities segregation](https://github.com/krkn-chaos/krkn/issues/497)
+- [x] [Krknctl - client for running Krkn scenarios with ease](https://github.com/krkn-chaos/krknctl)

SECURITY.md

@@ -0,0 +1,43 @@
+# Security Policy
+
+We attach great importance to code security. We are very grateful to the users, security vulnerability researchers, etc. for reporting security vulnerabilities to the Krkn community. All reported security vulnerabilities will be carefully assessed and addressed in a timely manner.
+
+
+## Security Checks
+
+Krkn leverages [Snyk](https://snyk.io/) to ensure that any security vulnerabilities found 
+in the code base and dependencies are fixed and published in the latest release. Security 
+vulnerability checks are enabled for each pull request to enable developers to get insights 
+and proactively fix them.
+
+ 
+## Reporting a Vulnerability
+
+The Krkn project treats security vulnerabilities seriously, so we
+strive to take action quickly when required.
+
+The project requests that security issues be disclosed in a responsible
+manner to allow adequate time to respond.  If a security issue or
+vulnerability has been found, please disclose the details to our
+dedicated email address:
+
+cncf-krkn-maintainers@lists.cncf.io
+
+You can also use the [GitHub vulnerability report mechanism](https://docs.github.com/en/code-security/security-advisories/guidance-on-reporting-and-writing-information-about-vulnerabilities/privately-reporting-a-security-vulnerability#privately-reporting-a-security-vulnerability) to report the security vulnerability.
+
+Please include as much information as possible with the report. The
+following details assist with analysis efforts:
+  - Description of the vulnerability
+  - Affected component (version, commit, branch etc)
+  - Affected code (file path, line numbers)
+  - Exploit code
+
+
+## Security Team
+
+The security team currently consists of the [Maintainers of Krkn](https://github.com/krkn-chaos/krkn/blob/main/MAINTAINERS.md)
+
+
+## Process and Supported Releases
+
+The Krkn security team will investigate and provide a fix in a timely mannner depending on the severity. The fix will be included in the new release of Krkn and details will be included in the release notes.

config/config.yaml

@@ -1,6 +1,5 @@
 kraken:
-    distribution: kubernetes                                # Distribution can be kubernetes or openshift
-    kubeconfig_path: ~/.kube/config                        # Path to kubeconfig
+    kubeconfig_path: ~/.kube/config                     # Path to kubeconfig
     exit_on_failure: False                                 # Exit when a post action scenario fails
     publish_kraken_status: True                            # Can be accessed at http://0.0.0.0:8081
     signal_state: RUN                                      # Will wait for the RUN signal when set to PAUSE before running the scenarios, refer docs/signal.md for more details
@@ -8,44 +7,46 @@ kraken:
     port: 8081                                             # Signal port
     chaos_scenarios:
         # List of policies/chaos scenarios to load
-        - arcaflow_scenarios:
-            - scenarios/arcaflow/cpu-hog/input.yaml
-            - scenarios/arcaflow/memory-hog/input.yaml
-            - scenarios/arcaflow/io-hog/input.yaml
-        - application_outages:
+        - hog_scenarios:
+            - scenarios/kube/cpu-hog.yml
+            - scenarios/kube/memory-hog.yml
+            - scenarios/kube/io-hog.yml
+        - application_outages_scenarios:
             - scenarios/openshift/app_outage.yaml
         - container_scenarios:                             # List of chaos pod scenarios to load
-            - - scenarios/openshift/container_etcd.yml
-        - plugin_scenarios:
+            - scenarios/openshift/container_etcd.yml
+        - pod_network_scenarios:
+              - scenarios/openshift/network_chaos_ingress.yml
+              - scenarios/openshift/pod_network_outage.yml
+        - pod_disruption_scenarios:
             - scenarios/openshift/etcd.yml
             - scenarios/openshift/regex_openshift_pod_kill.yml
-            - scenarios/openshift/vmware_node_scenarios.yml
-            - scenarios/openshift/network_chaos_ingress.yml
             - scenarios/openshift/prom_kill.yml
-        - node_scenarios:                                  # List of chaos node scenarios to load
-            - scenarios/openshift/node_scenarios_example.yml
-        - plugin_scenarios:
             - scenarios/openshift/openshift-apiserver.yml
             - scenarios/openshift/openshift-kube-apiserver.yml
+        - node_scenarios:                                  # List of chaos node scenarios to load
+            - scenarios/openshift/aws_node_scenarios.yml
+            - scenarios/openshift/vmware_node_scenarios.yml
+            - scenarios/openshift/ibmcloud_node_scenarios.yml
         - time_scenarios:                                  # List of chaos time scenarios to load
             - scenarios/openshift/time_scenarios_example.yml
         - cluster_shut_down_scenarios:
-            - - scenarios/openshift/cluster_shut_down_scenario.yml
-              - scenarios/openshift/post_action_shut_down.py
+            - scenarios/openshift/cluster_shut_down_scenario.yml
         - service_disruption_scenarios:
-             - - scenarios/openshift/regex_namespace.yaml
-             - - scenarios/openshift/ingress_namespace.yaml
-               - scenarios/openshift/post_action_namespace.py
-        - zone_outages:
+             - scenarios/openshift/regex_namespace.yaml
+             - scenarios/openshift/ingress_namespace.yaml
+        - zone_outages_scenarios:
             - scenarios/openshift/zone_outage.yaml
         - pvc_scenarios:
             - scenarios/openshift/pvc_scenario.yaml
-        - network_chaos:
+        - network_chaos_scenarios:
             - scenarios/openshift/network_chaos.yaml
-        - service_hijacking:
+        - service_hijacking_scenarios:
               - scenarios/kube/service_hijacking.yaml
-        - syn_flood:
+        - syn_flood_scenarios:
               - scenarios/kube/syn_flood.yaml
+        -  network_chaos_ng_scenarios:
+               - scenarios/kube/network-filter.yml
 
 cerberus:
     cerberus_enabled: False                                # Enable it when cerberus is previously installed
@@ -55,12 +56,25 @@ cerberus:
 performance_monitoring:
     deploy_dashboards: False                              # Install a mutable grafana and load the performance dashboards. Enable this only when running on OpenShift
     repo: "https://github.com/cloud-bulldozer/performance-dashboards.git"
-    prometheus_url:                                      # The prometheus url/route is automatically obtained in case of OpenShift, please set it when the distribution is Kubernetes.
+    prometheus_url: ''                                      # The prometheus url/route is automatically obtained in case of OpenShift, please set it when the distribution is Kubernetes.
     prometheus_bearer_token:                              # The bearer token is automatically obtained in case of OpenShift, please set it when the distribution is Kubernetes. This is needed to authenticate with prometheus.
     uuid:                                                 # uuid for the run is generated by default if not set
     enable_alerts: False                                  # Runs the queries specified in the alert profile and displays the info or exits 1 when severity=error
+    enable_metrics: False
     alert_profile: config/alerts.yaml                          # Path or URL to alert profile with the prometheus queries
+    metrics_profile: config/metrics-report.yaml
     check_critical_alerts: False                          # When enabled will check prometheus for critical alerts firing post chaos
+elastic:
+    enable_elastic: False
+    verify_certs: False
+    elastic_url: ""                                         # To track results in elasticsearch, give url to server here; will post telemetry details when url and index not blank
+    elastic_port: 32766
+    username: "elastic"
+    password: "test"
+    metrics_index: "krkn-metrics"
+    alerts_index: "krkn-alerts"
+    telemetry_index: "krkn-telemetry"
+
 tunings:
     wait_duration: 60                                      # Duration to wait between each chaos scenario
     iterations: 1                                          # Number of times to execute the scenarios
@@ -94,10 +108,11 @@ telemetry:
      - "(\\d{4}-\\d{2}-\\d{2}T\\d{2}:\\d{2}:\\d{2}\\.\\d+Z).+"      # 2023-09-15T11:20:36.123425532Z log
     oc_cli_path: /usr/bin/oc                                # optional, if not specified will be search in $PATH
     events_backup: True                                     # enables/disables cluster events collection
-elastic: 
-    elastic_url: ""                                         # To track results in elasticsearch, give url to server here; will post telemetry details when url and index not blank
-    elastic_index: ""                                       # Elastic search index pattern to post results to
-
-
-
 
+health_checks:                                              # Utilizing health check endpoints to observe application behavior during chaos injection.
+    interval:                                               # Interval in seconds to perform health checks, default value is 2 seconds
+    config:                                                 # Provide list of health check configurations for applications
+        - url:                                              # Provide application endpoint
+          bearer_token:                                     # Bearer token for authentication if any
+          auth:                                             # Provide authentication credentials (username , password) in tuple format if any, ex:("admin","secretpassword")
+          exit_on_failure:                                  # If value is True exits when health check failed for application, values can be True/False

config/config_kind.yaml

@@ -6,7 +6,7 @@ kraken:
     publish_kraken_status: True                            # Can be accessed at http://0.0.0.0:8081
     signal_state: RUN                                      # Will wait for the RUN signal when set to PAUSE before running the scenarios, refer docs/signal.md for more details
     signal_address: 0.0.0.0                                # Signal listening address
-   chaos_scenarios:                                       # List of policies/chaos scenarios to load
+    chaos_scenarios:                                       # List of policies/chaos scenarios to load
         - plugin_scenarios:
             - scenarios/kind/scheduler.yml
         - node_scenarios:

config/config_kubernetes.yaml

@@ -7,7 +7,7 @@ kraken:
     signal_state: RUN                                      # Will wait for the RUN signal when set to PAUSE before running the scenarios, refer docs/signal.md for more details
     chaos_scenarios:                                       # List of policies/chaos scenarios to load
         -   container_scenarios:                                 # List of chaos pod scenarios to load
-            - -    scenarios/kube/container_dns.yml
+            - scenarios/kube/container_dns.yml
         -   plugin_scenarios:
             - scenarios/kube/scheduler.yml
 

config/config_performance.yaml

@@ -12,15 +12,14 @@ kraken:
             - scenarios/openshift/regex_openshift_pod_kill.yml
             - scenarios/openshift/prom_kill.yml
         -   node_scenarios:                                # List of chaos node scenarios to load
-            -   scenarios/openshift/node_scenarios_example.yml
+            -  scenarios/openshift/node_scenarios_example.yml
         -   plugin_scenarios:
             - scenarios/openshift/openshift-apiserver.yml
             - scenarios/openshift/openshift-kube-apiserver.yml
         -   time_scenarios:                                # List of chaos time scenarios to load
             - scenarios/openshift/time_scenarios_example.yml
         -   cluster_shut_down_scenarios:
-            - - scenarios/openshift/cluster_shut_down_scenario.yml
-              - scenarios/openshift/post_action_shut_down.py
+            - scenarios/openshift/cluster_shut_down_scenario.yml
         -   service_disruption_scenarios:
             - scenarios/openshift/regex_namespace.yaml
             - scenarios/openshift/ingress_namespace.yaml

config/metrics-aggregated.yaml

@@ -1,133 +1,126 @@
 metrics:
 # API server
-  - query: histogram_quantile(0.99, sum(rate(apiserver_request_duration_seconds_bucket{apiserver="kube-apiserver", verb!~"WATCH", subresource!="log"}[2m])) by (verb,resource,subresource,instance,le)) > 0
-    metricName: API99thLatency
-
   - query: sum(irate(apiserver_request_total{apiserver="kube-apiserver",verb!="WATCH",subresource!="log"}[2m])) by (verb,instance,resource,code) > 0
     metricName: APIRequestRate
+    instant: True
 
   - query: sum(apiserver_current_inflight_requests{}) by (request_kind) > 0
     metricName: APIInflightRequests
+    instant: True
+
+  - query: histogram_quantile(0.99, rate(apiserver_current_inflight_requests[5m]))
+    metricName: APIInflightRequests
+    instant: True
 
 # Container & pod metrics
   - query: (sum(container_memory_rss{name!="",container!="POD",namespace=~"openshift-(etcd|oauth-apiserver|.*apiserver|ovn-kubernetes|sdn|ingress|authentication|.*controller-manager|.*scheduler)"}) by (container, pod, namespace, node) and on (node) kube_node_role{role="master"}) > 0
     metricName: containerMemory-Masters
+    instant: true
 
   - query: (sum(irate(container_cpu_usage_seconds_total{name!="",container!="POD",namespace=~"openshift-(etcd|oauth-apiserver|sdn|ovn-kubernetes|.*apiserver|authentication|.*controller-manager|.*scheduler)"}[2m]) * 100) by (container, pod, namespace, node) and on (node) kube_node_role{role="master"}) > 0
     metricName: containerCPU-Masters
+    instant: true
 
   - query: (sum(irate(container_cpu_usage_seconds_total{pod!="",container="prometheus",namespace="openshift-monitoring"}[2m]) * 100) by (container, pod, namespace, node) and on (node) kube_node_role{role="infra"}) > 0
     metricName: containerCPU-Prometheus
+    instant: true
 
   - query: (avg(irate(container_cpu_usage_seconds_total{name!="",container!="POD",namespace=~"openshift-(sdn|ovn-kubernetes|ingress)"}[2m]) * 100 and on (node) kube_node_role{role="worker"}) by (namespace, container)) > 0
     metricName: containerCPU-AggregatedWorkers
+    instant: true
 
   - query: (avg(irate(container_cpu_usage_seconds_total{name!="",container!="POD",namespace=~"openshift-(sdn|ovn-kubernetes|ingress|monitoring|image-registry|logging)"}[2m]) * 100 and on (node) kube_node_role{role="infra"}) by (namespace, container)) > 0
     metricName: containerCPU-AggregatedInfra
 
   - query: (sum(container_memory_rss{pod!="",namespace="openshift-monitoring",name!="",container="prometheus"}) by (container, pod, namespace, node) and on (node) kube_node_role{role="infra"}) > 0
     metricName: containerMemory-Prometheus
+    instant: True
 
   - query: avg(container_memory_rss{name!="",container!="POD",namespace=~"openshift-(sdn|ovn-kubernetes|ingress)"} and on (node) kube_node_role{role="worker"}) by (container, namespace)
     metricName: containerMemory-AggregatedWorkers
+    instant: True
 
   - query: avg(container_memory_rss{name!="",container!="POD",namespace=~"openshift-(sdn|ovn-kubernetes|ingress|monitoring|image-registry|logging)"} and on (node) kube_node_role{role="infra"}) by (container, namespace)
     metricName: containerMemory-AggregatedInfra
+    instant: True
 
 # Node metrics
   - query: (sum(irate(node_cpu_seconds_total[2m])) by (mode,instance) and on (instance) label_replace(kube_node_role{role="master"}, "instance", "$1", "node", "(.+)")) > 0
     metricName: nodeCPU-Masters
+    instant: True
+
+  - query: max(max_over_time(sum(irate(node_cpu_seconds_total{mode!="idle", mode!="steal"}[2m]) and on (instance) label_replace(kube_node_role{role="master"}, "instance", "$1", "node", "(.+)")) by (instance)[.elapsed:]))
+    metricName: maxCPU-Masters
+    instant: true
+  
+  - query: avg(avg_over_time((node_memory_MemTotal_bytes - node_memory_MemAvailable_bytes)[.elapsed:]) and on (instance) label_replace(kube_node_role{role="master"}, "instance", "$1", "node", "(.+)"))
+    metricName: nodeMemory-Masters
+    instant: true
 
   - query: (avg((sum(irate(node_cpu_seconds_total[2m])) by (mode,instance) and on (instance) label_replace(kube_node_role{role="worker"}, "instance", "$1", "node", "(.+)"))) by (mode)) > 0
     metricName: nodeCPU-AggregatedWorkers
+    instant: True
 
   - query: (avg((sum(irate(node_cpu_seconds_total[2m])) by (mode,instance) and on (instance) label_replace(kube_node_role{role="infra"}, "instance", "$1", "node", "(.+)"))) by (mode)) > 0
     metricName: nodeCPU-AggregatedInfra
+    instant: True
 
-  - query: avg(node_memory_MemAvailable_bytes) by (instance) and on (instance) label_replace(kube_node_role{role="master"}, "instance", "$1", "node", "(.+)")
-    metricName: nodeMemoryAvailable-Masters
+  - query: avg(avg_over_time((node_memory_MemTotal_bytes - node_memory_MemAvailable_bytes)[.elapsed:]) and on (instance) label_replace(kube_node_role{role="master"}, "instance", "$1", "node", "(.+)"))
+    metricName: nodeMemory-Masters
+    instant: true
+
+  - query: max(max_over_time((node_memory_MemTotal_bytes - node_memory_MemAvailable_bytes)[.elapsed:]) and on (instance) label_replace(kube_node_role{role="master"}, "instance", "$1", "node", "(.+)"))
+    metricName: maxMemory-Masters
+    instant: true
 
   - query: avg(node_memory_MemAvailable_bytes and on (instance) label_replace(kube_node_role{role="worker"}, "instance", "$1", "node", "(.+)"))
     metricName: nodeMemoryAvailable-AggregatedWorkers
+    instant: True
+
+  - query: max(max_over_time(sum(irate(node_cpu_seconds_total{mode!="idle", mode!="steal"}[2m]) and on (instance) label_replace(kube_node_role{role="worker"}, "instance", "$1", "node", "(.+)")) by (instance)[.elapsed:]))
+    metricName: maxCPU-Workers
+    instant: true
+  
+  - query: max(max_over_time((node_memory_MemTotal_bytes - node_memory_MemAvailable_bytes)[.elapsed:]) and on (instance) label_replace(kube_node_role{role="worker"}, "instance", "$1", "node", "(.+)"))
+    metricName: maxMemory-Workers
+    instant: true
 
   - query: avg(node_memory_MemAvailable_bytes and on (instance) label_replace(kube_node_role{role="infra"}, "instance", "$1", "node", "(.+)"))
     metricName: nodeMemoryAvailable-AggregatedInfra
+    instant: True
 
   - query: avg(node_memory_Active_bytes) by (instance) and on (instance) label_replace(kube_node_role{role="master"}, "instance", "$1", "node", "(.+)")
     metricName: nodeMemoryActive-Masters
+    instant: True
 
   - query: avg(node_memory_Active_bytes and on (instance) label_replace(kube_node_role{role="worker"}, "instance", "$1", "node", "(.+)"))
     metricName: nodeMemoryActive-AggregatedWorkers
+    instant: True
 
   - query: avg(avg(node_memory_Active_bytes) by (instance) and on (instance) label_replace(kube_node_role{role="infra"}, "instance", "$1", "node", "(.+)"))
     metricName: nodeMemoryActive-AggregatedInfra
-
-  - query: avg(node_memory_Cached_bytes) by (instance) + avg(node_memory_Buffers_bytes) by (instance) and on (instance) label_replace(kube_node_role{role="master"}, "instance", "$1", "node", "(.+)")
-    metricName: nodeMemoryCached+nodeMemoryBuffers-Masters
-
-  - query: avg(node_memory_Cached_bytes + node_memory_Buffers_bytes and on (instance) label_replace(kube_node_role{role="worker"}, "instance", "$1", "node", "(.+)"))
-    metricName: nodeMemoryCached+nodeMemoryBuffers-AggregatedWorkers
-
-  - query: avg(node_memory_Cached_bytes + node_memory_Buffers_bytes and on (instance) label_replace(kube_node_role{role="infra"}, "instance", "$1", "node", "(.+)"))
-    metricName: nodeMemoryCached+nodeMemoryBuffers-AggregatedInfra
-
-  - query: irate(node_network_receive_bytes_total{device=~"^(ens|eth|bond|team).*"}[2m]) and on (instance) label_replace(kube_node_role{role="master"}, "instance", "$1", "node", "(.+)")
-    metricName: rxNetworkBytes-Masters
-
-  - query: avg(irate(node_network_receive_bytes_total{device=~"^(ens|eth|bond|team).*"}[2m]) and on (instance) label_replace(kube_node_role{role="worker"}, "instance", "$1", "node", "(.+)")) by (device)
-    metricName: rxNetworkBytes-AggregatedWorkers
-
-  - query: avg(irate(node_network_receive_bytes_total{device=~"^(ens|eth|bond|team).*"}[2m]) and on (instance) label_replace(kube_node_role{role="infra"}, "instance", "$1", "node", "(.+)")) by (device)
-    metricName: rxNetworkBytes-AggregatedInfra
-
-  - query: irate(node_network_transmit_bytes_total{device=~"^(ens|eth|bond|team).*"}[2m]) and on (instance) label_replace(kube_node_role{role="master"}, "instance", "$1", "node", "(.+)")
-    metricName: txNetworkBytes-Masters
-
-  - query: avg(irate(node_network_transmit_bytes_total{device=~"^(ens|eth|bond|team).*"}[2m]) and on (instance) label_replace(kube_node_role{role="worker"}, "instance", "$1", "node", "(.+)")) by (device)
-    metricName: txNetworkBytes-AggregatedWorkers
-
-  - query: avg(irate(node_network_transmit_bytes_total{device=~"^(ens|eth|bond|team).*"}[2m]) and on (instance) label_replace(kube_node_role{role="infra"}, "instance", "$1", "node", "(.+)")) by (device)
-    metricName: txNetworkBytes-AggregatedInfra
-
-  - query: rate(node_disk_written_bytes_total{device!~"^(dm|rb).*"}[2m]) and on (instance) label_replace(kube_node_role{role="master"}, "instance", "$1", "node", "(.+)")
-    metricName: nodeDiskWrittenBytes-Masters
-
-  - query: avg(rate(node_disk_written_bytes_total{device!~"^(dm|rb).*"}[2m]) and on (instance) label_replace(kube_node_role{role="worker"}, "instance", "$1", "node", "(.+)")) by (device)
-    metricName: nodeDiskWrittenBytes-AggregatedWorkers
-
-  - query: avg(rate(node_disk_written_bytes_total{device!~"^(dm|rb).*"}[2m]) and on (instance) label_replace(kube_node_role{role="infra"}, "instance", "$1", "node", "(.+)")) by (device)
-    metricName: nodeDiskWrittenBytes-AggregatedInfra
-
-  - query: rate(node_disk_read_bytes_total{device!~"^(dm|rb).*"}[2m]) and on (instance) label_replace(kube_node_role{role="master"}, "instance", "$1", "node", "(.+)")
-    metricName: nodeDiskReadBytes-Masters
-
-  - query: avg(rate(node_disk_read_bytes_total{device!~"^(dm|rb).*"}[2m]) and on (instance) label_replace(kube_node_role{role="worker"}, "instance", "$1", "node", "(.+)")) by (device)
-    metricName: nodeDiskReadBytes-AggregatedWorkers
-
-  - query: avg(rate(node_disk_read_bytes_total{device!~"^(dm|rb).*"}[2m]) and on (instance) label_replace(kube_node_role{role="infra"}, "instance", "$1", "node", "(.+)")) by (device)
-    metricName: nodeDiskReadBytes-AggregatedInfra
+    instant: True
 
 # Etcd metrics
   - query: sum(rate(etcd_server_leader_changes_seen_total[2m]))
     metricName: etcdLeaderChangesRate
+    instant: True
 
   - query: etcd_server_is_leader > 0
     metricName: etcdServerIsLeader
+    instant: True
 
   - query: histogram_quantile(0.99, rate(etcd_disk_backend_commit_duration_seconds_bucket[2m]))
     metricName: 99thEtcdDiskBackendCommitDurationSeconds
+    instant: True
 
   - query: histogram_quantile(0.99, rate(etcd_disk_wal_fsync_duration_seconds_bucket[2m]))
     metricName: 99thEtcdDiskWalFsyncDurationSeconds
+    instant: True
 
   - query: histogram_quantile(0.99, rate(etcd_network_peer_round_trip_time_seconds_bucket[5m]))
     metricName: 99thEtcdRoundTripTimeSeconds
-
-  - query: etcd_mvcc_db_total_size_in_bytes
-    metricName: etcdDBPhysicalSizeBytes
-
-  - query: etcd_mvcc_db_total_size_in_use_in_bytes
-    metricName: etcdDBLogicalSizeBytes
+    instant: True
 
   - query: sum by (cluster_version)(etcd_cluster_version)
     metricName: etcdVersion
@@ -135,83 +128,16 @@ metrics:
 
   - query: sum(rate(etcd_object_counts{}[5m])) by (resource) > 0
     metricName: etcdObjectCount
+    instant: True
 
   - query: histogram_quantile(0.99,sum(rate(etcd_request_duration_seconds_bucket[2m])) by (le,operation,apiserver)) > 0
     metricName: P99APIEtcdRequestLatency
-
-  - query: sum(grpc_server_started_total{namespace="openshift-etcd",grpc_service="etcdserverpb.Watch",grpc_type="bidi_stream"}) - sum(grpc_server_handled_total{namespace="openshift-etcd",grpc_service="etcdserverpb.Watch",grpc_type="bidi_stream"})
-    metricName: ActiveWatchStreams
-
-  - query: sum(grpc_server_started_total{namespace="openshift-etcd",grpc_service="etcdserverpb.Lease",grpc_type="bidi_stream"}) - sum(grpc_server_handled_total{namespace="openshift-etcd",grpc_service="etcdserverpb.Lease",grpc_type="bidi_stream"})
-    metricName: ActiveLeaseStreams
-
-  - query: sum(rate(etcd_debugging_snap_save_total_duration_seconds_sum{namespace="openshift-etcd"}[2m]))
-    metricName: snapshotSaveLatency
-
-  - query: sum(rate(etcd_server_heartbeat_send_failures_total{namespace="openshift-etcd"}[2m]))
-    metricName: HeartBeatFailures
-
-  - query: sum(rate(etcd_server_health_failures{namespace="openshift-etcd"}[2m]))
-    metricName: HealthFailures
-
-  - query: sum(rate(etcd_server_slow_apply_total{namespace="openshift-etcd"}[2m]))
-    metricName: SlowApplies
-
-  - query: sum(rate(etcd_server_slow_read_indexes_total{namespace="openshift-etcd"}[2m]))
-    metricName: SlowIndexRead
-
-  - query: sum(etcd_server_proposals_pending)
-    metricName: PendingProposals
-
-  - query: histogram_quantile(1.0, sum(rate(etcd_debugging_mvcc_db_compaction_pause_duration_milliseconds_bucket[1m])) by (le, instance))
-    metricName: CompactionMaxPause
+    instant: True
 
   - query: sum by (instance) (apiserver_storage_objects)
     metricName: etcdTotalObjectCount 
+    instant: True
 
   - query: topk(500, max by(resource) (apiserver_storage_objects))
     metricName: etcdTopObectCount    
-
-# Cluster metrics
-  - query: count(kube_namespace_created)
-    metricName: namespaceCount
-
-  - query: sum(kube_pod_status_phase{}) by (phase)
-    metricName: podStatusCount
-
-  - query: count(kube_secret_info{})
-    metricName: secretCount
-
-  - query: count(kube_deployment_labels{})
-    metricName: deploymentCount
-
-  - query: count(kube_configmap_info{})
-    metricName: configmapCount
-
-  - query: count(kube_service_info{})
-    metricName: serviceCount
-
-  - query: kube_node_role
-    metricName: nodeRoles
-    instant: true
-
-  - query: sum(kube_node_status_condition{status="true"}) by (condition)
-    metricName: nodeStatus
-
-  - query: (sum(rate(container_fs_writes_bytes_total{container!="",device!~".+dm.+"}[5m])) by (device, container, node) and on (node) kube_node_role{role="master"}) > 0
-    metricName: containerDiskUsage
-
-  - query: cluster_version{type="completed"}
-    metricName: clusterVersion
-    instant: true
-
-# Golang metrics
-
-  - query: go_memstats_heap_alloc_bytes{job=~"apiserver|api|etcd"}
-    metricName: goHeapAllocBytes
-
-  - query: go_memstats_heap_inuse_bytes{job=~"apiserver|api|etcd"}
-    metricName: goHeapInuseBytes
-
-  - query: go_gc_duration_seconds{job=~"apiserver|api|etcd",quantile="1"}
-    metricName: goGCDurationSeconds
+    instant: True

config/metrics-report.yaml

@@ -0,0 +1,248 @@
+metrics:
+
+# API server
+- query: sum(apiserver_current_inflight_requests{}) by (request_kind) > 0
+  metricName: APIInflightRequests
+  instant: true
+
+# Kubelet & CRI-O
+
+# Average and max of the CPU usage from all worker's kubelet
+- query: avg(avg_over_time(irate(process_cpu_seconds_total{service="kubelet",job="kubelet"}[2m])[.elapsed:]) and on (node) kube_node_role{role="worker"})
+  metricName: cpu-kubelet
+  instant: true
+
+- query: max(max_over_time(irate(process_cpu_seconds_total{service="kubelet",job="kubelet"}[2m])[.elapsed:]) and on (node) kube_node_role{role="worker"})
+  metricName: max-cpu-kubelet
+  instant: true
+
+# Average of the memory usage from all worker's kubelet
+- query: avg(avg_over_time(process_resident_memory_bytes{service="kubelet",job="kubelet"}[.elapsed:]) and on (node) kube_node_role{role="worker"})
+  metricName: memory-kubelet
+  instant: true
+
+# Max of the memory usage from all worker's kubelet
+- query: max(max_over_time(process_resident_memory_bytes{service="kubelet",job="kubelet"}[.elapsed:]) and on (node) kube_node_role{role="worker"})
+  metricName: max-memory-kubelet
+  instant: true
+
+- query: max_over_time(sum(process_resident_memory_bytes{service="kubelet",job="kubelet"} and on (node) kube_node_role{role="worker"})[.elapsed:])
+  metricName: max-memory-sum-kubelet
+  instant: true
+
+# Average and max of the CPU usage from all worker's CRI-O
+- query: avg(avg_over_time(irate(process_cpu_seconds_total{service="kubelet",job="crio"}[2m])[.elapsed:]) and on (node) kube_node_role{role="worker"})
+  metricName: cpu-crio
+  instant: true
+
+- query: max(max_over_time(irate(process_cpu_seconds_total{service="kubelet",job="crio"}[2m])[.elapsed:]) and on (node) kube_node_role{role="worker"})
+  metricName: max-cpu-crio
+  instant: true
+
+# Average of the memory usage from all worker's CRI-O
+- query: avg(avg_over_time(process_resident_memory_bytes{service="kubelet",job="crio"}[.elapsed:]) and on (node) kube_node_role{role="worker"})
+  metricName: memory-crio
+  instant: true
+
+# Max of the memory usage from all worker's CRI-O
+- query: max(max_over_time(process_resident_memory_bytes{service="kubelet",job="crio"}[.elapsed:]) and on (node) kube_node_role{role="worker"})
+  metricName: max-memory-crio
+  instant: true
+
+# Etcd
+
+- query: avg(avg_over_time(histogram_quantile(0.99, rate(etcd_disk_backend_commit_duration_seconds_bucket[2m]))[.elapsed:]))
+  metricName: 99thEtcdDiskBackendCommit
+  instant: true
+
+- query: avg(avg_over_time(histogram_quantile(0.99, rate(etcd_disk_wal_fsync_duration_seconds_bucket[2m]))[.elapsed:]))
+  metricName: 99thEtcdDiskWalFsync
+  instant: true
+
+- query: avg(avg_over_time(histogram_quantile(0.99, irate(etcd_network_peer_round_trip_time_seconds_bucket[2m]))[.elapsed:]))
+  metricName: 99thEtcdRoundTripTime
+  instant: true
+
+# Control-plane
+
+- query: avg(avg_over_time(topk(1, sum(irate(container_cpu_usage_seconds_total{name!="", namespace="openshift-kube-controller-manager"}[2m])) by (pod))[.elapsed:]))
+  metricName: cpu-kube-controller-manager
+  instant: true
+
+- query: max(max_over_time(topk(1, sum(irate(container_cpu_usage_seconds_total{name!="", namespace="openshift-kube-controller-manager"}[2m])) by (pod))[.elapsed:]))
+  metricName: max-cpu-kube-controller-manager
+  instant: true
+
+- query: avg(avg_over_time(topk(1, sum(container_memory_rss{name!="", namespace="openshift-kube-controller-manager"}) by (pod))[.elapsed:]))
+  metricName: memory-kube-controller-manager
+  instant: true
+
+- query: max(max_over_time(topk(1, sum(container_memory_rss{name!="", namespace="openshift-kube-controller-manager"}) by (pod))[.elapsed:]))
+  metricName: max-memory-kube-controller-manager
+  instant: true
+
+- query: avg(avg_over_time(topk(3, sum(irate(container_cpu_usage_seconds_total{name!="", namespace="openshift-kube-apiserver"}[2m])) by (pod))[.elapsed:]))
+  metricName: cpu-kube-apiserver
+  instant: true
+
+- query: avg(avg_over_time(topk(3, sum(container_memory_rss{name!="", namespace="openshift-kube-apiserver"}) by (pod))[.elapsed:]))
+  metricName: memory-kube-apiserver
+  instant: true
+
+- query: avg(avg_over_time(topk(3, sum(irate(container_cpu_usage_seconds_total{name!="", namespace="openshift-apiserver"}[2m])) by (pod))[.elapsed:]))
+  metricName: cpu-openshift-apiserver
+  instant: true
+
+- query: avg(avg_over_time(topk(3, sum(container_memory_rss{name!="", namespace="openshift-apiserver"}) by (pod))[.elapsed:]))
+  metricName: memory-openshift-apiserver
+  instant: true
+
+- query: avg(avg_over_time(topk(3, sum(irate(container_cpu_usage_seconds_total{name!="", namespace="openshift-etcd"}[2m])) by (pod))[.elapsed:]))
+  metricName: cpu-etcd
+  instant: true
+
+- query: avg(avg_over_time(topk(3,sum(container_memory_rss{name!="", namespace="openshift-etcd"}) by (pod))[.elapsed:]))
+  metricName: memory-etcd
+  instant: true
+
+- query: avg(avg_over_time(topk(1, sum(irate(container_cpu_usage_seconds_total{name!="", namespace="openshift-controller-manager"}[2m])) by (pod))[.elapsed:]))
+  metricName: cpu-openshift-controller-manager
+  instant: true
+
+- query: avg(avg_over_time(topk(1, sum(container_memory_rss{name!="", namespace="openshift-controller-manager"}) by (pod))[.elapsed:]))
+  metricName: memory-openshift-controller-manager
+  instant: true
+
+ # multus
+
+- query: avg(avg_over_time(irate(container_cpu_usage_seconds_total{name!="", namespace="openshift-multus", pod=~"(multus).+", container!="POD"}[2m])[.elapsed:])) by (container)
+  metricName: cpu-multus
+  instant: true
+
+- query: avg(avg_over_time(container_memory_rss{name!="", namespace="openshift-multus", pod=~"(multus).+", container!="POD"}[.elapsed:])) by (container)
+  metricName: memory-multus
+  instant: true
+
+# OVNKubernetes - standard & IC
+
+- query: avg(avg_over_time(irate(container_cpu_usage_seconds_total{name!="", namespace="openshift-ovn-kubernetes", pod=~"(ovnkube-master|ovnkube-control-plane).+", container!="POD"}[2m])[.elapsed:])) by (container)
+  metricName: cpu-ovn-control-plane
+  instant: true
+
+- query: avg(avg_over_time(container_memory_rss{name!="", namespace="openshift-ovn-kubernetes", pod=~"(ovnkube-master|ovnkube-control-plane).+", container!="POD"}[.elapsed:])) by (container)
+  metricName: memory-ovn-control-plane
+  instant: true
+
+- query: avg(avg_over_time(irate(container_cpu_usage_seconds_total{name!="", namespace="openshift-ovn-kubernetes", pod=~"ovnkube-node.+", container!="POD"}[2m])[.elapsed:])) by (container)
+  metricName: cpu-ovnkube-node
+  instant: true
+
+- query: avg(avg_over_time(container_memory_rss{name!="", namespace="openshift-ovn-kubernetes", pod=~"ovnkube-node.+", container!="POD"}[.elapsed:])) by (container)
+  metricName: memory-ovnkube-node
+  instant: true
+
+# Nodes
+
+- query: avg(avg_over_time(sum(irate(node_cpu_seconds_total{mode!="idle", mode!="steal"}[2m]) and on (instance) label_replace(kube_node_role{role="master"}, "instance", "$1", "node", "(.+)")) by (instance)[.elapsed:]))
+  metricName: cpu-masters
+  instant: true
+
+- query: avg(avg_over_time((node_memory_MemTotal_bytes - node_memory_MemAvailable_bytes)[.elapsed:]) and on (instance) label_replace(kube_node_role{role="master"}, "instance", "$1", "node", "(.+)"))
+  metricName: memory-masters
+  instant: true
+
+- query: max(max_over_time((node_memory_MemTotal_bytes - node_memory_MemAvailable_bytes)[.elapsed:]) and on (instance) label_replace(kube_node_role{role="master"}, "instance", "$1", "node", "(.+)"))
+  metricName: max-memory-masters
+  instant: true
+
+- query: avg(avg_over_time(sum(irate(node_cpu_seconds_total{mode!="idle", mode!="steal"}[2m]) and on (instance) label_replace(kube_node_role{role="worker"}, "instance", "$1", "node", "(.+)")) by (instance)[.elapsed:]))
+  metricName: cpu-workers
+  instant: true
+
+- query: max(max_over_time(sum(irate(node_cpu_seconds_total{mode!="idle", mode!="steal"}[2m]) and on (instance) label_replace(kube_node_role{role="worker"}, "instance", "$1", "node", "(.+)")) by (instance)[.elapsed:]))
+  metricName: max-cpu-workers
+  instant: true
+
+- query: avg(avg_over_time((node_memory_MemTotal_bytes - node_memory_MemAvailable_bytes)[.elapsed:]) and on (instance) label_replace(kube_node_role{role="worker"}, "instance", "$1", "node", "(.+)"))
+  metricName: memory-workers
+  instant: true
+
+- query: max(max_over_time((node_memory_MemTotal_bytes - node_memory_MemAvailable_bytes)[.elapsed:]) and on (instance) label_replace(kube_node_role{role="worker"}, "instance", "$1", "node", "(.+)"))
+  metricName: max-memory-workers
+  instant: true
+
+- query: sum( (node_memory_MemTotal_bytes - node_memory_MemAvailable_bytes) and on (instance) label_replace(kube_node_role{role="worker"}, "instance", "$1", "node", "(.+)") )
+  metricName: memory-sum-workers
+  instant: true
+
+
+- query: avg(avg_over_time(sum(irate(node_cpu_seconds_total{mode!="idle", mode!="steal"}[2m]) and on (instance) label_replace(kube_node_role{role="infra"}, "instance", "$1", "node", "(.+)")) by (instance)[.elapsed:]))
+  metricName: cpu-infra
+  instant: true
+
+- query: max(max_over_time(sum(irate(node_cpu_seconds_total{mode!="idle", mode!="steal"}[2m]) and on (instance) label_replace(kube_node_role{role="infra"}, "instance", "$1", "node", "(.+)")) by (instance)[.elapsed:]))
+  metricName: max-cpu-infra
+  instant: true
+
+- query: avg(avg_over_time((node_memory_MemTotal_bytes - node_memory_MemAvailable_bytes)[.elapsed:]) and on (instance) label_replace(kube_node_role{role="infra"}, "instance", "$1", "node", "(.+)"))
+  metricName: memory-infra
+  instant: true
+
+- query: max(max_over_time((node_memory_MemTotal_bytes - node_memory_MemAvailable_bytes)[.elapsed:]) and on (instance) label_replace(kube_node_role{role="infra"}, "instance", "$1", "node", "(.+)"))
+  metricName: max-memory-infra
+  instant: true
+
+- query: max_over_time(sum((node_memory_MemTotal_bytes - node_memory_MemAvailable_bytes) and on (instance) label_replace(kube_node_role{role="infra"}, "instance", "$1", "node", "(.+)"))[.elapsed:])
+  metricName: max-memory-sum-infra
+  instant: true
+
+# Monitoring and ingress
+
+- query: avg(avg_over_time(sum(irate(container_cpu_usage_seconds_total{name!="", namespace="openshift-monitoring", pod=~"prometheus-k8s.+"}[2m])) by (pod)[.elapsed:]))
+  metricName: cpu-prometheus
+  instant: true
+
+- query: max(max_over_time(sum(irate(container_cpu_usage_seconds_total{name!="", namespace="openshift-monitoring", pod=~"prometheus-k8s.+"}[2m])) by (pod)[.elapsed:]))
+  metricName: max-cpu-prometheus
+  instant: true
+
+- query: avg(avg_over_time(sum(container_memory_rss{name!="", namespace="openshift-monitoring", pod=~"prometheus-k8s.+"}) by (pod)[.elapsed:]))
+  metricName: memory-prometheus
+  instant: true
+
+- query: max(max_over_time(sum(container_memory_rss{name!="", namespace="openshift-monitoring", pod=~"prometheus-k8s.+"}) by (pod)[.elapsed:]))
+  metricName: max-memory-prometheus
+  instant: true
+
+- query: avg(avg_over_time(sum(irate(container_cpu_usage_seconds_total{name!="", namespace="openshift-ingress", pod=~"router-default.+"}[2m])) by (pod)[.elapsed:]))
+  metricName: cpu-router
+  instant: true
+
+- query: avg(avg_over_time(sum(container_memory_rss{name!="", namespace="openshift-ingress", pod=~"router-default.+"}) by (pod)[.elapsed:]))
+  metricName: memory-router
+  instant: true
+
+# Cluster
+
+- query: avg_over_time(cluster:memory_usage:ratio[.elapsed:])
+  metricName: memory-cluster-usage-ratio
+  instant: true
+
+- query: avg_over_time(cluster:node_cpu:ratio[.elapsed:])
+  metricName: cpu-cluster-usage-ratio
+  instant: true
+
+# Retain the raw CPU seconds totals for comparison
+- query: sum(node_cpu_seconds_total and on (instance) label_replace(kube_node_role{role="worker",role!="infra"}, "instance", "$1", "node", "(.+)")) by (mode)
+  metricName: nodeCPUSeconds-Workers
+  instant: true
+
+
+- query: sum(node_cpu_seconds_total and on (instance) label_replace(kube_node_role{role="master"}, "instance", "$1", "node", "(.+)")) by (mode)
+  metricName: nodeCPUSeconds-Masters
+  instant: true
+
+
+- query: sum(node_cpu_seconds_total and on (instance) label_replace(kube_node_role{role="infra"}, "instance", "$1", "node", "(.+)")) by (mode)
+  metricName: nodeCPUSeconds-Infra
+  instant: true

config/metrics.yaml

@@ -1,13 +1,7 @@
 metrics:
 # API server
-  - query: histogram_quantile(0.99, sum(rate(apiserver_request_duration_seconds_bucket{apiserver="kube-apiserver", verb!~"WATCH", subresource!="log"}[2m])) by (verb,resource,subresource,instance,le)) > 0
-    metricName: API99thLatency
-
-  - query: sum(irate(apiserver_request_total{apiserver="kube-apiserver",verb!="WATCH",subresource!="log"}[2m])) by (verb,instance,resource,code) > 0
-    metricName: APIRequestRate
-
-  - query: sum(apiserver_current_inflight_requests{}) by (request_kind) > 0
-    metricName: APIInflightRequests
+  - query: irate(apiserver_request_total{verb="POST", resource="pods", subresource="binding",code="201"}[2m]) > 0
+    metricName: schedulingThroughput
 
 # Containers & pod metrics
   - query: sum(irate(container_cpu_usage_seconds_total{name!="",namespace=~"openshift-(etcd|oauth-apiserver|.*apiserver|ovn-kubernetes|sdn|ingress|authentication|.*controller-manager|.*scheduler|monitoring|logging|image-registry)"}[2m]) * 100) by (pod, namespace, node)
@@ -33,8 +27,17 @@ metrics:
     metricName: crioMemory
 
 # Node metrics
-  - query: sum(irate(node_cpu_seconds_total[2m])) by (mode,instance) > 0
-    metricName: nodeCPU
+  - query: (sum(irate(node_cpu_seconds_total[2m])) by (mode,instance) and on (instance) label_replace(kube_node_role{role="master"}, "instance", "$1", "node", "(.+)")) > 0
+    metricName: nodeCPU-Masters
+
+  - query: (avg_over_time((node_memory_MemTotal_bytes - node_memory_MemAvailable_bytes)[.elapsed:]) and on (instance) label_replace(kube_node_role{role="master"}, "instance", "$1", "node", "(.+)"))
+    metricName: nodeMemory-Masters
+  
+  - query: (sum(irate(node_cpu_seconds_total[2m])) by (mode,instance) and on (instance) label_replace(kube_node_role{role="worker"}, "instance", "$1", "node", "(.+)")) > 0
+    metricName: nodeCPU-Workers
+  
+  - query: (avg_over_time((node_memory_MemTotal_bytes - node_memory_MemAvailable_bytes)[2m:]) and on (instance) label_replace(kube_node_role{role="worker"}, "instance", "$1", "node", "(.+)"))
+    metricName: nodeMemory-Workers
 
   - query: avg(node_memory_MemAvailable_bytes) by (instance)
     metricName: nodeMemoryAvailable
@@ -42,6 +45,9 @@ metrics:
   - query: avg(node_memory_Active_bytes) by (instance)
     metricName: nodeMemoryActive
 
+  - query: max(max_over_time((node_memory_MemTotal_bytes - node_memory_MemAvailable_bytes)[.elapsed:]) and on (instance) label_replace(kube_node_role{role="master"}, "instance", "$1", "node", "(.+)"))
+    metricName: maxMemory-Masters
+
   - query: avg(node_memory_Cached_bytes) by (instance) + avg(node_memory_Buffers_bytes) by (instance)
     metricName: nodeMemoryCached+nodeMemoryBuffers
 
@@ -84,34 +90,4 @@ metrics:
 
   - query: sum by (cluster_version)(etcd_cluster_version)
     metricName: etcdVersion
-    instant: true
-
-# Cluster metrics
-  - query: count(kube_namespace_created)
-    metricName: namespaceCount
-
-  - query: sum(kube_pod_status_phase{}) by (phase)
-    metricName: podStatusCount
-
-  - query: count(kube_secret_info{})
-    metricName: secretCount
-
-  - query: count(kube_deployment_labels{})
-    metricName: deploymentCount
-
-  - query: count(kube_configmap_info{})
-    metricName: configmapCount
-
-  - query: count(kube_service_info{})
-    metricName: serviceCount
-
-  - query: kube_node_role
-    metricName: nodeRoles
-    instant: true
-
-  - query: sum(kube_node_status_condition{status="true"}) by (condition)
-    metricName: nodeStatus
-
-  - query: cluster_version{type="completed"}
-    metricName: clusterVersion
-    instant: true
+    instant: true

containers/Dockerfile.template

@@ -1,13 +1,19 @@
 # oc build
-FROM golang:1.22.4 AS oc-build
+FROM golang:1.23.1 AS oc-build
 RUN apt-get update && apt-get install -y --no-install-recommends libkrb5-dev
 WORKDIR /tmp
 RUN git clone --branch release-4.18 https://github.com/openshift/oc.git
 WORKDIR /tmp/oc
-RUN go mod edit -go 1.22.3 &&\
+RUN go mod edit -go 1.23.1 &&\
     go get github.com/moby/buildkit@v0.12.5 &&\
     go get github.com/containerd/containerd@v1.7.11&&\
-    go get github.com/docker/docker@v25.0.5&&\
+    go get github.com/docker/docker@v25.0.6&&\
+    go get github.com/opencontainers/runc@v1.1.14&&\
+    go get github.com/go-git/go-git/v5@v5.13.0&&\
+    go get golang.org/x/net@v0.36.0&&\
+    go get github.com/containerd/containerd@v1.7.27&&\
+    go get golang.org/x/oauth2@v0.27.0&&\
+    go get golang.org/x/crypto@v0.35.0&&\
     go mod tidy && go mod vendor
 RUN make GO_REQUIRED_MIN_VERSION:= oc
 
@@ -19,10 +25,6 @@ RUN dnf update -y
 
 ENV KUBECONFIG /home/krkn/.kube/config
 
-# install kubectl
-RUN curl -LO "https://dl.k8s.io/release/$(curl -L -s https://dl.k8s.io/release/stable.txt)/bin/linux/amd64/kubectl" &&\
-    cp kubectl /usr/local/bin/kubectl && chmod +x /usr/local/bin/kubectl &&\
-    cp kubectl /usr/bin/kubectl && chmod +x /usr/bin/kubectl
 
 # This overwrites any existing configuration in /etc/yum.repos.d/kubernetes.repo
 RUN dnf update && dnf install -y --setopt=install_weak_deps=False \
@@ -44,10 +46,16 @@ RUN if [ -n "$PR_NUMBER" ]; then git fetch origin pull/${PR_NUMBER}/head:pr-${PR
 # if it is a TAG trigger checkout the tag
 RUN if [ -n "$TAG" ]; then git checkout "$TAG";fi
 
-RUN python3.9 -m ensurepip
+RUN python3.9 -m ensurepip --upgrade --default-pip
+RUN python3.9 -m pip install --upgrade pip setuptools==70.0.0
 RUN pip3.9 install -r requirements.txt
 RUN pip3.9 install jsonschema
 
+LABEL krknctl.title.global="Krkn Base Image"
+LABEL krknctl.description.global="This is the krkn base image."
+LABEL krknctl.input_fields.global='$KRKNCTL_INPUT'
+
+
 RUN chown -R krkn:krkn /home/krkn && chmod 755 /home/krkn
 USER krkn
 ENTRYPOINT ["python3.9", "run_kraken.py"]

containers/README.md

@@ -6,7 +6,7 @@ Container image gets automatically built by quay.io at [Kraken image](https://qu
 
 ### Run containerized version
 
-Refer [instructions](https://github.com/redhat-chaos/krkn/blob/main/docs/installation.md#run-containerized-version) for information on how to run the containerized version of kraken.
+Refer [instructions](https://krkn-chaos.dev/docs/installation/) for information on how to run the containerized version of kraken.
 
 
 ### Run Custom Kraken Image

containers/compile_dockerfile.sh

@@ -0,0 +1,5 @@
+SCRIPT_DIR="$(cd "$(dirname "${BASH_SOURCE[0]}")" && pwd)"
+cd "$SCRIPT_DIR"
+export KRKNCTL_INPUT=$(cat krknctl-input.json|tr -d "\n")
+
+envsubst '${KRKNCTL_INPUT}' < Dockerfile.template > Dockerfile

containers/krknctl-input.json

@@ -0,0 +1,439 @@
+[
+  {
+    "name": "cerberus-enabled",
+    "short_description": "Enable Cerberus",
+    "description": "Enables Cerberus Support",
+    "variable": "CERBERUS_ENABLED",
+    "type": "enum",
+    "default": "False",
+    "allowed_values": "True,False",
+    "separator": ",",
+    "required": "false"
+  },
+  {
+    "name": "cerberus-url",
+    "short_description": "Cerberus URL",
+    "description": "Cerberus http url",
+    "variable": "CERBERUS_URL",
+    "type": "string",
+    "default": "http://0.0.0.0:8080",
+    "validator": "^(http|https):\/\/.*",
+    "required": "false"
+  },
+  {
+    "name": "distribution",
+    "short_description": "Orchestrator distribution",
+    "description": "Selects the orchestrator distribution",
+    "variable": "DISTRIBUTION",
+    "type": "enum",
+    "default": "openshift",
+    "allowed_values": "openshift,kubernetes",
+    "separator": ",",
+    "required": "false"
+  },
+  {
+    "name": "krkn-kubeconfig",
+    "short_description": "Krkn kubeconfig path",
+    "description": "Sets the path where krkn will search for kubeconfig (in container)",
+    "variable": "KRKN_KUBE_CONFIG",
+    "type": "string",
+    "default": "/home/krkn/.kube/config",
+    "required": "false"
+  },
+  {
+    "name": "wait-duration",
+    "short_description": "Post chaos wait duration",
+    "description": "waits for a certain amount of time after the scenario",
+    "variable": "WAIT_DURATION",
+    "type": "number",
+    "default": "1"
+  },
+  {
+    "name": "iterations",
+    "short_description": "Chaos scenario iterations",
+    "description": "number of times the same chaos scenario will be executed",
+    "variable": "ITERATIONS",
+    "type": "number",
+    "default": "1"
+  },
+  {
+    "name": "daemon-mode",
+    "short_description": "Sets krkn daemon mode",
+    "description": "if set the scenario will execute forever",
+    "variable": "DAEMON_MODE",
+    "type": "enum",
+    "allowed_values": "True,False",
+    "separator": ",",
+    "default": "False",
+    "required": "false"
+  },
+  {
+    "name": "uuid",
+    "short_description": "Sets krkn run uuid",
+    "description": "sets krkn run uuid instead of generating it",
+    "variable": "UUID",
+    "type": "string",
+    "default": "",
+    "required": "false"
+  },
+  {
+    "name": "capture-metrics",
+    "short_description": "Enables metrics capture",
+    "description": "Enables metrics capture",
+    "variable": "CAPTURE_METRICS",
+    "type": "enum",
+    "allowed_values": "True,False",
+    "separator": ",",
+    "default": "False",
+    "required": "false"
+  },
+  {
+    "name": "enable-alerts",
+    "short_description": "Enables cluster alerts check",
+    "description": "Enables cluster alerts check",
+    "variable": "ENABLE_ALERTS",
+    "type": "enum",
+    "allowed_values": "True,False",
+    "separator": ",",
+    "default": "False",
+    "required": "false"
+  },
+  {
+    "name": "alerts-path",
+    "short_description": "Cluster alerts path file (in container)",
+    "description": "Allows to specify a different alert file path",
+    "variable": "ALERTS_PATH",
+    "type": "string",
+    "default": "config/alerts.yaml",
+    "required": "false"
+  },
+  {
+    "name": "metrics-path",
+    "short_description": "Cluster metrics path file (in container)",
+    "description": "Allows to specify a different metrics file path",
+    "variable": "METRICS_PATH",
+    "type": "string",
+    "default": "config/metrics-aggregated.yaml",
+    "required": "false"
+  },
+  {
+    "name": "enable-es",
+    "short_description": "Enables elastic search data collection",
+    "description": "Enables elastic search data collection",
+    "variable": "ENABLE_ES",
+    "type": "enum",
+    "allowed_values": "True,False",
+    "separator": ",",
+    "default": "False",
+    "required": "false"
+  },
+  {
+    "name": "es-server",
+    "short_description": "Elasticsearch instance URL",
+    "description": "Elasticsearch instance URL",
+    "variable": "ES_SERVER",
+    "type": "string",
+    "default": "http://0.0.0.0",
+    "required": "false"
+  },
+  {
+    "name": "es-port",
+    "short_description": "Elasticsearch instance port",
+    "description": "Elasticsearch instance port",
+    "variable": "ES_PORT",
+    "type": "number",
+    "default": "443",
+    "required": "false"
+  },
+  {
+    "name": "es-username",
+    "short_description": "Elasticsearch instance username",
+    "description": "Elasticsearch instance username",
+    "variable": "ES_USERNAME",
+    "type": "string",
+    "default": "elastic",
+    "required": "false"
+  },
+  {
+    "name": "es-password",
+    "short_description": "Elasticsearch instance password",
+    "description": "Elasticsearch instance password",
+    "variable": "ES_PASSWORD",
+    "type": "string",
+    "default": "",
+    "required": "false"
+  },
+  {
+    "name": "es-verify-certs",
+    "short_description": "Enables elasticsearch TLS certificate verification",
+    "description": "Enables elasticsearch TLS certificate verification",
+    "variable": "ES_VERIFY_CERTS",
+    "type": "enum",
+    "allowed_values": "True,False",
+    "separator": ",",
+    "default": "False",
+    "required": "false"
+  },
+  {
+    "name": "es-metrics-index",
+    "short_description": "Elasticsearch metrics index",
+    "description": "Index name for metrics in Elasticsearch",
+    "variable": "ES_METRICS_INDEX",
+    "type": "string",
+    "default": "krkn-metrics",
+    "required": "false"
+  },
+  {
+    "name": "es-alerts-index",
+    "short_description": "Elasticsearch alerts index",
+    "description": "Index name for alerts in Elasticsearch",
+    "variable": "ES_ALERTS_INDEX",
+    "type": "string",
+    "default": "krkn-alerts",
+    "required": "false"
+  },
+  {
+    "name": "es-telemetry-index",
+    "short_description": "Elasticsearch telemetry index",
+    "description": "Index name for telemetry in Elasticsearch",
+    "variable": "ES_TELEMETRY_INDEX",
+    "type": "string",
+    "default": "krkn-telemetry",
+    "required": "false"
+  },
+  {
+    "name": "check-critical-alerts",
+    "short_description": "Check critical alerts",
+    "description": "Enables checking for critical alerts",
+    "variable": "CHECK_CRITICAL_ALERTS",
+    "type": "enum",
+    "allowed_values": "True,False",
+    "separator": ",",
+    "default": "False",
+    "required": "false"
+  },
+  {
+    "name": "telemetry-enabled",
+    "short_description": "Enable telemetry",
+    "description": "Enables telemetry support",
+    "variable": "TELEMETRY_ENABLED",
+    "type": "enum",
+    "allowed_values": "True,False",
+    "separator": ",",
+    "default": "False",
+    "required": "false"
+  },
+  {
+    "name": "telemetry-api-url",
+    "short_description": "Telemetry API URL",
+    "description": "API endpoint for telemetry data",
+    "variable": "TELEMETRY_API_URL",
+    "type": "string",
+    "default": "https://ulnmf9xv7j.execute-api.us-west-2.amazonaws.com/production",
+    "validator": "^(http|https):\/\/.*",
+    "required": "false"
+  },
+  {
+    "name": "telemetry-username",
+    "short_description": "Telemetry username",
+    "description": "Username for telemetry authentication",
+    "variable": "TELEMETRY_USERNAME",
+    "type": "string",
+    "default": "redhat-chaos",
+    "required": "false"
+  },
+  {
+    "name": "telemetry-password",
+    "short_description": "Telemetry password",
+    "description": "Password for telemetry authentication",
+    "variable": "TELEMETRY_PASSWORD",
+    "type": "string",
+    "default": "",
+    "required": "false"
+  },
+  {
+    "name": "telemetry-prometheus-backup",
+    "short_description": "Prometheus backup for telemetry",
+    "description": "Enables Prometheus backup for telemetry",
+    "variable": "TELEMETRY_PROMETHEUS_BACKUP",
+    "type": "enum",
+    "allowed_values": "True,False",
+    "separator": ",",
+    "default": "True",
+    "required": "false"
+  },
+  {
+    "name": "telemetry-full-prometheus-backup",
+    "short_description": "Full Prometheus backup",
+    "description": "Enables full Prometheus backup for telemetry",
+    "variable": "TELEMETRY_FULL_PROMETHEUS_BACKUP",
+    "type": "enum",
+    "allowed_values": "True,False",
+    "separator": ",",
+    "default": "False",
+    "required": "false"
+  },
+  {
+    "name": "telemetry-backup-threads",
+    "short_description": "Telemetry backup threads",
+    "description": "Number of threads for telemetry backup",
+    "variable": "TELEMETRY_BACKUP_THREADS",
+    "type": "number",
+    "default": "5",
+    "required": "false"
+  },
+  {
+    "name": "telemetry-archive-path",
+    "short_description": "Telemetry archive path",
+    "description": "Path to save telemetry archive",
+    "variable": "TELEMETRY_ARCHIVE_PATH",
+    "type": "string",
+    "default": "/tmp",
+    "required": "false"
+  },
+  {
+    "name": "telemetry-max-retries",
+    "short_description": "Telemetry max retries",
+    "description": "Maximum retries for telemetry operations",
+    "variable": "TELEMETRY_MAX_RETRIES",
+    "type": "number",
+    "default": "0",
+    "required": "false"
+  },
+  {
+    "name": "telemetry-run-tag",
+    "short_description": "Telemetry run tag",
+    "description": "Tag for telemetry run",
+    "variable": "TELEMETRY_RUN_TAG",
+    "type": "string",
+    "default": "chaos",
+    "required": "false"
+  },
+  {
+    "name": "telemetry-group",
+    "short_description": "Telemetry group",
+    "description": "Group name for telemetry data",
+    "variable": "TELEMETRY_GROUP",
+    "type": "string",
+    "default": "default",
+    "required": "false"
+  },
+  {
+    "name": "telemetry-archive-size",
+    "short_description": "Telemetry archive size",
+    "description": "Maximum size for telemetry archives",
+    "variable": "TELEMETRY_ARCHIVE_SIZE",
+    "type": "number",
+    "default": "1000",
+    "required": "false"
+  },
+  {
+    "name": "telemetry-logs-backup",
+    "short_description": "Telemetry logs backup",
+    "description": "Enables logs backup for telemetry",
+    "variable": "TELEMETRY_LOGS_BACKUP",
+    "type": "enum",
+    "allowed_values": "True,False",
+    "separator": ",",
+    "default": "False",
+    "required": "false"
+  },
+  {
+    "name": "telemetry-filter-pattern",
+    "short_description": "Telemetry filter pattern",
+    "description": "Filter pattern for telemetry logs",
+    "variable": "TELEMETRY_FILTER_PATTERN",
+    "type": "string",
+    "default": "[\"(\\\\w{3}\\\\s\\\\d{1,2}\\\\s\\\\d{2}:\\\\d{2}:\\\\d{2}\\\\.\\\\d+).+\",\"kinit (\\\\d+/\\\\d+/\\\\d+\\\\s\\\\d{2}:\\\\d{2}:\\\\d{2})\\\\s+\",\"(\\\\d{4}-\\\\d{2}-\\\\d{2}T\\\\d{2}:\\\\d{2}:\\\\d{2}\\\\.\\\\d+Z).+\"]",
+    "required": "false"
+  },
+  {
+    "name": "telemetry-cli-path",
+    "short_description": "Telemetry CLI path (oc)",
+    "description": "Path to telemetry CLI tool (oc)",
+    "variable": "TELEMETRY_CLI_PATH",
+    "type": "string",
+    "default": "",
+    "required": "false"
+  },
+  {
+    "name": "telemetry-events-backup",
+    "short_description": "Telemetry events backup",
+    "description": "Enables events backup for telemetry",
+    "variable": "TELEMETRY_EVENTS_BACKUP",
+    "type": "enum",
+    "allowed_values": "True,False",
+    "separator": ",",
+    "default": "True",
+    "required": "false"
+  },
+  {
+    "name": "health-check-interval",
+    "short_description": "Heath check interval",
+    "description": "How often to check the health check urls",
+    "variable": "HEALTH_CHECK_INTERVAL",
+    "type": "number",
+    "default": "2",
+    "required": "false"
+  },
+  {
+    "name": "health-check-url",
+    "short_description": "Health check url",
+    "description": "Url to check the health of",
+    "variable": "HEALTH_CHECK_URL",
+    "type": "string",
+    "default": "",
+    "required": "false"
+  },
+  {
+    "name": "health-check-auth",
+    "short_description": "Health check authentication tuple",
+    "description": "Authentication tuple to authenticate into health check URL",
+    "variable": "HEALTH_CHECK_AUTH",
+    "type": "string",
+    "default": "",
+    "required": "false"
+  },
+  {
+    "name": "health-check-bearer-token",
+    "short_description": "Health check bearer token",
+    "description": "Bearer token to authenticate into health check URL",
+    "variable": "HEALTH_CHECK_BEARER_TOKEN",
+    "type": "string",
+    "default": "",
+    "required": "false"
+  },
+  {
+    "name": "health-check-exit",
+    "short_description": "Health check exit on failure",
+    "description": "Exit on failure when health check URL is not able to connect",
+    "variable": "HEALTH_CHECK_EXIT_ON_FAILURE",
+    "type": "enum",
+    "allowed_values": "True,False",
+    "separator": ",",
+    "default": "False",
+    "required": "false"
+  },
+  {
+    "name": "health-check-verify",
+    "short_description": "SSL Verification of health check url",
+    "description": "SSL Verification to authenticate into health check URL",
+    "variable": "HEALTH_CHECK_VERIFY",
+    "type": "enum",
+    "allowed_values": "True,False",
+    "separator": ",",
+    "default": "False",
+    "required": "false"
+  },
+  {
+    "name": "krkn-debug",
+    "short_description": "Krkn debug mode",
+    "description": "Enables debug mode for Krkn",
+    "variable": "KRKN_DEBUG",
+    "type": "enum",
+    "allowed_values": "True,False",
+    "separator": ",",
+    "default": "False",
+    "required": "false"
+  }
+]

docs/SLOs_validation.md

@@ -1,48 +0,0 @@
-## SLOs validation
-
-Pass/fail based on metrics captured from the cluster is important in addition to checking the health status and recovery. Kraken supports:
-
-###  Checking for critical alerts post chaos 
-If enabled, the check runs at the end of each scenario ( post chaos ) and Kraken exits in case critical alerts are firing to allow user to debug. You can enable it in the config:
-
-```
-performance_monitoring:
-    check_critical_alerts: False                          # When enabled will check prometheus for critical alerts firing post chaos
-```
-
-### Validation and alerting based on the queries defined by the user during chaos
-Takes PromQL queries as input and modifies the return code of the run to determine pass/fail. It's especially useful in case of automated runs in CI where user won't be able to monitor the system. This feature can be enabled in the [config](https://github.com/redhat-chaos/krkn/blob/main/config/config.yaml) by setting the following:
-
-```
-performance_monitoring:
-    prometheus_url:                                       # The prometheus url/route is automatically obtained in case of OpenShift, please set it when the distribution is Kubernetes.
-    prometheus_bearer_token:                              # The bearer token is automatically obtained in case of OpenShift, please set it when the distribution is Kubernetes. This is needed to authenticate with prometheus.
-    enable_alerts: True                                   # Runs the queries specified in the alert profile and displays the info or exits 1 when severity=error.
-    alert_profile: config/alerts.yaml                          # Path to alert profile with the prometheus queries.
-```
-
-#### Alert profile
-A couple of [alert profiles](https://github.com/redhat-chaos/krkn/tree/main/config) [alerts](https://github.com/redhat-chaos/krkn/blob/main/config/alerts.yaml) are shipped by default and can be tweaked to add more queries to alert on. User can provide a URL or path to the file in the [config](https://github.com/redhat-chaos/krkn/blob/main/config/config.yaml). The following are a few alerts examples:
-
-```
-- expr: avg_over_time(histogram_quantile(0.99, rate(etcd_disk_wal_fsync_duration_seconds_bucket[2m]))[5m:]) > 0.01
-  description: 5 minutes avg. etcd fsync latency on {{$labels.pod}} higher than 10ms {{$value}}
-  severity: error
-
-- expr: avg_over_time(histogram_quantile(0.99, rate(etcd_network_peer_round_trip_time_seconds_bucket[5m]))[5m:]) > 0.1
-  description: 5 minutes avg. etcd network peer round trip on {{$labels.pod}} higher than 100ms {{$value}}
-  severity: info
-
-- expr: increase(etcd_server_leader_changes_seen_total[2m]) > 0
-  description: etcd leader changes observed
-  severity: critical
-```
-
-Kube-burner supports setting the severity for the alerts with each one having different effects:
-
-```
-info: Prints an info message with the alarm description to stdout. By default all expressions have this severity.
-warning: Prints a warning message with the alarm description to stdout.
-error: Prints a error message with the alarm description to stdout and makes kube-burner rc = 1
-critical: Prints a fatal message with the alarm description to stdout and exits execution inmediatly with rc != 0
-```

docs/_config.yml

@@ -1 +0,0 @@
-theme: jekyll-theme-cayman

docs/application_outages.md

@@ -1,17 +0,0 @@
-### Application outages
-Scenario to block the traffic ( Ingress/Egress ) of an application matching the labels for the specified duration of time to understand the behavior of the service/other services which depend on it during downtime. This helps with planning the requirements accordingly, be it improving the timeouts or tweaking the alerts etc.
-
-##### Sample scenario config
-```
-application_outage:                                  # Scenario to create an outage of an application by blocking traffic
-  duration: 600                                      # Duration in seconds after which the routes will be accessible
-  namespace: <namespace-with-application>            # Namespace to target - all application routes will go inaccessible if pod selector is empty
-  pod_selector: {app: foo}                            # Pods to target
-  block: [Ingress, Egress]                           # It can be Ingress or Egress or Ingress, Egress
-```
-
-##### Debugging steps in case of failures
-Kraken creates a network policy blocking the ingress/egress traffic to create an outage, in case of failures before reverting back the network policy, you can delete it manually by executing the following commands to stop the outage:
-```
-$ oc delete networkpolicy/kraken-deny -n <targeted-namespace>
-```

docs/arcaflow_scenarios.md

@@ -1,70 +0,0 @@
-## Arcaflow Scenarios
-Arcaflow is a workflow engine in development which provides the ability to execute workflow steps in sequence, in parallel, repeatedly, etc. The main difference to competitors such as Netflix Conductor is the ability to run ad-hoc workflows without an infrastructure setup required.
-
-The engine uses containers to execute plugins and runs them either locally in Docker/Podman or remotely on a Kubernetes cluster. The workflow system is strongly typed and allows for generating JSON schema and OpenAPI documents for all data formats involved.
-
-### Available Scenarios
-#### Hog scenarios:
-- [CPU Hog](arcaflow_scenarios/cpu_hog.md)
-- [Memory Hog](arcaflow_scenarios/memory_hog.md)
-- [I/O Hog](arcaflow_scenarios/io_hog.md)
-
-
-### Prequisites
-Arcaflow supports three deployment technologies:
-- Docker
-- Podman
-- Kubernetes
-
-#### Docker
-In order to run Arcaflow Scenarios with the Docker deployer, be sure that:
-- Docker is correctly installed in your Operating System (to find instructions on how to install docker please refer to [Docker Documentation](https://www.docker.com/))
-- The Docker daemon is running
-
-#### Podman
-The podman deployer is built around the podman CLI and doesn't need necessarily to be run along with the podman daemon.
-To run Arcaflow Scenarios in your Operating system be sure that:
-- podman is correctly installed in your Operating System (to find instructions on how to install podman refer to [Podman Documentation](https://podman.io/))
-- the podman CLI is in your shell PATH
-
-#### Kubernetes
-The kubernetes deployer integrates directly the Kubernetes API Client and needs only a valid kubeconfig file and a reachable Kubernetes/OpenShift Cluster.
-
-### Usage
-
-To enable arcaflow scenarios edit the kraken config file, go to the section `kraken -> chaos_scenarios` of the yaml structure
-and add a new element to the list named `arcaflow_scenarios` then add the desired scenario
-pointing to the `input.yaml` file.
-```
-kraken:
-    ...
-    chaos_scenarios:
-        - arcaflow_scenarios:
-            - scenarios/arcaflow/cpu-hog/input.yaml
-```
-
-#### input.yaml
-The implemented scenarios can be found in *scenarios/arcaflow/<scenario_name>* folder.
-The entrypoint of each scenario is the *input.yaml* file. 
-In this file there are all the options to set up the scenario accordingly to the desired target 
-### config.yaml
-The arcaflow config file. Here you can set the arcaflow deployer and the arcaflow log level.
-The supported deployers are:
-- Docker
-- Podman (podman daemon not needed, suggested option)
-- Kubernetes
-
-The supported log levels are:
-- debug
-- info
-- warning
-- error
-### workflow.yaml
-This file contains the steps that will be executed to perform the scenario against the target.
-Each step is represented by a container that will be executed from the deployer and its options.
-Note that we provide the scenarios as a template, but they can be manipulated to define more complex workflows.
-To have more details regarding the arcaflow workflows architecture and syntax it is suggested to refer to the [Arcaflow Documentation](https://arcalot.io/arcaflow/).
-
-This edit is no longer in quay image
-Working on fix in ticket: https://issues.redhat.com/browse/CHAOS-494
-This will effect all versions 4.12 and higher of OpenShift

docs/arcaflow_scenarios/cpu_hog.md

@@ -1,19 +0,0 @@
-# CPU Hog
-This scenario is based on the arcaflow [arcaflow-plugin-stressng](https://github.com/arcalot/arcaflow-plugin-stressng) plugin. 
-The purpose of this scenario is to create cpu pressure on a particular node of the Kubernetes/OpenShift cluster for a time span.
-To enable this plugin add the pointer to the scenario input file `scenarios/arcaflow/cpu-hog/input.yaml` as described in the 
-Usage section.
-This scenario takes a list of objects named `input_list` with the following properties:
-
-- **kubeconfig :** *string* the kubeconfig needed by the deployer to deploy the sysbench plugin in the target cluster
-- **namespace :** *string* the namespace where the scenario container will be deployed
-**Note:** this parameter will be automatically filled by kraken if the `kubeconfig_path` property is correctly set
-- **node_selector :** *key-value map* the node label that will be used as `nodeSelector` by the pod to target a specific cluster node
-- **duration :** *string* stop  stress  test  after  N  seconds.  One  can  also specify the units of time in seconds, minutes, hours, days or years with the suffix s, m, h, d or y.
-- **cpu_count :** *int* the number of CPU cores to be used (0 means all)
-- **cpu_method :** *string* a fine-grained control of which cpu stressors to use (ackermann, cfloat etc. see [manpage](https://manpages.org/sysbench) for all the cpu_method options)
-- **cpu_load_percentage :** *int* the CPU load by percentage
-
-To perform several load tests in the same run simultaneously (eg. stress two or more nodes in the same run) add another item
-to the `input_list` with the same properties (and eventually different values eg. different node_selectors 
-to schedule the pod on different nodes). To reduce (or increase) the parallelism change the value `parallelism` in `workload.yaml` file 

docs/arcaflow_scenarios/io_hog.md

@@ -1,21 +0,0 @@
-# I/O Hog
-This scenario is based on the arcaflow [arcaflow-plugin-stressng](https://github.com/arcalot/arcaflow-plugin-stressng) plugin. 
-The purpose of this scenario is to create disk pressure on a particular node of the Kubernetes/OpenShift cluster for a time span.
-The scenario allows to attach a node path to the pod as a `hostPath` volume.
-To enable this plugin add the pointer to the scenario input file `scenarios/arcaflow/io-hog/input.yaml` as described in the 
-Usage section.
-This scenario takes a list of objects named `input_list` with the following properties:
-
-- **kubeconfig :** *string* the kubeconfig needed by the deployer to deploy the sysbench plugin in the target cluster
-- **namespace :** *string* the namespace where the scenario container will be deployed
-**Note:** this parameter will be automatically filled by kraken if the `kubeconfig_path` property is correctly set
-- **node_selector :** *key-value map* the node label that will be used as `nodeSelector` by the pod to target a specific cluster node
-- **duration :** *string* stop  stress  test  after  N  seconds.  One  can  also specify the units of time in seconds, minutes, hours, days or years with the suffix s, m, h, d or y.
-- **target_pod_folder :** *string* the path in the pod where the volume is mounted
-- **target_pod_volume :** *object* the `hostPath` volume definition in the [Kubernetes/OpenShift](https://docs.openshift.com/container-platform/3.11/install_config/persistent_storage/using_hostpath.html) format, that will be attached to the pod as a volume
-- **io_write_bytes :** *string* writes N bytes for each hdd process. The size can be expressed as % of free space on the file system or in units of Bytes, KBytes, MBytes and GBytes using the suffix b, k, m or g
-- **io_block_size :** *string* size of each write in bytes. Size can be from 1 byte to 4m.
-
-To perform several load tests in the same run simultaneously (eg. stress two or more nodes in the same run) add another item
-to the `input_list` with the same properties (and eventually different values eg. different node_selectors 
-to schedule the pod on different nodes). To reduce (or increase) the parallelism change the value `parallelism` in `workload.yaml` file 

docs/arcaflow_scenarios/memory_hog.md

@@ -1,18 +0,0 @@
-# Memory Hog
-This scenario is based on the arcaflow [arcaflow-plugin-stressng](https://github.com/arcalot/arcaflow-plugin-stressng) plugin. 
-The purpose of this scenario is to create Virtual Memory pressure on a particular node of the Kubernetes/OpenShift cluster for a time span.
-To enable this plugin add the pointer to the scenario input file `scenarios/arcaflow/memory-hog/input.yaml` as described in the 
-Usage section.
-This scenario takes a list of objects named `input_list` with the following properties:
-
-- **kubeconfig :** *string* the kubeconfig needed by the deployer to deploy the sysbench plugin in the target cluster
-- **namespace :** *string* the namespace where the scenario container will be deployed
-**Note:** this parameter will be automatically filled by kraken if the `kubeconfig_path` property is correctly set
-- **node_selector :** *key-value map* the node label that will be used as `nodeSelector` by the pod to target a specific cluster node
-- **duration :** *string* stop  stress  test  after  N  seconds.  One  can  also specify the units of time in seconds, minutes, hours, days or years with the suffix s, m, h, d or y.
-- **vm_bytes :** *string* N bytes per vm process or percentage of memory used (using the % symbol). The size can be expressed in units of Bytes, KBytes, MBytes and GBytes using the suffix b, k, m or g.
-- **vm_workers :** *int* Number of VM stressors to be run (0 means 1 stressor per CPU)
-
-To perform several load tests in the same run simultaneously (eg. stress two or more nodes in the same run) add another item
-to the `input_list` with the same properties (and eventually different values eg. different node_selectors 
-to schedule the pod on different nodes). To reduce (or increase) the parallelism change the value `parallelism` in `workload.yaml` file 

docs/cloud_setup.md

@@ -1,87 +0,0 @@
-Supported Cloud Providers:
-
-- [AWS](#aws)
-- [GCP](#gcp)
-- [Openstack](#openstack)
-- [Azure](#azure)
-- [Alibaba](#alibaba)
-- [VMware](#vmware)
-- [IBMCloud](#ibmcloud)
-
-## AWS
-
-**NOTE**: For clusters with AWS make sure [AWS CLI](https://docs.aws.amazon.com/cli/latest/userguide/getting-started-install.html) is installed and properly [configured](https://docs.aws.amazon.com/cli/latest/userguide/cli-configure-quickstart.html) using an AWS account
-
-## GCP
-**NOTE**: For clusters with GCP make sure [GCP CLI](https://cloud.google.com/sdk/docs/install#linux) is installed.
-
-A google service account is required to give proper authentication to GCP for node actions. See [here](https://cloud.google.com/docs/authentication/getting-started) for how to create a service account.
-
-**NOTE**: A user with 'resourcemanager.projects.setIamPolicy' permission is required to grant project-level permissions to the service account.
-
-After creating the service account you will need to enable the account using the following: ```export GOOGLE_APPLICATION_CREDENTIALS="<serviceaccount.json>"```
-
-## Openstack
-
-**NOTE**: For clusters with Openstack Cloud, ensure to create and source the [OPENSTACK RC file](https://docs.openstack.org/newton/user-guide/common/cli-set-environment-variables-using-openstack-rc.html) to set the OPENSTACK environment variables from the server where Kraken runs.
-
-## Azure
-
-**NOTE**: You will need to create a service principal and give it the correct access, see [here](https://docs.openshift.com/container-platform/4.5/installing/installing_azure/installing-azure-account.html) for creating the service principal and setting the proper permissions.
-
-To properly run the service principal requires “Azure Active Directory Graph/Application.ReadWrite.OwnedBy” api permission granted and “User Access Administrator”.
-
-Before running you will need to set the following:
-1. ```export AZURE_SUBSCRIPTION_ID=<subscription_id>```
-
-2. ```export AZURE_TENANT_ID=<tenant_id>```
-
-3. ```export AZURE_CLIENT_SECRET=<client secret>```
-
-4. ```export AZURE_CLIENT_ID=<client id>```
-
-## Alibaba
-
-See the [Installation guide](https://www.alibabacloud.com/help/en/alibaba-cloud-cli/latest/installation-guide) to install alicloud cli.
-
-1. ```export ALIBABA_ID=<access_key_id>```
-
-2. ```export ALIBABA_SECRET=<access key secret>```
-
-3. ```export ALIBABA_REGION_ID=<region id>```
-
-Refer to [region and zone page](https://www.alibabacloud.com/help/en/elastic-compute-service/latest/regions-and-zones#concept-2459516) to get the region id for the region you are running on.
-
-Set cloud_type to either alibaba or alicloud in your node scenario yaml file.
-
-## VMware
-
-Set the following environment variables
-
-1. ```export VSPHERE_IP=<vSphere_client_IP_address>```
-
-2. ```export VSPHERE_USERNAME=<vSphere_client_username>```
-
-3. ```export VSPHERE_PASSWORD=<vSphere_client_password>```
-
-These are the credentials that you would normally use to access the vSphere client.
-
-
-## IBMCloud
-If no api key is set up with proper VPC resource permissions, use the following to create: 
-* Access group
-* Service id with the following access
-  * With policy **VPC Infrastructure Services**
-  * Resources = All
-  * Roles: 
-    * Editor
-    * Administrator 
-    * Operator  
-    * Viewer
-* API Key
-
-Set the following environment variables
-
-1. ```export IBMC_URL=https://<region>.iaas.cloud.ibm.com/v1```
-
-2. ```export IBMC_APIKEY=<ibmcloud_api_key>```

docs/cluster_shut_down_scenarios.md

@@ -1,18 +0,0 @@
-#### Kubernetes cluster shut down scenario
-Scenario to shut down all the nodes including the masters and restart them after specified duration. Cluster shut down scenario can be injected by placing the shut_down config file under cluster_shut_down_scenario option in the kraken config. Refer to [cluster_shut_down_scenario](https://github.com/krkn-chaos/krkn/blob/main/scenarios/cluster_shut_down_scenario.yml) config file.
-
-Refer to [cloud setup](cloud_setup.md) to configure your cli properly for the cloud provider of the cluster you want to shut down.
-
-Current accepted cloud types:
-* [Azure](cloud_setup.md#azure)
-* [GCP](cloud_setup.md#gcp)
-* [AWS](cloud_setup.md#aws)
-* [Openstack](cloud_setup.md#openstack)
-
-
-```
-cluster_shut_down_scenario:                          # Scenario to stop all the nodes for specified duration and restart the nodes.
-  runs: 1                                            # Number of times to execute the cluster_shut_down scenario.
-  shut_down_duration: 120                            # Duration in seconds to shut down the cluster.
-  cloud_type: aws                                    # Cloud type on which Kubernetes/OpenShift runs.
-```

docs/config.md

@@ -1,65 +0,0 @@
-### Config
-Set the scenarios to inject and the tunings like duration to wait between each scenario in the config file located at [config/config.yaml](https://github.com/redhat-chaos/krkn/blob/main/config/config.yaml).
-
-**NOTE**: [config](https://github.com/redhat-chaos/krkn/blob/main/config/config_performance.yaml) can be used if leveraging the [automated way](https://github.com/redhat-chaos/krkn#setting-up-infrastructure-dependencies) to install the infrastructure pieces.
-
-Config components: 
-* [Kraken](#kraken)
-* [Cerberus](#cerberus)
-* [Performance Monitoring](#performance-monitoring)
-* [Tunings](#tunings)
-
-# Kraken 
-This section defines scenarios and specific data to the chaos run 
-
-## Distribution
-Either **openshift** or **kubernetes** depending on the type of cluster you want to run chaos on. 
-The prometheus url/route and bearer token are automatically obtained in case of OpenShift, please set it when the distribution is Kubernetes.
-
-## Exit on failure
-**exit_on_failure**:  Exit when a post action check or cerberus run fails
-
-## Publish kraken status
-**publish_kraken_status**: Can be accessed at http://0.0.0.0:8081 (or what signal_address and port you set in signal address section)
-**signal_state**: State you want kraken to start at; will wait for the RUN signal to start running a chaos iteration. When set to PAUSE before running the scenarios, refer to [signal.md](signal.md) for more details
-
-## Signal Address 
-**signal_address**: Address to listen/post the signal state to
-**port**: port to listen/post the signal state to
-
-## Chaos Scenarios 
-
-**chaos_scenarios**: List of different types of chaos scenarios you want to run with paths to their specific yaml file configurations
-
-If a scenario has a post action check script, it will be run before and after each scenario to validate the component under test starts and ends at the same state
-
-Currently the scenarios are run one after another (in sequence) and will exit if one of the scenarios fail, without moving onto the next one
-
-Chaos scenario types: 
-- container_scenarios     
-- plugin_scenarios
-- node_scenarios
-- time_scenarios
-- cluster_shut_down_scenarios
-- namespace_scenarios
-- zone_outages
-- application_outages
-- pvc_scenarios
-- network_chaos
-
-
-# Cerberus 
-Parameters to set for enabling of cerberus checks at the end of each executed scenario. The given url will pinged after the scenario and post action check have been completed for each scenario and iteration.
-**cerberus_enabled**: Enable it when cerberus is previously installed
-**cerberus_url**: When cerberus_enabled is set to True, provide the url where cerberus publishes go/no-go signal
-**check_applicaton_routes**:  When enabled will look for application unavailability using the routes specified in the cerberus config and fails the run
-
-
-# Performance Monitoring 
-There are 2 main sections defined in this part of the config [metrics](metrics.md) and [alerts](alerts.md); read more about each of these configurations in their respective docs 
-
-# Tunings
-**wait_duration**: Duration to wait between each chaos scenario
-**iterations**: Number of times to execute the scenarios
-**daemon_mode**: True or False; If true, iterations are set to infinity which means that the kraken will cause chaos forever and number of iterations is ignored
-

docs/container_scenarios.md

@@ -1,40 +0,0 @@
-### Container Scenarios
-Kraken uses the `oc exec` command to `kill` specific containers in a pod.
-This can be based on the pods namespace or labels. If you know the exact object you want to kill, you can also specify the specific container name or pod name in the scenario yaml file.
-These scenarios are in a simple yaml format that you can manipulate to run your specific tests or use the pre-existing scenarios to see how it works.
-
-####  Example Config
-The following are the components of Kubernetes for which a basic chaos scenario config exists today.
-
-```
-scenarios:
-- name: "<name of scenario>"
-  namespace: "<specific namespace>" # can specify "*" if you want to find in all namespaces
-  label_selector: "<label of pod(s)>"
-  container_name: "<specific container name>"  # This is optional, can take out and will kill all containers in all pods found under namespace and label
-  pod_names:  # This is optional, can take out and will select all pods with given namespace and label
-  - <pod_name>
-  count: <number of containers to disrupt, default=1>
-  action: <kill signal to run. For example 1 ( hang up ) or 9. Default is set to 1>
-  expected_recovery_time: <number of seconds to wait for container to be running again> (defaults to 120seconds)
-```
-
-#### Post Action
-In all scenarios we do a post chaos check to wait and verify the specific component.
-
-Here there are two options:
-1. Pass a custom script in the main config scenario list that will run before the chaos and verify the output matches post chaos scenario.
-
-See [scenarios/post_action_etcd_container.py](https://github.com/krkn-chaos/krkn/blob/main/scenarios/post_action_etcd_container.py) for an example.
-```
--   container_scenarios:                                 # List of chaos pod scenarios to load.
-            - -    scenarios/container_etcd.yml
-              -    scenarios/post_action_etcd_container.py
-```
-
-2. Allow kraken to wait and check the killed containers until they become ready again. Kraken keeps a list of the specific
-containers that were killed as well as the namespaces and pods to verify all containers that were affected recover properly.
-
-```
-expected_recovery_time: <seconds to wait for container to recover>
-```

docs/contribute.md

@@ -1,95 +0,0 @@
-# How to contribute
-
-Contributions are always appreciated.
-
-How to:
-* [Submit Pull Request](#pull-request)
-* [Fix Formatting](#fix-formatting)
-* [Squash Commits](#squash-commits)
-* [Rebase Upstream](#rebase-with-upstream)
-
-## Pull request
-
-In order to submit a change or a PR, please fork the project and follow these instructions:
-```bash
-$ git clone http://github.com/<me>/krkn
-$ cd krkn
-$ git checkout -b <branch_name>
-$ <make change>
-$ git add <changes>
-$ git commit -a
-$ <insert good message>
-$ git push
-```
-
-## Fix Formatting
-Kraken uses [pre-commit](https://pre-commit.com) framework to maintain the code linting and python code styling.
-The CI would run the pre-commit check on each pull request.
-We encourage our contributors to follow the same pattern while contributing to the code.
-
-The pre-commit configuration file is present in the repository `.pre-commit-config.yaml`.
-It contains the different code styling and linting guides which we use for the application.
-
-The following command can be used to run the pre-commit:
-`pre-commit run --all-files`
-
-If pre-commit is not installed in your system, it can be installed with `pip install pre-commit`.
-
-## Squash Commits
-If there are multiple commits, please rebase/squash multiple commits
-before creating the PR by following:
-
-```bash
-$ git checkout <my-working-branch>
-$ git rebase -i HEAD~<num_of_commits_to_merge>
-   -OR-
-$ git rebase -i <commit_id_of_first_change_commit>
-```
-
-In the interactive rebase screen, set the first commit to `pick`, and all others to `squash`, or whatever else you may need to do.
-
-
-Push your rebased commits (you may need to force), then issue your PR.
-
-```
-$ git push origin <my-working-branch> --force
-```
-
-## Rebase with Upstream
-
-If changes go into the main repository while you're working on your code it is best to rebase your code with the
- upstream, so you stay up to date with all changes and fix any conflicting code changes.
-
-If not already configured, set the upstream url for kraken.
-```
- git remote add upstream https://github.com/krkn-chaos/krkn.git
-```
-
-Rebase to upstream master branch.
-```
-git fetch upstream
-git rebase upstream/master
-git push origin <branch_name> --force
-```
-
-If any errors occur, it will list off any files that have merge issues.
-Edit the files with the code you want to keep. See below for detailed help from Git.
-1. Vi <file(s)>
-2. Resolving-a-merge-conflict-using-the-command-line
-3. git add <all files you edit>
-4. git rebase --continue
-5. Might need to repeat steps 2 through 4 until rebase complete
-6. git status <this will also tell you if you have other files to edit>
-7. git push origin <branch_name> --force  [push the changes to github remote]
-
-
-Merge Conflicts Example
-```
-1. git rebase upstream/kraken
-2. vi run_kraken.py [edit at the indicated places, get rid of arrowed lines and dashes, and apply correct changes]
-3. git add run_kraken.py
-4. git rebase --continue
-5. repeat 2-4 until done
-6. git status <this will also tell you if you have other files to edit>
-7. git push origin <branch_name> --force  [push the changes to github remote]
-```

docs/getting_started.md

@@ -1,51 +0,0 @@
-## Getting Started Running Chaos Scenarios
-
-#### Adding New Scenarios
-Adding a new scenario is as simple as adding a new config file under [scenarios directory](https://github.com/redhat-chaos/krkn/tree/main/scenarios) and defining it in the main kraken [config](https://github.com/redhat-chaos/krkn/blob/main/config/config.yaml#L8).
-You can either copy an existing yaml file and make it your own, or fill in one of the templates below to suit your needs.
-
-### Templates
-#### Pod Scenario Yaml Template
-For example, for adding a pod level scenario for a new application, refer to the sample scenario below to know what fields are necessary and what to add in each location:
-```
-# yaml-language-server: $schema=../plugin.schema.json
-- id: kill-pods
-  config:
-    namespace_pattern: ^<namespace>$
-    label_selector: <pod label>
-    kill: <number of pods to kill>
-    krkn_pod_recovery_time: <expected time for the pod to become ready>
-```
-
-#### Node Scenario Yaml Template
-
-```
-node_scenarios:
-  - actions:  # Node chaos scenarios to be injected.
-    - <chaos scenario>
-    - <chaos scenario>
-    node_name: <node name>  # Can be left blank.
-    label_selector: <node label>
-    instance_kill_count: <number of nodes on which to perform action>
-    timeout: <duration to wait for completion>
-    cloud_type: <cloud provider>
-```
-
-
-#### Time Chaos Scenario Template
-```
-time_scenarios:
-  - action: 'skew_time' or 'skew_date'
-    object_type: 'pod' or 'node'
-    label_selector: <label of pod or node>
-```
-
-
-### Common Scenario Edits
-If you just want to make small changes to pre-existing scenarios, feel free to edit the scenario file itself.
-
-#### Example of Quick Pod Scenario Edit:
-If you want to kill 2 pods instead of 1 in any of the pre-existing scenarios, you can either edit the number located at filters -> randomSample -> size or the runs under the config -> runStrategy section.
-
-#### Example of Quick Nodes Scenario Edit:
-If your cluster is build on GCP instead of AWS, just change the cloud type in the node_scenarios_example.yml file.

docs/index.md

@@ -1,310 +0,0 @@
-## Chaos Testing Guide
-
-
-### Table of Contents
-* [Introduction](#introduction)
-* [Test Stratagies and Methodology](#test-strategies-and-methodology)
-* [Best Practices](#best-practices)
-* [Tooling](#tooling)
-  * [Workflow](#workflow)
-  * [Cluster recovery checks, metrics evaluation and pass/fail criteria](#cluster-recovery-checks-metrics-evaluation-and-passfail-criteria)
-* [Scenarios](#scenarios)
-* [Test Environment Recommendations - how and where to run chaos tests](#test-environment-recommendations---how-and-where-to-run-chaos-tests)
-* [Chaos testing in Practice](#chaos-testing-in-practice)
-  * [OpenShift oraganization](#openshift-organization)
-  * [startx-lab](#startx-lab)
-
-
-### Introduction
-There are a couple of false assumptions that users might have when operating and running their applications in distributed systems:
-
-The network is reliable.
-There is zero latency.
-Bandwidth is infinite.
-The network is secure.
-Topology never changes.
-The network is homogeneous.
-Consistent resource usage with no spikes.
-All shared resources are available from all places.
-
-Various assumptions led to a number of outages in production environments in the past.  The services suffered from poor performance or were inaccessible to the customers, leading to missing Service Level Agreement uptime promises, revenue loss, and a degradation in the perceived reliability of said services.
-
-How can we best avoid this from happening? This is where Chaos testing can add value.
-
-
-
-### Test Strategies and Methodology
-Failures in production are costly. To help mitigate risk to service health, consider the following strategies and approaches to service testing:
-
-- Be proactive vs reactive. We have different types of test suites in place - unit, integration and end-to-end - that help expose bugs in code in a controlled environment.  Through implementation of a chaos engineering strategy, we can discover potential causes of service degradation. We need to understand the systems' behavior under unpredictable conditions in order to find the areas to harden, and use performance data points to size the clusters to handle failures in order to keep downtime to a minimum.
-
-- Test the resiliency of a system under turbulent conditions by running tests that are designed to disrupt while monitoring the systems adaptability and performance:
-  - Establish and define your steady state and metrics - understand the behavior and performance under stable conditions and define the metrics that will be used to evaluate the system’s behavior.  Then decide on acceptable outcomes before injecting chaos.
-  - Analyze the statuses and metrics of all components during the chaos test runs.
-  - Improve the areas that are not resilient and performant by comparing the key metrics and Service Level Objectives (SLOs) to the stable conditions before the chaos.
-  For example: evaluating the API server latency or application uptime to see if the key performance indicators and service level indicators are still within acceptable limits.
-
-
-
-
-### Best Practices
-Now that we understand the test methodology, let us take a look at the best practices for an Kubernetes cluster.  On that platform there are user applications and cluster workloads that need to be designed for stability and to provide the best user experience possible:
-
-- Alerts with appropriate severity should get fired.
-  - Alerts are key to identify when a component starts degrading, and can help focus the investigation effort on affected system components.
-  - Alerts should have proper severity, description, notification policy, escalation policy, and SOP in order to reduce MTTR for responding SRE or Ops resources.
-  - Detailed information on the alerts consistency can be found [here](https://github.com/openshift/enhancements/blob/master/enhancements/monitoring/alerting-consistency.md).
-
-- Minimal performance impact - Network, CPU, Memory, Disk, Throughput etc.
-  - The system, as well as the applications, should be designed to have minimal performance impact during disruptions to ensure stability and also to avoid hogging resources that other applications can use.
-We want to look at this in terms of CPU, Memory, Disk, Throughput, Network etc.
-  - We want to look at this in terms of CPU, Memory, Disk, Throughput, Network etc.
-
-- Appropriate CPU/Memory limits set to avoid performance throttling and OOM kills.
-  - There might be rogue applications hogging resources ( CPU/Memory ) on the nodes which might lead to applications underperforming or worse getting OOM killed. It is important to ensure that applications and system components have reserved resources for the kube-scheduler to take into consideration in order to keep them performing at the expected levels.
-
-- Services dependent on the system under test need to handle the failure gracefully to avoid performance degradation and downtime - appropriate timeouts.
-  - In a distributed system, services deployed coordinate with each other and might have external dependencies. Each of the services deployed as a deployment, pod, or container, need to handle the downtime of other dependent services gracefully instead of crashing due to not having appropriate timeouts, fallback logic etc.
-
-- Proper node sizing to avoid cascading failures and ensure cluster stability especially when the cluster is large and dense
-  - The platform needs to be sized taking into account the resource usage spikes that might occur during chaotic events. For example, if one of the main nodes goes down, the other two main nodes need to have enough resources to handle the load. The resource usage depends on the load or number of objects that are running being managed by the Control Plane ( Api Server, Etcd, Controller and Scheduler ). As such, it’s critical to test such conditions, understand the behavior, and leverage the data to size the platform appropriately. This can help keep the applications stable during unplanned events without the control plane undergoing cascading failures which can potentially bring down the entire cluster.
-
-- Proper node sizing to avoid application failures and maintain stability.
-  - An application pod might use more resources during reinitialization after a crash, so it is important to take that into account for sizing the nodes in the cluster to accommodate it. For example, monitoring solutions like Prometheus need high amounts of memory to replay the write ahead log ( WAL ) when it restarts. As such, it’s critical to test such conditions, understand the behavior, and leverage the data to size the platform appropriately. This can help keep the application stable during unplanned events without undergoing degradation in performance or even worse hog the resources on the node which can impact other applications and system pods.
-
-
-- Minimal initialization time and fast recovery logic.
-  - The controller watching the component should recognize a failure as soon as possible. The component needs to have minimal initialization time to avoid extended downtime or overloading the replicas if it is a highly available configuration. The cause of failure can be because of issues with the infrastructure on top of which it is running, application failures, or because of service failures that it depends on.
-
-- High Availability deployment strategy.
-  - There should be multiple replicas ( both Kubernetes and application control planes ) running preferably in different availability zones to survive outages while still serving the user/system requests. Avoid single points of failure.
-- Backed by persistent storage
-  - It is important to have the system/application backed by persistent storage. This is especially important in cases where the application is a database or a stateful application given that a node, pod, or container failure will wipe off the data.
-
-- There should be fallback routes to the backend in case of using CDN, for example, Akamai in case of console.redhat.com - a managed service deployed on top of Kubernetes dedicated:
-  - Content delivery networks (CDNs) are commonly used to host resources such as images, JavaScript files, and CSS. The average web page is nearly 2 MB in size, and offloading heavy resources to third-parties is extremely effective for reducing backend server traffic and latency. However, this makes each CDN an additional point of failure for every site that relies on it. If the CDN fails, its customers could also fail.
-  - To test how the application reacts to failures, drop all network traffic between the system and CDN. The application should still serve the content to the user irrespective of the failure.
-
-- Appropriate caching and Content Delivery Network should be enabled to be performant and usable when there is a latency on the client side.
-  - Not every user or machine has access to unlimited bandwidth, there might be a delay on the user side ( client ) to access the API’s due to limited bandwidth, throttling or latency depending on the geographic location. It is important to inject latency between the client and API calls to understand the behavior and optimize things including caching wherever possible, using CDN’s or opting for different protocols like HTTP/2 or HTTP/3 vs HTTP.
-
-
-
-
-### Tooling
-Now that we looked at the best practices, In this section, we will go through how [Kraken](https://github.com/redhat-chaos/krkn) - a chaos testing framework can help test the resilience of Kubernetes and make sure the applications and services are following the best practices.
-
-#### Workflow
-Let us start by understanding the workflow of kraken: the user will start by running kraken by pointing to a specific Kubernetes cluster using kubeconfig to be able to talk to the platform on top of which the Kubernetes cluster is hosted. This can be done by either the oc/kubectl API or the cloud API. Based on the configuration of kraken, it will inject specific chaos scenarios as shown below, talk to [Cerberus](https://github.com/redhat-chaos/cerberus) to get the go/no-go signal representing the overall health of the cluster ( optional - can be turned off ), scrapes metrics from in-cluster prometheus given a metrics profile with the promql queries and stores them long term in Elasticsearch configured  ( optional - can be turned off ), evaluates the promql expressions specified in the alerts profile ( optional - can be turned off ) and aggregated everything to set the pass/fail i.e. exits 0 or 1. More about the metrics collection, cerberus and metrics evaluation can be found in the next section.
-
-![Kraken workflow](../media/kraken-workflow.png)
-
-#### Cluster recovery checks, metrics evaluation and pass/fail criteria
-- Most of the scenarios have built in checks to verify if the targeted component recovered from the failure after the specified duration of time but there might be cases where other components might have an impact because of a certain failure and it’s extremely important to make sure that the system/application is healthy as a whole post chaos. This is exactly where [Cerberus](https://github.com/redhat-chaos/cerberus) comes to the rescue.
-If the monitoring tool, cerberus is enabled it will consume the signal and continue running chaos or not based on that signal.
-
-- Apart from checking the recovery and cluster health status, it’s equally important to evaluate the performance metrics like latency, resource usage spikes, throughput, etcd health like disk fsync, leader elections etc. To help with this, Kraken has a way to evaluate promql expressions from the incluster prometheus and set the exit status to 0 or 1 based on the severity set for each of the query. Details on how to use this feature can be found [here](https://github.com/redhat-chaos/krkn#alerts).
-
-- The overall pass or fail of kraken is based on the recovery of the specific component (within a certain amount of time), the cerberus health signal which tracks the health of the entire cluster and metrics evaluation from incluster prometheus.
-
-
-
-
-### Scenarios
-
-Let us take a look at how to run the chaos scenarios on your Kubernetes clusters using Kraken-hub - a lightweight wrapper around Kraken to ease the runs by providing the ability to run them by just running container images using podman with parameters set as environment variables. This eliminates the need to carry around and edit configuration files and makes it easy for any CI framework integration. Here are the scenarios supported:
-
-- Pod Scenarios ([Documentation](https://github.com/redhat-chaos/krkn-hub/blob/main/docs/pod-scenarios.md))
-  - Disrupts Kubernetes/Kubernetes and applications deployed as pods:
-    - Helps understand the availability of the application, the initialization timing and recovery status.
-  - [Demo](https://asciinema.org/a/452351?speed=3&theme=solarized-dark)
-
-- Container Scenarios ([Documentation](https://github.com/redhat-chaos/krkn-hub/blob/main/docs/container-scenarios.md))
-  - Disrupts Kubernetes/Kubernetes and applications deployed as containers running as part of a pod(s) using a specified kill signal to mimic failures:
-    - Helps understand the impact and recovery timing when the program/process running in the containers are disrupted - hangs, paused, killed etc., using various kill signals, i.e. SIGHUP, SIGTERM, SIGKILL etc.
-  - [Demo](https://asciinema.org/a/BXqs9JSGDSEKcydTIJ5LpPZBM?speed=3&theme=solarized-dark)
-
-- Node Scenarios ([Documentation](https://github.com/redhat-chaos/krkn-hub/blob/main/docs/node-scenarios.md))
-  - Disrupts nodes as part of the cluster infrastructure by talking to the cloud API. AWS, Azure, GCP, OpenStack and Baremetal are the supported platforms as of now. Possible disruptions include:
-    - Terminate nodes
-    - Fork bomb inside the node
-    - Stop the node
-    - Crash the kubelet running on the node
-    - etc.
-  - [Demo](https://asciinema.org/a/ANZY7HhPdWTNaWt4xMFanF6Q5)
-
-- Zone Outages ([Documentation](https://github.com/redhat-chaos/krkn-hub/blob/main/docs/zone-outages.md))
-  - Creates outage of availability zone(s) in a targeted region in the public cloud where the Kubernetes cluster is running by tweaking the network acl of the zone to simulate the failure, and that in turn will stop both ingress and egress traffic from all nodes in a particular zone for the specified duration and reverts it back to the previous state.
-    - Helps understand the impact on both Kubernetes/Kubernetes control plane as well as applications and services running on the worker nodes in that zone.
-    - Currently, only set up for AWS cloud platform: 1 VPC and multiples subnets within the VPC can be specified.
-    - [Demo](https://asciinema.org/a/452672?speed=3&theme=solarized-dark)
-
-- Application Outages ([Documentation](https://github.com/redhat-chaos/krkn-hub/blob/main/docs/application-outages.md))
-  - Scenario to block the traffic ( Ingress/Egress ) of an application matching the labels for the specified duration of time to understand the behavior of the service/other services which depend on it during the downtime.
-    - Helps understand how the dependent services react to the unavailability.
-    - [Demo](https://asciinema.org/a/452403?speed=3&theme=solarized-dark)
-
-- Power Outages ([Documentation](https://github.com/redhat-chaos/krkn-hub/blob/main/docs/power-outages.md))
-  - This scenario imitates a power outage by shutting down of the entire cluster for a specified duration of time, then restarts all the nodes after the specified time and checks the health of the cluster.
-    - There are various use cases in the customer environments. For example, when some of the clusters are shutdown in cases where the applications are not needed to run in a particular time/season in order to save costs.
-    - The nodes are stopped in parallel to mimic a power outage i.e., pulling off the plug
-  - [Demo](https://asciinema.org/a/r0zLbh70XK7gnc4s5v0ZzSXGo)
-
-- Resource Hog
-  - Hogs CPU, Memory and IO on the targeted nodes
-    - Helps understand if the application/system components have reserved resources to not get disrupted because of rogue applications, or get performance throttled.
-      - CPU Hog ([Documentation](https://github.com/redhat-chaos/krkn-hub/blob/main/docs/node-cpu-hog.md), [Demo](https://asciinema.org/a/452762))
-      - Memory Hog ([Documentation](https://github.com/redhat-chaos/krkn-hub/blob/main/docs/node-memory-hog.md), [Demo](https://asciinema.org/a/452742?speed=3&theme=solarized-dark))
-
-- Time Skewing ([Documentation](https://github.com/redhat-chaos/krkn-hub/blob/main/docs/time-scenarios.md))
-  - Manipulate the system time and/or date of specific pods/nodes.
-    - Verify scheduling of objects so they continue to work.
-    - Verify time gets reset properly.
-
-- Namespace Failures ([Documentation](https://github.com/redhat-chaos/krkn-hub/blob/main/docs/namespace-scenarios.md))
-  - Delete namespaces for the specified duration.
-    - Helps understand the impact on other components and tests/improves recovery time of the components in the targeted namespace.
-
-- Persistent Volume Fill ([Documentation](https://github.com/redhat-chaos/krkn-hub/blob/main/docs/pvc-scenarios.md))
-  - Fills up the persistent volumes, up to a given percentage, used by the pod for the specified duration.
-    - Helps understand how an application deals when it is no longer able to write data to the disk. For example, kafka’s behavior when it is not able to commit data to the disk.
-
-- Network Chaos ([Documentation](https://github.com/redhat-chaos/krkn-hub/blob/main/docs/network-chaos.md))
-  - Scenarios supported includes:
-    - Network latency
-    - Packet loss
-    - Interface flapping
-    - DNS errors
-    - Packet corruption
-    - Bandwidth limitation
-
-
-
-
-### Test Environment Recommendations - how and where to run chaos tests
-
-Let us take a look at few recommendations on how and where to run the chaos tests:
-
-- Run the chaos tests continuously in your test pipelines:
-  - Software, systems, and infrastructure does change – and the condition/health of each can change pretty rapidly. A good place to run tests is in your CI/CD pipeline running on a regular cadence.
-
-- Run the chaos tests manually to learn from the system:
-  - When running a Chaos scenario or Fault tests, it is more important to understand how the system responds and reacts, rather than mark the execution as pass or fail.
-  - It is important to define the scope of the test before the execution to avoid some issues from masking others.
-
-- Run the chaos tests in production environments or mimic the load in staging environments:
-  - As scary as a thought about testing in production is, production is the environment that users are in and traffic spikes/load are real. To fully test the robustness/resilience of a production system, running Chaos Engineering experiments in a production environment will provide needed insights. A couple of things to keep in mind:
-    - Minimize blast radius and have a backup plan in place to make sure the users and customers do not undergo downtime.
-    - Mimic the load in a staging environment in case Service Level Agreements  are too tight to cover any downtime.
-
-- Enable Observability:
-  - Chaos Engineering Without Observability ... Is Just Chaos.
-  - Make sure to have logging and monitoring installed on the cluster to help with understanding the behaviour as to why it is happening. In case of running the tests in the CI where it is not humanly possible to monitor the cluster all the time, it is recommended to leverage Cerberus to capture the state during the runs and metrics collection in Kraken to store metrics long term even after the cluster is gone.
-  - Kraken ships with dashboards that will help understand API, Etcd and Kubernetes cluster level stats and performance metrics.
-  - Pay attention to Prometheus alerts. Check if they are firing as expected.
-
-- Run multiple chaos tests at once to mimic the production outages:
-  - For example, hogging both IO and Network at the same time instead of running them separately to observe the impact.
-  - You might have existing test cases, be it related to Performance, Scalability or QE. Run the chaos in the background during the test runs to observe the impact. Signaling feature in Kraken can help with coordinating the chaos runs i.e., start, stop, pause the scenarios based on the state of the other test jobs.
-
-
-#### Chaos testing in Practice
-
-##### OpenShift organization
-Within the OpenShift organization we use kraken to perform chaos testing throughout a release before the code is available to customers.
-
-    1. We execute kraken during our regression test suite.
-
-        i. We cover each of the chaos scenarios across different clouds.
-
-            a. Our testing is predominantly done on AWS, Azure and GCP.
-
-    2. We run the chaos scenarios during a long running reliability test.
-
-        i. During this test we perform different types of tasks by different users on the cluster.
-
-        ii. We have added the execution of kraken to perform at certain times throughout the long running test and monitor the health of the cluster.
-
-        iii. This test can be seen here: https://github.com/openshift/svt/tree/master/reliability-v2
-
-    3. We are starting to add in test cases that perform chaos testing during an upgrade (not many iterations of this have been completed).
-
-
-##### startx-lab
-
-**NOTE**: Requests for enhancements and any issues need to be filed at the mentioned links given that they are not natively supported in Kraken.
-
-The following content covers the implementation details around how Startx is leveraging Kraken:
-
-* Using kraken as part of a tekton pipeline
-
-You can find on [artifacthub.io](https://artifacthub.io/packages/search?kind=7&ts_query_web=kraken) the 
-[kraken-scenario](https://artifacthub.io/packages/tekton-task/startx-tekton-catalog/kraken-scenario) `tekton-task`
-which can be used to start a kraken chaos scenarios as part of a chaos pipeline.
-
-To use this task, you must have :
-
-  - Openshift pipeline enabled (or tekton CRD loaded for Kubernetes clusters)
-  - 1 Secret named `kraken-aws-creds` for scenarios using aws
-  - 1 ConfigMap named `kraken-kubeconfig` with credentials to the targeted cluster
-  - 1 ConfigMap named `kraken-config-example` with kraken configuration file (config.yaml)
-  - 1 ConfigMap named `kraken-common-example` with all kraken related files
-  - The `pipeline` SA with be autorized to run with priviveged SCC
-
-You can create theses resources using the following sequence :
-
-```bash
-oc project default
-oc adm policy add-scc-to-user privileged -z pipeline
-oc apply -f https://github.com/startxfr/tekton-catalog/raw/stable/task/kraken-scenario/0.1/samples/common.yaml
-```
-
-Then you must change content of `kraken-aws-creds` secret, `kraken-kubeconfig` and `kraken-config-example` configMap
-to reflect your cluster configuration. Refer to the [kraken configuration](https://github.com/redhat-chaos/krkn/blob/main/config/config.yaml)
-and [configuration examples](https://github.com/startxfr/tekton-catalog/blob/stable/task/kraken-scenario/0.1/samples/) 
-for details on how to configure theses resources.
-
-* Start as a single taskrun
-
-```bash
-oc apply -f https://github.com/startxfr/tekton-catalog/raw/stable/task/kraken-scenario/0.1/samples/taskrun.yaml
-```
-
-* Start as a pipelinerun
-
-```yaml
-oc apply -f https://github.com/startxfr/tekton-catalog/raw/stable/task/kraken-scenario/0.1/samples/pipelinerun.yaml
-```
-
-* Deploying kraken using a helm-chart
-
-You can find on [artifacthub.io](https://artifacthub.io/packages/search?kind=0&ts_query_web=kraken) the
-[chaos-kraken](https://artifacthub.io/packages/helm/startx/chaos-kraken) `helm-chart`
-which can be used to deploy a kraken chaos scenarios.
-
-Default configuration create the following resources :
-
-  - 1 project named **chaos-kraken**
-  - 1 scc with privileged context for kraken deployment
-  - 1 configmap with kraken 21 generic scenarios, various scripts and configuration
-  - 1 configmap with kubeconfig of the targeted cluster
-  - 1 job named kraken-test-xxx
-  - 1 service to the kraken pods
-  - 1 route to the kraken service
-
-```bash
-# Install the startx helm repository
-helm repo add startx https://startxfr.github.io/helm-repository/packages/
-# Install the kraken project
-helm install --set project.enabled=true chaos-kraken-project  startx/chaos-kraken
-# Deploy the kraken instance
-helm install \
---set kraken.enabled=true \
---set kraken.aws.credentials.region="eu-west-3" \
---set kraken.aws.credentials.key_id="AKIAXXXXXXXXXXXXXXXX" \
---set kraken.aws.credentials.secret="xxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxxx" \
---set kraken.kubeconfig.token.server="https://api.mycluster:6443" \
---set kraken.kubeconfig.token.token="sha256~XXXXXXXXXX_PUT_YOUR_TOKEN_HERE_XXXXXXXXXXXX" \
--n chaos-kraken \
-chaos-kraken-instance startx/chaos-kraken
-```

docs/installation.md

@@ -1,45 +0,0 @@
-## Installation
-
-The following ways are supported to run Kraken:
-
-- Standalone python program through Git.
-- Containerized version using either Podman or Docker as the runtime via [Krkn-hub](https://github.com/krkn-chaos/krkn-hub)
-- Kubernetes or OpenShift deployment ( unsupported )
-
-**NOTE**: It is recommended to run Kraken external to the cluster ( Standalone or Containerized ) hitting the Kubernetes/OpenShift API as running it internal to the cluster might be disruptive to itself and also might not report back the results if the chaos leads to cluster's API server instability.
-
-**NOTE**: To run Kraken on Power (ppc64le) architecture, build and run a containerized version by following the
- instructions given [here](https://github.com/krkn-chaos/krkn/blob/main/containers/build_own_image-README.md).
-
-**NOTE**: Helper functions for interactions in Krkn are part of [krkn-lib](https://github.com/redhat-chaos/krkn-lib). 
-Please feel free to reuse and expand them as you see fit when adding a new scenario or expanding 
-the capabilities of the current supported scenarios.
-
-
-### Git
-
-#### Clone the repository
-Pick the latest stable release to install [here](https://github.com/krkn-chaos/krkn/releases).
-```
-$ git clone https://github.com/krkn-chaos/krkn.git --branch <release version>
-$ cd krkn
-```
-
-#### Install the dependencies
-```
-$ python3.9 -m venv chaos
-$ source chaos/bin/activate
-$ pip3.9 install -r requirements.txt
-```
-
-**NOTE**: Make sure python3-devel and latest pip versions are installed on the system. The dependencies install has been tested with pip >= 21.1.3 versions.
-
-#### Run
-```
-$ python3.9 run_kraken.py --config <config_file_location>
-```
-
-### Run containerized version
-[Krkn-hub](https://github.com/krkn-chaos/krkn-hub) is a wrapper that allows running Krkn chaos scenarios via podman or docker runtime with scenario parameters/configuration defined as environment variables.
-
-Refer [instructions](https://github.com/krkn-chaos/krkn-hub#supported-chaos-scenarios) to get started.

docs/managedcluster_scenarios.md

@@ -1,36 +0,0 @@
-### ManagedCluster Scenarios
-
-[ManagedCluster](https://open-cluster-management.io/concepts/managedcluster/) scenarios provide a way to integrate kraken with [Open Cluster Management (OCM)](https://open-cluster-management.io/) and [Red Hat Advanced Cluster Management for Kubernetes (ACM)](https://www.redhat.com/en/technologies/management/advanced-cluster-management).
-
-ManagedCluster scenarios leverage [ManifestWorks](https://open-cluster-management.io/concepts/manifestwork/) to inject faults into the ManagedClusters.
-
-The following ManagedCluster chaos scenarios are supported:
-
-1. **managedcluster_start_scenario**: Scenario to start the ManagedCluster instance.
-2. **managedcluster_stop_scenario**: Scenario to stop the ManagedCluster instance.
-3. **managedcluster_stop_start_scenario**: Scenario to stop and then start the ManagedCluster instance.
-4. **start_klusterlet_scenario**: Scenario to start the klusterlet of the ManagedCluster instance.
-5. **stop_klusterlet_scenario**: Scenario to stop the klusterlet of the ManagedCluster instance.
-6. **stop_start_klusterlet_scenario**: Scenario to stop and start the klusterlet of the ManagedCluster instance.
-
-ManagedCluster scenarios can be injected by placing the ManagedCluster scenarios config files under `managedcluster_scenarios` option in the Kraken config. Refer to [managedcluster_scenarios_example](https://github.com/redhat-chaos/krkn/blob/main/scenarios/kube/managedcluster_scenarios_example.yml) config file.
-
-```
-managedcluster_scenarios:
-  - actions:                                                        # ManagedCluster chaos scenarios to be injected
-    - managedcluster_stop_start_scenario
-    managedcluster_name: cluster1                                   # ManagedCluster on which scenario has to be injected; can set multiple names separated by comma
-    # label_selector:                                               # When managedcluster_name is not specified, a ManagedCluster with matching label_selector is selected for ManagedCluster chaos scenario injection
-    instance_count: 1                                               # Number of managedcluster to perform action/select that match the label selector
-    runs: 1                                                         # Number of times to inject each scenario under actions (will perform on same ManagedCluster each time)
-    timeout: 420                                                    # Duration to wait for completion of ManagedCluster scenario injection
-                                                                    # For OCM to detect a ManagedCluster as unavailable, have to wait 5*leaseDurationSeconds
-                                                                    # (default leaseDurationSeconds = 60 sec)
-  - actions:
-    - stop_start_klusterlet_scenario
-    managedcluster_name: cluster1
-    # label_selector:
-    instance_count: 1
-    runs: 1
-    timeout: 60
-```

docs/network_chaos.md

@@ -1,49 +0,0 @@
-### Network chaos
-Scenario to introduce network latency, packet loss, and bandwidth restriction in the Node's host network interface. The purpose of this scenario is to observe faults caused by random variations in the network.
-
-##### Sample scenario config for egress traffic shaping
-```
-network_chaos:                                    # Scenario to create an outage by simulating random variations in the network.
-  duration: 300                                   # In seconds - duration network chaos will be applied.
-  node_name:                                      # Comma separated node names on which scenario has to be injected.
-  label_selector: node-role.kubernetes.io/master  # When node_name is not specified, a node with matching label_selector is selected for running the scenario.
-  instance_count: 1                               # Number of nodes in which to execute network chaos.
-  interfaces:                                     # List of interface on which to apply the network restriction.
-  - "ens5"                                        # Interface name would be the Kernel host network interface name.
-  execution: serial|parallel                      # Execute each of the egress options as a single scenario(parallel) or as separate scenario(serial).
-  egress:
-    latency: 500ms
-    loss: 50%                                    # percentage
-    bandwidth: 10mbit
-```
-
-##### Sample scenario config for ingress traffic shaping (using a plugin)
-'''
-- id: network_chaos
-  config:
-    node_interface_name:                            # Dictionary with key as node name(s) and value as a list of its interfaces to test
-      ip-10-0-128-153.us-west-2.compute.internal:
-        - ens5
-        - genev_sys_6081
-    label_selector: node-role.kubernetes.io/master  # When node_interface_name is not specified, nodes with matching label_selector is selected for node chaos scenario injection
-    instance_count: 1                               # Number of nodes to perform action/select that match the label selector
-    kubeconfig_path: ~/.kube/config                 # Path to kubernetes config file. If not specified, it defaults to ~/.kube/config
-    execution_type: parallel                        # Execute each of the ingress options as a single scenario(parallel) or as separate scenario(serial).
-    network_params:
-        latency: 500ms
-        loss: '50%'
-        bandwidth: 10mbit
-    wait_duration: 120
-    test_duration: 60
-  '''
-
-  Note: For ingress traffic shaping, ensure that your node doesn't have any [IFB](https://wiki.linuxfoundation.org/networking/ifb) interfaces already present. The scenario relies on creating IFBs to do the shaping, and they are deleted at the end of the scenario.
-
-
-##### Steps
- - Pick the nodes to introduce the network anomaly either from node_name or label_selector.
- - Verify interface list in one of the nodes or use the interface with a default route, as test interface, if no interface is specified by the user.
- - Set traffic shaping config on node's interface using tc and netem.
- - Wait for the duration time.
- - Remove traffic shaping config on node's interface.
- - Remove the job that spawned the pod.

docs/node_scenarios.md

@@ -1,115 +0,0 @@
-### Node Scenarios
-
-The following node chaos scenarios are supported:
-
-1. **node_start_scenario**: Scenario to stop the node instance.
-2. **node_stop_scenario**: Scenario to stop the node instance.
-3. **node_stop_start_scenario**: Scenario to stop and then start the node instance. Not supported on VMware.
-4. **node_termination_scenario**: Scenario to terminate the node instance.
-5. **node_reboot_scenario**: Scenario to reboot the node instance.
-6. **stop_kubelet_scenario**: Scenario to stop the kubelet of the node instance.
-7. **stop_start_kubelet_scenario**: Scenario to stop and start the kubelet of the node instance.
-8. **node_crash_scenario**: Scenario to crash the node instance.
-9. **stop_start_helper_node_scenario**: Scenario to stop and start the helper node and check service status.
-
-
-**NOTE**: If the node does not recover from the node_crash_scenario injection, reboot the node to get it back to Ready state.
-
-**NOTE**: node_start_scenario, node_stop_scenario, node_stop_start_scenario, node_termination_scenario
-, node_reboot_scenario and stop_start_kubelet_scenario are supported on AWS, Azure, OpenStack, BareMetal, GCP
-, VMware and Alibaba.
-
-
-#### AWS
-
-Cloud setup instructions can be found [here](cloud_setup.md#aws). Sample scenario config can be found [here](https://github.com/krkn-chaos/krkn/blob/main/scenarios/openshift/aws_node_scenarios.yml).
-
-
-
-#### Baremetal
-
-Sample scenario config can be found [here](https://github.com/krkn-chaos/krkn/blob/main/scenarios/openshift/baremetal_node_scenarios.yml).
-
-**NOTE**: Baremetal requires setting the IPMI user and password to power on, off, and reboot nodes, using the config options `bm_user` and `bm_password`. It can either be set in the root of the entry in the scenarios config, or it can be set per machine.
-
-If no per-machine addresses are specified, kraken attempts to use the BMC value in the BareMetalHost object. To list them, you can do 'oc get bmh -o wide --all-namespaces'. If the BMC values are blank, you must specify them per-machine using the config option 'bmc_addr' as specified below.
-
-For per-machine settings, add a "bmc_info" section to the entry in the scenarios config. Inside there, add a configuration section using the node name. In that, add per-machine settings. Valid settings are 'bmc_user', 'bmc_password', and 'bmc_addr'.
-See the example node scenario or the example below.
-
-**NOTE**: Baremetal requires oc (openshift client) be installed on the machine running Kraken.
-
-**NOTE**: Baremetal machines are fragile. Some node actions can occasionally corrupt the filesystem if it does not shut down properly, and sometimes the kubelet does not start properly.
-
-
-
-#### Docker
-
-The Docker provider can be used to run node scenarios against kind clusters.
-
-[kind](https://kind.sigs.k8s.io/) is a tool for running local Kubernetes clusters using Docker container "nodes".
-
-kind was primarily designed for testing Kubernetes itself, but may be used for local development or CI.
-
-
-
-#### GCP
-Cloud setup instructions can be found [here](cloud_setup.md#gcp). Sample scenario config can be found [here](https://github.com/krkn-chaos/krkn/blob/main/scenarios/openshift/gcp_node_scenarios.yml).
-
-
-#### Openstack
-
-How to set up Openstack cli to run node scenarios is defined [here](cloud_setup.md#openstack).
-
-The supported node level chaos scenarios on an OPENSTACK cloud are `node_stop_start_scenario`, `stop_start_kubelet_scenario` and `node_reboot_scenario`.
-
-**NOTE**: For `stop_start_helper_node_scenario`,  visit [here](https://github.com/redhat-cop/ocp4-helpernode) to learn more about the helper node and its usage.
-
-To execute the scenario, ensure the value for `ssh_private_key` in the node scenarios config file is set with the correct private key file path for ssh connection to the helper node. Ensure passwordless ssh is configured on the host running Kraken and the helper node to avoid connection errors.
-
-
-
-#### Azure
-
-Cloud setup instructions can be found [here](cloud_setup.md#azure). Sample scenario config can be found [here](https://github.com/krkn-chaos/krkn/blob/main/scenarios/openshift/azure_node_scenarios.yml).
-
-
-
-#### Alibaba
-
-How to set up Alibaba cli to run node scenarios is defined [here](cloud_setup.md#alibaba).
-
-**NOTE**: There is no "terminating" idea in Alibaba, so any scenario with terminating will "release" the node
-. Releasing a node is 2 steps, stopping the node and then releasing it.
-
-
-
-#### VMware
-How to set up VMware vSphere to run node scenarios is defined [here](cloud_setup.md#vmware)
-
-This cloud type uses a different configuration style, see actions below and [example config file](../scenarios/openshift/vmware_node_scenarios.yml)
-
-- vmware-node-terminate
-- vmware-node-reboot
-- vmware-node-stop
-- vmware-node-start
-
-
-
-#### IBMCloud
-How to set up IBMCloud to run node scenarios is defined [here](cloud_setup.md#ibmcloud)
-
-This cloud type uses a different configuration style, see actions below and [example config file](../scenarios/openshift/ibmcloud_node_scenarios.yml)
-
-- ibmcloud-node-terminate
-- ibmcloud-node-reboot
-- ibmcloud-node-stop
-- ibmcloud-node-start
-
-
-
-#### General
-
-**NOTE**: The `node_crash_scenario` and `stop_kubelet_scenario` scenario is supported independent of the cloud platform.
-
-Use 'generic' or do not add the 'cloud_type' key to your scenario if your cluster is not set up using one of the current supported cloud types.

docs/performance_dashboards.md

@@ -1,12 +0,0 @@
-## Performance dashboards
-
-Kraken supports installing a mutable grafana on the cluster with the dashboards loaded to help with monitoring the cluster for things like resource usage to find the outliers, API stats, Etcd health, Critical alerts etc. It can be deployed by enabling the following in the config:
-
-```
-performance_monitoring:
-    deploy_dashboards: True
-```
-
-The route and credentials to access the dashboards will be printed on the stdout before Kraken starts creating chaos. The dashboards can be edited/modified to include your queries of interest.
-
-**NOTE**: The dashboards leverage Prometheus for scraping the metrics off of the cluster and currently only supports OpenShift since Prometheus is setup on the cluster by default and leverages routes object to expose the grafana dashboards externally.

docs/pod_network_scenarios.md

@@ -1,46 +0,0 @@
-## Pod network Scenarios
-
-### Pod outage
-Scenario to block the traffic ( Ingress/Egress ) of a pod matching the labels for the specified duration of time to understand the behavior of the service/other services which depend on it during downtime. This helps with planning the requirements accordingly, be it improving the timeouts or tweaking the alerts etc.
-With the current network policies, it is not possible to explicitly block ports which are enabled by allowed network policy rule. This chaos scenario addresses this issue by using OVS flow rules to block ports related to the pod. It supports OpenShiftSDN and OVNKubernetes based networks.
-
-##### Sample scenario config (using a plugin)
-```
-- id: pod_network_outage
-  config:
-    namespace: openshift-console   # Required - Namespace of the pod to which filter need to be applied
-    direction:                     # Optioinal - List of directions to apply filters
-        - ingress                  # Blocks ingress traffic, Default both egress and ingress
-    ingress_ports:                 # Optional - List of ports to block traffic on
-        - 8443                     # Blocks 8443, Default [], i.e. all ports.
-    label_selector: 'component=ui' # Blocks access to openshift console
-```
-### Pod Network shaping
-Scenario to introduce network latency, packet loss, and bandwidth restriction in the Pod's network interface. The purpose of this scenario is to observe faults caused by random variations in the network.
-
-##### Sample scenario config for egress traffic shaping (using plugin)
-```
-- id: pod_egress_shaping
-  config:
-    namespace: openshift-console   # Required - Namespace of the pod to which filter need to be applied.
-    label_selector: 'component=ui' # Applies traffic shaping to access openshift console.
-    network_params:
-        latency: 500ms             # Add 500ms latency to egress traffic from the pod.
-```
-##### Sample scenario config for ingress traffic shaping (using plugin)
-```
-- id: pod_ingress_shaping
-  config:
-    namespace: openshift-console   # Required - Namespace of the pod to which filter need to be applied.
-    label_selector: 'component=ui' # Applies traffic shaping to access openshift console.
-    network_params:
-        latency: 500ms             # Add 500ms latency to egress traffic from the pod.
-```
-
-##### Steps
- - Pick the pods to introduce the network anomaly either from label_selector or pod_name.
- - Identify the pod interface name on the node.
- - Set traffic shaping config on pod's interface using tc and netem.
- - Wait for the duration time.
- - Remove traffic shaping config on pod's interface.
- - Remove the job that spawned the pod.

docs/pod_scenarios.md

@@ -1,37 +0,0 @@
-### Pod Scenarios
-
-Krkn recently replaced PowerfulSeal with its own internal pod scenarios using a plugin system. You can run pod scenarios by adding the following config to Krkn:
-
-```yaml
-kraken:
-  chaos_scenarios:
-    - plugin_scenarios:
-      - path/to/scenario.yaml
-```
-
-You can then create the scenario file with the following contents:
-
-```yaml
-# yaml-language-server: $schema=../plugin.schema.json
-- id: kill-pods
-  config:
-    namespace_pattern: ^kube-system$
-    label_selector: k8s-app=kube-scheduler
-    krkn_pod_recovery_time: 120
-    
-```
-
-Please adjust the schema reference to point to the [schema file](../scenarios/plugin.schema.json). This file will give you code completion and documentation for the available options in your IDE.
-
-#### Pod Chaos Scenarios
-
-The following are the components of Kubernetes/OpenShift for which a basic chaos scenario config exists today.
-
-| Component                | Description | Working  |
-| ------------------------ |-------------| -------- |
-| [Basic pod scenario](../scenarios/kube/pod.yml) | Kill a pod. | :heavy_check_mark: |
-| [Etcd](../scenarios/openshift/etcd.yml) | Kills a single/multiple etcd replicas. | :heavy_check_mark: |
-| [Kube ApiServer](../scenarios/openshift/openshift-kube-apiserver.yml)| Kills a single/multiple kube-apiserver replicas. | :heavy_check_mark: |
-| [ApiServer](../scenarios/openshift/openshift-apiserver.yml) | Kills a single/multiple apiserver replicas. | :heavy_check_mark: |
-| [Prometheus](../scenarios/openshift/prometheus.yml) | Kills a single/multiple prometheus replicas. | :heavy_check_mark: |
-| [OpenShift System Pods](../scenarios/openshift/regex_openshift_pod_kill.yml) | Kills random pods running in the OpenShift system namespaces. | :heavy_check_mark: |

docs/pvc_scenario.md

@@ -1,26 +0,0 @@
-### PVC scenario
-Scenario to fill up a given PersistenVolumeClaim by creating a temp file on the PVC from a pod associated with it. The purpose of this scenario is to fill up a volume to understand faults caused by the application using this volume.
-
-##### Sample scenario config
-```
-pvc_scenario:
-  pvc_name: <pvc_name>          # Name of the target PVC.
-  pod_name: <pod_name>          # Name of the pod where the PVC is mounted. It will be ignored if the pvc_name is defined.
-  namespace: <namespace_name>   # Namespace where the PVC is.
-  fill_percentage: 50           # Target percentage to fill up the cluster. Value must be higher than current percentage. Valid values are between 0 and 99.
-  duration: 60                  # Duration in seconds for the fault.
-```
-
-##### Steps
- - Get the pod name where the PVC is mounted.
- - Get the volume name mounted in the container pod.
- - Get the container name where the PVC is mounted.
- - Get the mount path where the PVC is mounted in the pod.
- - Get the PVC capacity and current used capacity.
- - Calculate file size to fill the PVC to the target fill_percentage.
- - Connect to the pod.
- - Create a temp file `kraken.tmp` with random data on the mount path:
-    - `dd bs=1024 count=$file_size </dev/urandom > /mount_path/kraken.tmp`
- - Wait for the duration time.
- - Remove the temp file created:
-    - `rm kraken.tmp`

docs/service_disruption_scenarios.md

@@ -1,63 +0,0 @@
-###  Service Disruption Scenarios (Previously Delete Namespace Scenario)
-
-Using this type of scenario configuration one is able to delete crucial objects in a specific namespace, or a namespace matching a certain regex string.
-
-Configuration Options:
-
-**namespace:** Specific namespace or regex style namespace of what you want to delete. Gets all namespaces if not specified; set to "" if you want to use the label_selector field.
-
-Set to '^.*$' and label_selector to "" to randomly select any namespace in your cluster.
-
-**label_selector:** Label on the namespace you want to delete. Set to "" if you are using the namespace variable.
-
-**delete_count:** Number of namespaces to kill in each run. Based on matching namespace and label specified, default is 1.
-
-**runs:** Number of runs/iterations to kill namespaces, default is 1.
-
-**sleep:** Number of seconds to wait between each iteration/count of killing namespaces. Defaults to 10 seconds if not set
-
-Refer to [namespace_scenarios_example](https://github.com/krkn-chaos/krkn/blob/main/scenarios/regex_namespace.yaml) config file.
-
-```
-scenarios:
-- namespace: "^.*$"
-  runs: 1
-- namespace: "^.*ingress.*$"
-  runs: 1
-  sleep: 15
-```
-
-
-### Steps
-
-This scenario will select a namespace (or multiple) dependent on the configuration and will kill all of the below object types in that namespace and will wait for them to be Running in the post action 
-1. Services 
-2. Daemonsets
-3. Statefulsets
-4. Replicasets
-5. Deployments 
-
-
-#### Post Action
-
-We do a post chaos check to wait and verify the specific objects in each namespace are Ready
-
-Here there are two options:
-
-1. Pass a custom script in the main config scenario list that will run before the chaos and verify the output matches post chaos scenario.
-
-See [scenarios/post_action_namespace.py](https://github.com/cloud-bulldozer/kraken/tree/master/scenarios/post_action_namespace.py) for an example
-
-```
--   namespace_scenarios:
-     - -    scenarios/regex_namespace.yaml
-       -    scenarios/post_action_namespace.py
-```
-
-
-1. Allow kraken to wait and check all killed objects in the namespaces become 'Running' again. Kraken keeps a list of the specific
-objects in namespaces that were killed to verify all that were affected recover properly.
-
-```
-wait_time: <seconds to wait for namespace to recover>
-```

docs/service_hijacking_scenarios.md

@@ -1,80 +0,0 @@
-### Service Hijacking Scenarios
-
-Service Hijacking Scenarios aim to simulate fake HTTP responses from a workload targeted by a 
-`Service` already deployed in the cluster. 
-This scenario is executed by deploying a custom-made web service and modifying the target `Service`
-selector to direct traffic to this web service for a specified duration.
-
-The web service's source code is available [here](https://github.com/krkn-chaos/krkn-service-hijacking). 
-It employs a time-based test plan from the scenario configuration file, which specifies the behavior of resources during the chaos scenario as follows:
-
-```yaml
-service_target_port: http-web-svc # The port of the service to be hijacked (can be named or numeric, based on the workload and service configuration).
-service_name: nginx-service # The name of the service that will be hijacked.
-service_namespace: default # The namespace where the target service is located.
-image: quay.io/krkn-chaos/krkn-service-hijacking:v0.1.3 # Image of the krkn web service to be deployed to receive traffic.
-chaos_duration: 30 # Total duration of the chaos scenario in seconds.
-plan:
-  - resource: "/list/index.php" # Specifies the resource or path to respond to in the scenario. For paths, both the path and query parameters are captured but ignored. For resources, only query parameters are captured.
-
-    steps:                      # A time-based plan consisting of steps can be defined for each resource.
-      GET:                      # One or more HTTP methods can be specified for each step. Note: Non-standard methods are supported for fully custom web services (e.g., using NONEXISTENT instead of POST).
-
-        - duration: 15          # Duration in seconds for this step before moving to the next one, if defined. Otherwise, this step will continue until the chaos scenario ends.
-
-          status: 500           # HTTP status code to be returned in this step.
-          mime_type: "application/json" # MIME type of the response for this step.
-          payload: |            # The response payload for this step.
-            {
-              "status":"internal server error"
-            }
-        - duration: 15
-          status: 201
-          mime_type: "application/json"
-          payload: |
-            {
-              "status":"resource created"
-            }
-      POST:
-        - duration: 15
-          status: 401
-          mime_type: "application/json"
-          payload: |
-            {
-               "status": "unauthorized"
-            }
-        - duration: 15
-          status: 404
-          mime_type: "text/plain"
-          payload: "not found"
-
-
-```
-The scenario will focus on the `service_name` within the `service_namespace`, 
-substituting the selector with a randomly generated one, which is added as a label in the mock service manifest.
-This allows multiple scenarios to be executed in the same namespace, each targeting different services without 
-causing conflicts.
-
-The newly deployed mock web service will expose a `service_target_port`, 
-which can be either a named or numeric port based on the service configuration. 
-This ensures that the Service correctly routes HTTP traffic to the mock web service during the chaos run.
-
-Each step will last for `duration` seconds from the deployment of the mock web service in the cluster. 
-For each HTTP resource, defined as a top-level YAML property of the plan 
-(it could be a specific resource, e.g., /list/index.php, or a path-based resource typical in MVC frameworks), 
-one or more HTTP request methods can be specified. Both standard and custom request methods are supported.
-
-During this time frame, the web service will respond with:
-
-- `status`: The [HTTP status code](https://datatracker.ietf.org/doc/html/rfc7231#section-6) (can be standard or custom).
-- `mime_type`: The [MIME type](https://developer.mozilla.org/en-US/docs/Web/HTTP/Basics_of_HTTP/MIME_types) (can be standard or custom).
-- `payload`: The response body to be returned to the client.
-
-At the end of the step `duration`, the web service will proceed to the next step (if available) until 
-the global `chaos_duration` concludes. At this point, the original service will be restored, 
-and the custom web service and its resources will be undeployed.
-
-__NOTE__: Some clients (e.g., cURL, jQuery) may optimize queries using lightweight methods (like HEAD or OPTIONS) 
-to probe API behavior. If these methods are not defined in the test plan, the web service may respond with 
-a `405` or `404` status code. If you encounter unexpected behavior, consider this use case.
-

docs/signal.md

@@ -1,71 +0,0 @@
-### Signaling to Kraken
-This functionality allows a user to be able to pause or stop the kraken run at any time no matter the number of iterations or daemon_mode set in the config.
-
-If publish_kraken_status is set to True in the config, kraken will start up a connection to a url at a certain port to decide if it should continue running.
-
-By default, it will get posted to http://0.0.0.0:8081/
-
-An example use case for this feature would be coordinating kraken runs based on the status of the service installation or load on the cluster.
-
-
-
-#### States
-There are 3 states in the kraken status:
-
-```PAUSE```: When the Kraken signal is 'PAUSE', this will pause the kraken test and wait for the wait_duration until the signal returns to RUN.
-
-```STOP```: When the Kraken signal is 'STOP', end the kraken run and print out report.
-
-```RUN```: When the Kraken signal is 'RUN', continue kraken run based on iterations.
-
-
-
-#### Configuration
-
-In the config you need to set these parameters to tell kraken which port to post the kraken run status to.
-As well if you want to publish and stop running based on the kraken status or not.
-The signal is set to `RUN` by default, meaning it will continue to run the scenarios. It can set to `PAUSE` for Kraken to act as listener and wait until set to `RUN` before injecting chaos.
-```
-    port: 8081
-    publish_kraken_status: True
-    signal_state: RUN
-```
-
-
-#### Setting Signal
-
-You can reset the kraken status during kraken execution with a `set_stop_signal.py` script with the following contents:
-
-```
-import http.client as cli
-
-conn = cli.HTTPConnection("0.0.0.0", "<port>")
-
-conn.request("POST", "/STOP", {})
-
-# conn.request('POST', '/PAUSE', {})
-
-# conn.request('POST', '/RUN', {})
-
-response = conn.getresponse()
-print(response.read().decode())
-```
-
-Make sure to set the correct port number in your set_stop_signal script.
-
-##### Url Examples
-To stop run:
-
-```
-curl -X POST http:/0.0.0.0:8081/STOP
-```
-
-To pause run:
-```
-curl -X POST http:/0.0.0.0:8081/PAUSE
-```
-
-To start running again:
-```
-curl -X POST http:/0.0.0.0:8081/RUN
-```

docs/syn_flood_scenarios.md

@@ -1,33 +0,0 @@
-### SYN Flood Scenarios
-
-This scenario generates a substantial amount of TCP traffic directed at one or more Kubernetes services within 
-the cluster to test the server's resiliency under extreme traffic conditions. 
-It can also target hosts outside the cluster by specifying a reachable IP address or hostname. 
-This scenario leverages the distributed nature of Kubernetes clusters to instantiate multiple instances 
-of the same pod against a single host, significantly increasing the effectiveness of the attack. 
-The configuration also allows for the specification of multiple node selectors, enabling Kubernetes to schedule 
-the attacker pods on a user-defined subset of nodes to make the test more realistic.
-
- ```yaml
-packet-size: 120 # hping3 packet size
-window-size: 64 # hping 3 TCP window size
-duration: 10 # chaos scenario duration
-namespace: default # namespace where the target service(s) are deployed
-target-service: target-svc # target service name (if set target-service-label must be empty)
-target-port: 80 # target service TCP port
-target-service-label : "" # target service label, can be used to target multiple target at the same time
-                          # if they have the same label set (if set target-service must be empty)
-number-of-pods: 2 # number of attacker pod instantiated per each target
-image: quay.io/krkn-chaos/krkn-syn-flood # syn flood attacker container image
-attacker-nodes: # this will set the node affinity to schedule the attacker node. Per each node label selector
-                # can be specified multiple values in this way the kube scheduler will schedule the attacker pods
-                # in the best way possible based on the provided labels. Multiple labels can be specified
-  kubernetes.io/hostname:
-    - host_1
-    - host_2
-  kubernetes.io/os:
-    - linux
-
- ```
-
-The attacker container source code is available [here](https://github.com/krkn-chaos/krkn-syn-flood).

docs/test_your_changes.md

@@ -1,44 +0,0 @@
-# How to Test Your Changes/Additions
-
-## Current list of Scenario Types
-
-Scenario Types:
-* pod-scenarios
-* node-scenarios
-* zone-outages
-* time-scenarios
-* cluster-shutdown
-* container-scenarios
-* node-cpu-hog
-* node-io-hog
-* node-memory-hog
-* application-outages
-
-## Adding a New Scenario
-1. Create folder under [kraken/kraken](../kraken) with name pertinent to your scenario name.
-
-2. Create a python file that will have a generic run function to be the base of your scenario.
-
-    a. See [shut_down.py](../kraken/shut_down/common_shut_down_func.py) for example.
-
-3. Add in a scenario yaml file to run your specific scenario under [scenarios](../scenarios).
-
-    a. Try to add as many parameters as possible and be sure to give them default values in your run function.
-
-4. Add all functionality and helper functions in file you made above (Step 2).
-
-5. Add in caller to new scenario type in [run_kraken.py](../run_kraken.py) (around line 154).
-
-    a. This will also require you to add the new scenario python script to your imports.
-
-6. Add scenario type and scenario yaml to the scenario list in [config](../config/config.yaml) and [config_performance](../config/config_performance.yaml).
-
-7. Update this doc and main README with new scenario type.
-
-8. Add CI test for new scenario.
-
-    a. Refer to test [Readme](../CI/README.md#adding-a-test-case) for more details.
-
-## Follow Contribute guide
-
-Once all you are happy with your changes, follow the [contribution](#docs/contribute.md) guide on how to create your own branch and squash your commits.

docs/time_scenarios.md

@@ -1,33 +0,0 @@
-###  Time/Date Skew Scenarios
-
-Using this type of scenario configuration, one is able to change the time and/or date of the system for pods or nodes.
-
-Configuration Options:
-
-**action:** skew_time or skew_date.
-
-**object_type:** pod or node.
-
-**namespace:** namespace of the pods you want to skew. Needs to be set if setting a specific pod name.
-
-**label_selector:** Label on the nodes or pods you want to skew.
-
-**container_name:** Container name in pod you want to reset time on. If left blank it will randomly select one.
-
-**object_name:** List of the names of pods or nodes you want to skew.
-
-Refer to [time_scenarios_example](https://github.com/krkn-chaos/krkn/blob/main/scenarios/time_scenarios_example.yml) config file.
-
-```
-time_scenarios:
-  - action: skew_time
-    object_type: pod
-    object_name:
-      - apiserver-868595fcbb-6qnsc
-      - apiserver-868595fcbb-mb9j5
-    namespace: openshift-apiserver
-    container_name: openshift-apiserver
-  - action: skew_date
-    object_type: node
-    label_selector: node-role.kubernetes.io/worker
-```

docs/zone_outage.md

@@ -1,26 +0,0 @@
-### Zone outage scenario
-Scenario to create outage in a targeted zone in the public cloud to understand the impact on both Kubernetes/OpenShift control plane as well as applications running on the worker nodes in that zone. It tweaks the network acl of the zone to simulate the failure and that in turn will stop both ingress and egress traffic from all the nodes in a particular zone for the specified duration and reverts it back to the previous state. Zone outage can be injected by placing the zone_outage config file under zone_outages option in the [kraken config](https://github.com/redhat-chaos/krkn/blob/main/config/config.yaml). Refer to [zone_outage_scenario](https://github.com/redhat-chaos/krkn/blob/main/scenarios/zone_outage.yaml) config file for the parameters that need to be defined.
-
-Refer to [cloud setup](cloud_setup.md) to configure your cli properly for the cloud provider of the cluster you want to shut down.
-
-##### Current accepted cloud types:
-* [AWS](cloud_setup.md#aws)
-
-##### Sample scenario config
-```
-zone_outage:                                         # Scenario to create an outage of a zone by tweaking network ACL.
-  cloud_type: aws                                    # Cloud type on which Kubernetes/OpenShift runs. aws is the only platform supported currently for this scenario.
-  duration: 600                                      # Duration in seconds after which the zone will be back online.
-  vpc_id:                                            # Cluster virtual private network to target.
-  subnet_id: [subnet1, subnet2]                      # List of subnet-id's to deny both ingress and egress traffic.
-```
-
-**NOTE**: vpc_id and subnet_id can be obtained from the cloud web console by selecting one of the instances in the targeted zone ( us-west-2a for example ).
-**NOTE**: Multiple zones will experience downtime in case of targeting multiple subnets which might have an impact on the cluster health especially if the zones have control plane components deployed.
-
-##### Debugging steps in case of failures
-In case of failures during the steps which revert back the network acl to allow traffic and bring back the cluster nodes in the zone, the nodes in the particular zone will be in `NotReady` condition. Here is how to fix it:
-- OpenShift by default deploys the nodes in different zones for fault tolerance, for example us-west-2a, us-west-2b, us-west-2c. The cluster is associated with a virtual private network and each zone has its own subnet with a network acl which defines the ingress and egress traffic rules at the zone level unlike security groups which are at an instance level.
-- From the cloud web console, select one of the instances in the zone which is down and go to the subnet_id specified in the config.
-- Look at the network acl associated with the subnet and you will see both ingress and egress traffic being denied which is expected as Kraken deliberately injects it.
-- Kraken just switches the network acl while still keeping the original or default network acl around, switching to the default network acl from the drop-down menu will get back the nodes in the targeted zone into Ready state.

kraken/application_outage/actions.py

@@ -1,84 +0,0 @@
-import yaml
-import logging
-import time
-import kraken.cerberus.setup as cerberus
-from jinja2 import Template
-import kraken.invoke.command as runcommand
-from krkn_lib.k8s import KrknKubernetes
-from krkn_lib.telemetry.k8s import KrknTelemetryKubernetes
-from krkn_lib.models.telemetry import ScenarioTelemetry
-from krkn_lib.utils.functions import get_yaml_item_value, log_exception
-
-
-# Reads the scenario config, applies and deletes a network policy to
-# block the traffic for the specified duration
-def run(scenarios_list, config, wait_duration,kubecli: KrknKubernetes, telemetry: KrknTelemetryKubernetes) -> (list[str], list[ScenarioTelemetry]):
-    failed_post_scenarios = ""
-    scenario_telemetries: list[ScenarioTelemetry] = []
-    failed_scenarios = []
-    for app_outage_config in scenarios_list:
-        scenario_telemetry = ScenarioTelemetry()
-        scenario_telemetry.scenario = app_outage_config
-        scenario_telemetry.start_timestamp = time.time()
-        telemetry.set_parameters_base64(scenario_telemetry, app_outage_config)
-        if len(app_outage_config) > 1:
-            try:
-                with open(app_outage_config, "r") as f:
-                    app_outage_config_yaml = yaml.full_load(f)
-                    scenario_config = app_outage_config_yaml["application_outage"]
-                    pod_selector = get_yaml_item_value(
-                        scenario_config, "pod_selector", "{}"
-                    )
-                    traffic_type = get_yaml_item_value(
-                        scenario_config, "block", "[Ingress, Egress]"
-                    )
-                    namespace = get_yaml_item_value(
-                        scenario_config, "namespace", ""
-                    )
-                    duration = get_yaml_item_value(
-                        scenario_config, "duration", 60
-                    )
-
-                    start_time = int(time.time())
-
-                    network_policy_template = """---
-apiVersion: networking.k8s.io/v1
-kind: NetworkPolicy
-metadata:
-  name: kraken-deny
-spec:
-  podSelector:
-    matchLabels: {{ pod_selector }}
-  policyTypes: {{ traffic_type }}
-"""
-                    t = Template(network_policy_template)
-                    rendered_spec = t.render(pod_selector=pod_selector, traffic_type=traffic_type)
-                    yaml_spec = yaml.safe_load(rendered_spec)
-                    # Block the traffic by creating network policy
-                    logging.info("Creating the network policy")
-
-                    kubecli.create_net_policy(yaml_spec, namespace)
-                   
-                    # wait for the specified duration
-                    logging.info("Waiting for the specified duration in the config: %s" % (duration))
-                    time.sleep(duration)
-
-                    # unblock the traffic by deleting the network policy
-                    logging.info("Deleting the network policy")
-                    kubecli.delete_net_policy("kraken-deny", namespace)
-
-                    logging.info("End of scenario. Waiting for the specified duration: %s" % (wait_duration))
-                    time.sleep(wait_duration)
-
-                    end_time = int(time.time())
-                    cerberus.publish_kraken_status(config, failed_post_scenarios, start_time, end_time)
-            except Exception as e :
-                scenario_telemetry.exit_status = 1
-                failed_scenarios.append(app_outage_config)
-                log_exception(app_outage_config)
-            else:
-                scenario_telemetry.exit_status = 0
-            scenario_telemetry.end_timestamp = time.time()
-            scenario_telemetries.append(scenario_telemetry)
-    return failed_scenarios, scenario_telemetries
-

kraken/arcaflow_plugin/__init__.py

@@ -1,2 +0,0 @@
-from .arcaflow_plugin import *
-from .context_auth import ContextAuth

kraken/arcaflow_plugin/arcaflow_plugin.py

@@ -1,180 +0,0 @@
-import time
-import arcaflow
-import os
-import yaml
-import logging
-from pathlib import Path
-from typing import List
-from .context_auth import ContextAuth
-from krkn_lib.telemetry.k8s import KrknTelemetryKubernetes
-from krkn_lib.models.telemetry import ScenarioTelemetry
-
-
-def run(scenarios_list: List[str], kubeconfig_path: str, telemetry: KrknTelemetryKubernetes) -> (list[str], list[ScenarioTelemetry]):
-    scenario_telemetries: list[ScenarioTelemetry] = []
-    failed_post_scenarios = []
-    for scenario in scenarios_list:
-        scenario_telemetry = ScenarioTelemetry()
-        scenario_telemetry.scenario = scenario
-        scenario_telemetry.start_timestamp = time.time()
-        telemetry.set_parameters_base64(scenario_telemetry,scenario)
-        engine_args = build_args(scenario)
-        status_code = run_workflow(engine_args, kubeconfig_path)
-        scenario_telemetry.end_timestamp = time.time()
-        scenario_telemetry.exit_status = status_code
-        scenario_telemetries.append(scenario_telemetry)
-        if status_code != 0:
-            failed_post_scenarios.append(scenario)
-    return failed_post_scenarios, scenario_telemetries
-
-
-def run_workflow(engine_args: arcaflow.EngineArgs, kubeconfig_path: str) -> int:
-    set_arca_kubeconfig(engine_args, kubeconfig_path)
-    exit_status = arcaflow.run(engine_args)
-    return exit_status
-
-
-def build_args(input_file: str) -> arcaflow.EngineArgs:
-    """sets the kubeconfig parsed by setArcaKubeConfig as an input to the arcaflow workflow"""
-    current_path = Path().resolve()
-    context = f"{current_path}/{Path(input_file).parent}"
-    workflow = f"{context}/workflow.yaml"
-    config = f"{context}/config.yaml"
-    if not os.path.exists(context):
-        raise Exception(
-            "context folder for arcaflow workflow not found: {}".format(
-                context)
-        )
-    if not os.path.exists(input_file):
-        raise Exception(
-            "input file for arcaflow workflow not found: {}".format(input_file))
-    if not os.path.exists(workflow):
-        raise Exception(
-            "workflow file for arcaflow workflow not found: {}".format(
-                workflow)
-        )
-    if not os.path.exists(config):
-        raise Exception(
-            "configuration file for arcaflow workflow not found: {}".format(
-                config)
-        )
-
-    engine_args = arcaflow.EngineArgs()
-    engine_args.context = context
-    engine_args.config = config
-    engine_args.workflow = workflow
-    engine_args.input = f"{current_path}/{input_file}"
-    return engine_args
-
-
-def set_arca_kubeconfig(engine_args: arcaflow.EngineArgs, kubeconfig_path: str):
-
-    context_auth = ContextAuth()
-    if not os.path.exists(kubeconfig_path):
-        raise Exception("kubeconfig not found in {}".format(kubeconfig_path))
-
-    with open(kubeconfig_path, "r") as stream:
-        try:
-            kubeconfig = yaml.safe_load(stream)
-            context_auth.fetch_auth_data(kubeconfig)
-        except Exception as e:
-            logging.error("impossible to read kubeconfig file in: {}".format(
-                    kubeconfig_path))
-            raise e
-
-    kubeconfig_str = set_kubeconfig_auth(kubeconfig, context_auth)
-
-    with open(engine_args.input, "r") as stream:
-        input_file = yaml.safe_load(stream)
-        if "input_list" in input_file and isinstance(input_file["input_list"],list):
-            for index, _ in enumerate(input_file["input_list"]):
-                if isinstance(input_file["input_list"][index], dict):
-                    input_file["input_list"][index]["kubeconfig"] = kubeconfig_str
-        else:
-            input_file["kubeconfig"] = kubeconfig_str
-        stream.close()
-    with open(engine_args.input, "w") as stream:
-        yaml.safe_dump(input_file, stream)
-
-    with open(engine_args.config, "r") as stream:
-        config_file = yaml.safe_load(stream)
-    if config_file["deployers"]["image"]["deployer_name"] == "kubernetes":
-        kube_connection = set_kubernetes_deployer_auth(config_file["deployers"]["image"]["connection"], context_auth)
-        config_file["deployers"]["image"]["connection"]=kube_connection
-        with open(engine_args.config, "w") as stream:
-            yaml.safe_dump(config_file, stream,explicit_start=True, width=4096)
-
-
-def set_kubernetes_deployer_auth(deployer: any, context_auth: ContextAuth) -> any:
-    if context_auth.clusterHost is not None :
-        deployer["host"] = context_auth.clusterHost
-    if context_auth.clientCertificateData is not None :
-        deployer["cert"] = context_auth.clientCertificateData
-    if context_auth.clientKeyData is not None:
-        deployer["key"] = context_auth.clientKeyData
-    if context_auth.clusterCertificateData is not None:
-        deployer["cacert"] = context_auth.clusterCertificateData
-    if context_auth.username is not None:
-        deployer["username"] = context_auth.username
-    if context_auth.password is not None:
-        deployer["password"] = context_auth.password
-    if context_auth.bearerToken is not None:
-        deployer["bearerToken"] = context_auth.bearerToken
-    return deployer
-
-
-def set_kubeconfig_auth(kubeconfig: any, context_auth: ContextAuth) -> str:
-    """
-    Builds an arcaflow-compatible kubeconfig representation and returns it as a string.
-    In order to run arcaflow plugins in kubernetes/openshift the kubeconfig must contain client certificate/key
-    and server certificate base64 encoded within the kubeconfig file itself in *-data fields. That is not always the
-    case, infact kubeconfig may contain filesystem paths to those files, this function builds an arcaflow-compatible
-    kubeconfig file and returns it as a string that can be safely included in input.yaml 
-    """
-
-    if "current-context" not in kubeconfig.keys():
-        raise Exception(
-            "invalid kubeconfig file, impossible to determine current-context"
-        )
-    user_id = None
-    cluster_id = None
-    user_name = None
-    cluster_name = None
-    current_context = kubeconfig["current-context"]
-    for context in kubeconfig["contexts"]:
-        if context["name"] == current_context:
-            user_name = context["context"]["user"]
-            cluster_name = context["context"]["cluster"]
-    if user_name is None:
-        raise Exception(
-            "user not set for context {} in kubeconfig file".format(current_context)
-        )
-    if cluster_name is None:
-        raise Exception(
-            "cluster not set for context {} in kubeconfig file".format(current_context)
-        )
-
-    for index, user in enumerate(kubeconfig["users"]):
-        if user["name"] == user_name:
-            user_id = index
-    for index, cluster in enumerate(kubeconfig["clusters"]):
-        if cluster["name"] == cluster_name:
-            cluster_id = index
-
-    if cluster_id is None:
-        raise Exception(
-            "no cluster {} found in kubeconfig users".format(cluster_name)
-        )
-    if "client-certificate" in kubeconfig["users"][user_id]["user"]:
-        kubeconfig["users"][user_id]["user"]["client-certificate-data"] = context_auth.clientCertificateDataBase64
-        del kubeconfig["users"][user_id]["user"]["client-certificate"]
-
-    if "client-key" in kubeconfig["users"][user_id]["user"]:
-        kubeconfig["users"][user_id]["user"]["client-key-data"] = context_auth.clientKeyDataBase64
-        del kubeconfig["users"][user_id]["user"]["client-key"]
-
-    if "certificate-authority" in kubeconfig["clusters"][cluster_id]["cluster"]:
-        kubeconfig["clusters"][cluster_id]["cluster"]["certificate-authority-data"] = context_auth.clusterCertificateDataBase64
-        del kubeconfig["clusters"][cluster_id]["cluster"]["certificate-authority"]
-    kubeconfig_str = yaml.dump(kubeconfig)
-    return kubeconfig_str

kraken/arcaflow_plugin/context_auth.py

@@ -1,142 +0,0 @@
-import yaml
-import os
-import base64
-
-
-class ContextAuth:
-    clusterCertificate: str = None
-    clusterCertificateData: str = None
-    clusterHost: str = None
-    clientCertificate: str = None
-    clientCertificateData: str = None
-    clientKey: str = None
-    clientKeyData: str = None
-    clusterName: str = None
-    username: str = None
-    password: str = None
-    bearerToken: str = None
-    # TODO: integrate in krkn-lib-kubernetes in the next iteration
-
-    @property
-    def clusterCertificateDataBase64(self):
-        if self.clusterCertificateData is not None:
-            return base64.b64encode(bytes(self.clusterCertificateData,'utf8')).decode("ascii")
-        return
-
-    @property
-    def clientCertificateDataBase64(self):
-        if self.clientCertificateData is not None:
-            return base64.b64encode(bytes(self.clientCertificateData,'utf8')).decode("ascii")
-        return
-
-    @property
-    def clientKeyDataBase64(self):
-        if self.clientKeyData is not None:
-            return base64.b64encode(bytes(self.clientKeyData,"utf-8")).decode("ascii")
-        return
-
-
-
-    def fetch_auth_data(self, kubeconfig: any):
-        context_username = None
-        current_context = kubeconfig["current-context"]
-        if current_context is None:
-            raise Exception("no current-context found in kubeconfig")
-
-        for context in kubeconfig["contexts"]:
-            if context["name"] == current_context:
-                context_username = context["context"]["user"]
-                self.clusterName = context["context"]["cluster"]
-        if context_username is None:
-            raise Exception("user not found for context {0}".format(current_context))
-        if self.clusterName is None:
-            raise Exception("cluster not found for context {0}".format(current_context))
-        cluster_id = None
-        user_id = None
-        for index, user in enumerate(kubeconfig["users"]):
-            if user["name"] == context_username:
-                user_id = index
-        if user_id is None :
-            raise Exception("user {0} not found in kubeconfig users".format(context_username))
-
-        for index, cluster in enumerate(kubeconfig["clusters"]):
-            if cluster["name"] == self.clusterName:
-                cluster_id = index
-
-        if cluster_id is None:
-            raise Exception(
-                "no cluster {} found in kubeconfig users".format(self.clusterName)
-            )
-
-        user = kubeconfig["users"][user_id]["user"]
-        cluster = kubeconfig["clusters"][cluster_id]["cluster"]
-        # sets cluster api URL
-        self.clusterHost = cluster["server"]
-        # client certificates
-
-        if "client-key" in user:
-            try:
-                self.clientKey = user["client-key"]
-                self.clientKeyData = self.read_file(user["client-key"])
-            except Exception as e:
-                raise e
-
-        if "client-key-data" in user:
-            try:
-                self.clientKeyData = base64.b64decode(user["client-key-data"]).decode('utf-8')
-            except Exception as e:
-                raise Exception("impossible to decode client-key-data")
-
-        if "client-certificate" in user:
-            try:
-                self.clientCertificate = user["client-certificate"]
-                self.clientCertificateData = self.read_file(user["client-certificate"])
-            except Exception as e:
-                raise e
-
-        if "client-certificate-data" in user:
-            try:
-                self.clientCertificateData = base64.b64decode(user["client-certificate-data"]).decode('utf-8')
-            except Exception as e:
-                raise Exception("impossible to decode client-certificate-data")
-
-        # cluster certificate authority
-
-        if "certificate-authority" in cluster:
-            try:
-                self.clusterCertificate = cluster["certificate-authority"]
-                self.clusterCertificateData = self.read_file(cluster["certificate-authority"])
-            except Exception as e:
-                raise e
-
-        if "certificate-authority-data" in cluster:
-            try:
-                self.clusterCertificateData = base64.b64decode(cluster["certificate-authority-data"]).decode('utf-8')
-            except Exception as e:
-                raise Exception("impossible to decode certificate-authority-data")
-
-        if "username" in user:
-            self.username = user["username"]
-
-        if "password" in user:
-            self.password = user["password"]
-
-        if "token" in user:
-            self.bearerToken = user["token"]
-
-    def read_file(self, filename:str) -> str:
-        if not os.path.exists(filename):
-            raise Exception("file not found {0} ".format(filename))
-        with open(filename, "rb") as file_stream:
-            return file_stream.read().decode('utf-8')
-
-
-
-
-
-
-
-
-
-
-

kraken/arcaflow_plugin/fixtures/ca.crt

@@ -1,19 +0,0 @@
------BEGIN CERTIFICATE-----
-MIIDBjCCAe6gAwIBAgIBATANBgkqhkiG9w0BAQsFADAVMRMwEQYDVQQDEwptaW5p
-a3ViZUNBMB4XDTIzMDMxMzE1NDAxM1oXDTMzMDMxMTE1NDAxM1owFTETMBEGA1UE
-AxMKbWluaWt1YmVDQTCCASIwDQYJKoZIhvcNAQEBBQADggEPADCCAQoCggEBAMnz
-U/gIbJBRGOgNYVKX2fV03ANOwnM4VjquR28QMAdxURqgOFZ6IxYNysHEyxxE9I+I
-DAm9hi4vQPbOX7FlxUezuzw+ExEfa6RRJ+n+AGJOV1lezCVph6OaJxB1+L1UqaDZ
-eM3B4cUf/iCc5Y4bs927+CBG3MJL/jmCVPCO+MiSn/l73PXSFNJAYMvRj42zkXqD
-CVG9CwY2vWgZnnzl01l7jNGtie871AmV2uqKakJrQ2ILhD+8fZk4jE5JBDTCZnqQ
-pXIc+vERNKLUS8cvjO6Ux8dMv/Z7+xonpXOU59LlpUdHWP9jgCvMTwiOriwqGjJ+
-pQJWpX9Dm+oxJiVOJzsCAwEAAaNhMF8wDgYDVR0PAQH/BAQDAgKkMB0GA1UdJQQW
-MBQGCCsGAQUFBwMCBggrBgEFBQcDATAPBgNVHRMBAf8EBTADAQH/MB0GA1UdDgQW
-BBQU9pDMtbayJdNM6bp0IG8dcs15qTANBgkqhkiG9w0BAQsFAAOCAQEAtl9TVKPA
-hTnPODqv0AGTqreS9kLg4WUUjZRaPUkPWmtCoTh2Yf55nRWdHOHeZnCWDSg24x42
-lpt+13IdqKew1RKTpKCTkicMFi090A01bYu/w39Cm6nOAA5h8zkgSkV5czvQotuV
-SoN2vB+nbuY28ah5PkdqjMHEZbNwa59cgEke8wB1R1DWFQ/pqflrH2v9ACAuY+5Q
-i673tA6CXrb1YfaCQnVBzcfvjGS1MqShPKpOLMF+/GccPczNimaBxMnKvYLvf3pN
-qEUrJC00mAcein8HmxR2Xz8wredbMUUyrQxW29pZJwfGE5GU0olnlsA0lZLbTwio
-xoolo5y+fsK/dA==
------END CERTIFICATE-----

kraken/arcaflow_plugin/fixtures/client.crt

@@ -1,19 +0,0 @@
------BEGIN CERTIFICATE-----
-MIIDITCCAgmgAwIBAgIBAjANBgkqhkiG9w0BAQsFADAVMRMwEQYDVQQDEwptaW5p
-a3ViZUNBMB4XDTIzMDUwMTA4NTc0N1oXDTI2MDUwMTA4NTc0N1owMTEXMBUGA1UE
-ChMOc3lzdGVtOm1hc3RlcnMxFjAUBgNVBAMTDW1pbmlrdWJlLXVzZXIwggEiMA0G
-CSqGSIb3DQEBAQUAA4IBDwAwggEKAoIBAQC0b7uy9nQYrh7uC5NODve7dFNLAgo5
-pWRS6Kx13ULA55gOpieZiI5/1jwUBjOz0Hhl5QAdHC1HDNu5wf4MmwIEheuq3kMA
-mfuvNxW2BnWSDuXyUMlBfqlwg5o6W8ndEWaK33D7wd2WQsSsAnhQPJSjnzWKvWKq
-+Kbcygc4hdss/ZWN+SXLTahNpHBw0sw8AcJqddNeXs2WI5GdZmbXL4QZI36EaNUm
-m4xKmKRKYIP9wYkmXOV/D2h1meM44y4lul5v2qvo6I+umJ84q4W1/W1vVmAzyVfL
-v1TQCUx8cpKMHzw3ma6CTBCtU3Oq9HKHBnf8GyHZicmV7ESzf/phJu4ZAgMBAAGj
-YDBeMA4GA1UdDwEB/wQEAwIFoDAdBgNVHSUEFjAUBggrBgEFBQcDAQYIKwYBBQUH
-AwIwDAYDVR0TAQH/BAIwADAfBgNVHSMEGDAWgBQU9pDMtbayJdNM6bp0IG8dcs15
-qTANBgkqhkiG9w0BAQsFAAOCAQEABNzEQQMYUcLsBASHladEjr46avKn7gREfaDl
-Y5PBvgCPP42q/sW/9iCNY3UpT9TJZWM6s01+0p6I96jYbRQER1NX7O4OgQYHmFw2
-PF6UOG2vMo54w11OvL7sbr4d+nkE6ItdM9fLDIJ3fEOYJZkSoxhOL/U3jSjIl7Wu
-KCIlpM/M/gcZ4w2IvcLrWtvswbFNUd+dwQfBGcQTmSQDOLE7MqSvzYAkeNv73GLB
-ieba7gs/PmoTFsf9nW60iXymDDF4MtODn15kqT/y1uD6coujmiEiIomBfxqAkUCU
-0ciP/KF5oOEMmMedm7/peQxaRTMdRSk4yu7vbj/BxnTcj039Qg==
------END CERTIFICATE-----

kraken/arcaflow_plugin/fixtures/client.key

@@ -1,27 +0,0 @@
------BEGIN RSA PRIVATE KEY-----
-MIIEowIBAAKCAQEAtG+7svZ0GK4e7guTTg73u3RTSwIKOaVkUuisdd1CwOeYDqYn
-mYiOf9Y8FAYzs9B4ZeUAHRwtRwzbucH+DJsCBIXrqt5DAJn7rzcVtgZ1kg7l8lDJ
-QX6pcIOaOlvJ3RFmit9w+8HdlkLErAJ4UDyUo581ir1iqvim3MoHOIXbLP2Vjfkl
-y02oTaRwcNLMPAHCanXTXl7NliORnWZm1y+EGSN+hGjVJpuMSpikSmCD/cGJJlzl
-fw9odZnjOOMuJbpeb9qr6OiPrpifOKuFtf1tb1ZgM8lXy79U0AlMfHKSjB88N5mu
-gkwQrVNzqvRyhwZ3/Bsh2YnJlexEs3/6YSbuGQIDAQABAoIBAQCdJxPb8zt6o2zc
-98f8nJy378D7+3LccmjGrVBH98ZELXIKkDy9RGqYfQcmiaBOZKv4U1OeBwSIdXKK
-f6O9ZuSC/AEeeSbyRysmmFuYhlewNrmgKyyelqsNDBIv8fIHUTh2i9Xj8B4G2XBi
-QGR5vcnYGLqRdBGTx63Nb0iKuksDCwPAuPA/e0ySz9HdWL1j4bqpVSYsOIXsqTDr
-CVnxUeSIL0fFQnRm3IASXQD7zdq9eEFX7vESeleZoz8qNcKb4Na/C3N6crScjgH7
-qyNZ2zNLfy1LT84k8uc1TMX2KcEVEmfdDv5cCnUH2ic12CwXMZ0vgId5LJTaHx4x
-ytIQIe5hAoGBANB+TsRXP4KzcjZlUUfiAp/pWUM4kVktbsfZa1R2NEuIGJUxPk3P
-7WS0WX5W75QKRg+UWTubg5kfd0f9fklLgofmliBnY/HrpgdyugJmUZBgzIxmy0k+
-aCe0biD1gULfyyrKtfe8k5wRFstzhfGszlOf2ebR87sSVNBuF2lEwPTvAoGBAN2M
-0/XrsodGU4B9Mj86Go2gb2k2WU2izI0cO+tm2S5U5DvKmVEnmjXfPRaOFj2UUQjo
-cljnDAinbN+O0+Inc35qsEeYdAIepNAPglzcpfTHagja9mhx2idLYTXGhbZLL+Ei
-TRzMyP27NF+GVVfYU/cA86ns6NboG6spohmnqh13AoGAKPc4aNGv0/GIVnHP56zb
-0SnbdR7PSFNp+fCZay4Slmi2U9IqKMXbIjdhgjZ4uoDORU9jvReQYuzQ1h9TyfkB
-O8yt4M4P0D/6DmqXa9NI4XJznn6wIMMXWf3UybsTW913IQBVgsjVxAuDjBQ11Eec
-/sdg3D6SgkZWzeFjzjZJJ5cCgYBSYVg7fE3hERxhjawOaJuRCBQFSklAngVzfwkk
-yhR9ruFC/l2uGIy19XFwnprUgP700gIa3qbR3PeV1TUiRcsjOaacqKqSUzSzjODL
-iNxIvZHHAyxWv+b/b38REOWNWD3QeAG2cMtX1bFux7OaO31VPkxcZhRaPOp05cE5
-yudtlwKBgDBbR7RLYn03OPm3NDBLLjTybhD8Iu8Oj7UeNCiEWAdZpqIKYnwSxMzQ
-kdo4aTENA/seEwq+XDV7TwbUIFFJg5gDXIhkcK2c9kiO2bObCAmKpBlQCcrp0a5X
-NSBk1N/ZG/Qhqns7z8k01KN4LNcdpRoNiYYPgY+p3xbY8+nWhv+q
------END RSA PRIVATE KEY-----

kraken/arcaflow_plugin/test_context_auth.py

@@ -1,100 +0,0 @@
-import os
-import unittest
-
-from context_auth import ContextAuth
-
-
-class TestCurrentContext(unittest.TestCase):
-
-    def get_kubeconfig_with_data(self) -> str:
-        """
-        This function returns a test kubeconfig file as a string.
-    
-        :return: a test kubeconfig file in string format (for unit testing purposes)
-        """  # NOQA
-        return """apiVersion: v1
-clusters:
-- cluster:
-    certificate-authority-data: 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
-    server: https://127.0.0.1:6443
-  name: default
-contexts:
-- context:
-    cluster: default
-    namespace: default
-    user: testuser
-  name: default
-current-context: default
-kind: Config
-preferences: {}
-users:
-- name: testuser
-  user:
-    client-certificate-data: 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
-    client-key-data: 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
-    username: testuser
-    password: testpassword
-    token: sha256~fFyEqjf1xxFMO0tbEyGRvWeNOd7QByuEgS4hyEq_A9o
-    """  # NOQA
-
-    def get_kubeconfig_with_paths(self) -> str:
-        """
-        This function returns a test kubeconfig file as a string.
-
-        :return: a test kubeconfig file in string format (for unit testing purposes)
-        """  # NOQA
-        return """apiVersion: v1
-clusters:
-- cluster:
-    certificate-authority: fixtures/ca.crt
-    server: https://127.0.0.1:6443
-  name: default
-contexts:
-- context:
-    cluster: default
-    namespace: default
-    user: testuser
-  name: default
-current-context: default
-kind: Config
-preferences: {}
-users:
-- name: testuser
-  user:
-    client-certificate: fixtures/client.crt
-    client-key: fixtures/client.key
-    username: testuser
-    password: testpassword
-    token: sha256~fFyEqjf1xxFMO0tbEyGRvWeNOd7QByuEgS4hyEq_A9o
-    """  # NOQA
-
-    def test_current_context(self):
-        cwd = os.getcwd()
-        current_context_data = ContextAuth()
-        current_context_data.fetch_auth_data(self.get_kubeconfig_with_data())
-        self.assertIsNotNone(current_context_data.clusterCertificateData)
-        self.assertIsNotNone(current_context_data.clientCertificateData)
-        self.assertIsNotNone(current_context_data.clientKeyData)
-        self.assertIsNotNone(current_context_data.username)
-        self.assertIsNotNone(current_context_data.password)
-        self.assertIsNotNone(current_context_data.bearerToken)
-        self.assertIsNotNone(current_context_data.clusterHost)
-
-        current_context_no_data = ContextAuth()
-        current_context_no_data.fetch_auth_data(self.get_kubeconfig_with_paths())
-        self.assertIsNotNone(current_context_no_data.clusterCertificate)
-        self.assertIsNotNone(current_context_no_data.clusterCertificateData)
-        self.assertIsNotNone(current_context_no_data.clientCertificate)
-        self.assertIsNotNone(current_context_no_data.clientCertificateData)
-        self.assertIsNotNone(current_context_no_data.clientKey)
-        self.assertIsNotNone(current_context_no_data.clientKeyData)
-        self.assertIsNotNone(current_context_no_data.username)
-        self.assertIsNotNone(current_context_no_data.password)
-        self.assertIsNotNone(current_context_no_data.bearerToken)
-        self.assertIsNotNone(current_context_data.clusterHost)
-
-
-
-
-
-

kraken/chaos_recommender/prometheus.py

@@ -1,144 +0,0 @@
-import logging
-
-from prometheus_api_client import PrometheusConnect
-import pandas as pd
-import urllib3
-
-
-saved_metrics_path = "./utilisation.txt"
-
-
-def convert_data_to_dataframe(data, label):
-    df = pd.DataFrame()
-    df['service'] = [item['metric']['pod'] for item in data]
-    df[label] = [item['value'][1] for item in data]
-
-    return df
-
-
-def convert_data(data, service):
-    result = {}
-    for entry in data:
-        pod_name = entry['metric']['pod']
-        value = entry['value'][1]
-        result[pod_name] = value
-    return result.get(service) # for those pods whose limits are not defined they can take as much resources, there assigning a very high value
-
-
-def convert_data_limits(data, node_data, service, prometheus):
-    result = {}
-    for entry in data:
-        pod_name = entry['metric']['pod']
-        value = entry['value'][1]
-        result[pod_name] = value
-    return result.get(service, get_node_capacity(node_data, service, prometheus)) # for those pods whose limits are not defined they can take as much resources, there assigning a very high value
-
-def get_node_capacity(node_data, pod_name, prometheus ):
-
-    # Get the node name on which the pod is running
-    query = f'kube_pod_info{{pod="{pod_name}"}}'
-    result = prometheus.custom_query(query)
-    if not result:
-        return None
-
-    node_name = result[0]['metric']['node']
-
-    for item in node_data:
-        if item['metric']['node'] == node_name:
-            return item['value'][1]
-
-    return '1000000000'
-
-
-def save_utilization_to_file(utilization, filename, prometheus):
-
-    merged_df = pd.DataFrame(columns=['namespace', 'service', 'CPU', 'CPU_LIMITS', 'MEM', 'MEM_LIMITS', 'NETWORK'])
-    for namespace in utilization:
-        # Loading utilization_data[] for namespace
-        # indexes -- 0 CPU, 1 CPU limits, 2 mem, 3 mem limits, 4 network
-        utilization_data = utilization[namespace]
-        df_cpu = convert_data_to_dataframe(utilization_data[0], "CPU")
-        services = df_cpu.service.unique()
-        logging.info(f"Services for namespace {namespace}: {services}")
-
-        for s in services:
-
-            new_row_df = pd.DataFrame({
-                "namespace": namespace, "service": s,
-                "CPU": convert_data(utilization_data[0], s),
-                "CPU_LIMITS": convert_data_limits(utilization_data[1],utilization_data[5], s, prometheus),
-                "MEM": convert_data(utilization_data[2], s),
-                "MEM_LIMITS": convert_data_limits(utilization_data[3], utilization_data[6], s, prometheus),
-                "NETWORK": convert_data(utilization_data[4], s)}, index=[0])
-            merged_df = pd.concat([merged_df, new_row_df], ignore_index=True)
-
-    # Convert columns to string
-    merged_df['CPU'] = merged_df['CPU'].astype(str)
-    merged_df['MEM'] = merged_df['MEM'].astype(str)
-    merged_df['CPU_LIMITS'] = merged_df['CPU_LIMITS'].astype(str)
-    merged_df['MEM_LIMITS'] = merged_df['MEM_LIMITS'].astype(str)
-    merged_df['NETWORK'] = merged_df['NETWORK'].astype(str)
-
-    # Extract integer part before the decimal point
-    #merged_df['CPU'] = merged_df['CPU'].str.split('.').str[0]
-    #merged_df['MEM'] = merged_df['MEM'].str.split('.').str[0]
-    #merged_df['CPU_LIMITS'] = merged_df['CPU_LIMITS'].str.split('.').str[0]
-    #merged_df['MEM_LIMITS'] = merged_df['MEM_LIMITS'].str.split('.').str[0]
-    #merged_df['NETWORK'] = merged_df['NETWORK'].str.split('.').str[0]
-
-    merged_df.to_csv(filename, sep='\t', index=False)
-
-
-def fetch_utilization_from_prometheus(prometheus_endpoint, auth_token,
-                                      namespaces, scrape_duration):
-    urllib3.disable_warnings()
-    prometheus = PrometheusConnect(url=prometheus_endpoint, headers={
-        'Authorization':'Bearer {}'.format(auth_token)}, disable_ssl=True)
-
-    # Dicts for saving utilisation and queries -- key is namespace
-    utilization = {}
-    queries = {}
-
-    logging.info("Fetching utilization...")
-    for namespace in namespaces:
-
-        # Fetch CPU utilization
-        cpu_query = 'sum (rate (container_cpu_usage_seconds_total{image!="", namespace="%s"}[%s])) by (pod) *1000' % (namespace,scrape_duration)
-        cpu_result = prometheus.custom_query(cpu_query)
-
-        cpu_limits_query = '(sum by (pod) (kube_pod_container_resource_limits{resource="cpu", namespace="%s"}))*1000' %(namespace)
-        cpu_limits_result = prometheus.custom_query(cpu_limits_query)
-
-        node_cpu_limits_query = 'kube_node_status_capacity{resource="cpu", unit="core"}*1000'
-        node_cpu_limits_result = prometheus.custom_query(node_cpu_limits_query)
-
-        mem_query = 'sum by (pod) (avg_over_time(container_memory_usage_bytes{image!="", namespace="%s"}[%s]))' % (namespace, scrape_duration)
-        mem_result = prometheus.custom_query(mem_query)
-
-        mem_limits_query = 'sum by (pod) (kube_pod_container_resource_limits{resource="memory", namespace="%s"})  ' %(namespace)
-        mem_limits_result = prometheus.custom_query(mem_limits_query)
-
-        node_mem_limits_query = 'kube_node_status_capacity{resource="memory", unit="byte"}'
-        node_mem_limits_result = prometheus.custom_query(node_mem_limits_query)
-
-        network_query = 'sum by (pod) ((avg_over_time(container_network_transmit_bytes_total{namespace="%s"}[%s])) + \
-        (avg_over_time(container_network_receive_bytes_total{namespace="%s"}[%s])))' % (namespace, scrape_duration, namespace, scrape_duration)
-        network_result = prometheus.custom_query(network_query)
-
-        utilization[namespace] = [cpu_result, cpu_limits_result, mem_result, mem_limits_result, network_result, node_cpu_limits_result, node_mem_limits_result ]
-        queries[namespace] = json_queries(cpu_query, cpu_limits_query, mem_query, mem_limits_query, network_query)
-
-    save_utilization_to_file(utilization, saved_metrics_path, prometheus)
-
-    return saved_metrics_path, queries
-
-
-def json_queries(cpu_query, cpu_limits_query, mem_query, mem_limits_query, network_query):
-    queries = {
-        "cpu_query": cpu_query,
-        "cpu_limit_query": cpu_limits_query,
-        "memory_query": mem_query,
-        "memory_limit_query": mem_limits_query,
-        "network_query": network_query
-    }
-    return queries

kraken/managedcluster_scenarios/manifestwork.j2

@@ -1,68 +0,0 @@
-apiVersion: work.open-cluster-management.io/v1
-kind: ManifestWork
-metadata:
-  namespace: {{managedcluster_name}}
-  name: managedcluster-scenarios-template
-spec:
-  workload:
-    manifests:
-      - apiVersion: rbac.authorization.k8s.io/v1
-        kind: ClusterRole
-        metadata:
-          name: scale-deploy
-          namespace: open-cluster-management 
-        rules:
-        - apiGroups: ["apps"]
-          resources: ["deployments/scale"]
-          verbs: ["patch"]
-        - apiGroups: ["apps"]
-          resources: ["deployments"]
-          verbs: ["get"]
-      - apiVersion: rbac.authorization.k8s.io/v1
-        kind: RoleBinding
-        metadata:
-          name: scale-deploy-to-sa
-          namespace: open-cluster-management
-        subjects:
-          - kind: ServiceAccount
-            name: internal-kubectl
-            namespace: open-cluster-management
-        roleRef:
-          kind: ClusterRole
-          name: scale-deploy
-          apiGroup: rbac.authorization.k8s.io
-      - apiVersion: rbac.authorization.k8s.io/v1
-        kind: RoleBinding
-        metadata:
-          name: scale-deploy-to-sa
-          namespace: open-cluster-management-agent
-        subjects:
-          - kind: ServiceAccount
-            name: internal-kubectl
-            namespace: open-cluster-management
-        roleRef:
-          kind: ClusterRole
-          name: scale-deploy
-          apiGroup: rbac.authorization.k8s.io
-      - apiVersion: v1
-        kind: ServiceAccount
-        metadata:
-          name: internal-kubectl
-          namespace: open-cluster-management 
-      - apiVersion: batch/v1
-        kind: Job
-        metadata:
-          name: managedcluster-scenarios-template
-          namespace: open-cluster-management
-        spec:
-          template:
-            spec:
-              serviceAccountName: internal-kubectl
-              containers:
-              - name: kubectl
-                image: quay.io/sighup/kubectl-kustomize:1.21.6_3.9.1
-                command: ["/bin/sh", "-c"]
-                args:
-                  - {{args}}
-              restartPolicy: Never
-          backoffLimit: 0

kraken/managedcluster_scenarios/run.py

@@ -1,78 +0,0 @@
-import yaml
-import logging
-import time
-from kraken.managedcluster_scenarios.managedcluster_scenarios import managedcluster_scenarios
-import kraken.managedcluster_scenarios.common_managedcluster_functions as common_managedcluster_functions
-import kraken.cerberus.setup as cerberus
-from krkn_lib.k8s import KrknKubernetes
-from krkn_lib.utils.functions import get_yaml_item_value
-
-# Get the managedcluster scenarios object of specfied cloud type
-# krkn_lib
-def get_managedcluster_scenario_object(managedcluster_scenario, kubecli: KrknKubernetes):
-    return managedcluster_scenarios(kubecli)
-
-# Run defined scenarios
-# krkn_lib
-def run(scenarios_list, config, wait_duration, kubecli: KrknKubernetes):
-    for managedcluster_scenario_config in scenarios_list:
-        with open(managedcluster_scenario_config, "r") as f:
-            managedcluster_scenario_config = yaml.full_load(f)
-            for managedcluster_scenario in managedcluster_scenario_config["managedcluster_scenarios"]:
-                managedcluster_scenario_object = get_managedcluster_scenario_object(managedcluster_scenario, kubecli)
-                if managedcluster_scenario["actions"]:
-                    for action in managedcluster_scenario["actions"]:
-                        start_time = int(time.time())
-                        inject_managedcluster_scenario(action, managedcluster_scenario, managedcluster_scenario_object, kubecli)
-                        logging.info("Waiting for the specified duration: %s" % (wait_duration))
-                        time.sleep(wait_duration)
-                        end_time = int(time.time())
-                        cerberus.get_status(config, start_time, end_time)
-                        logging.info("")
-
-
-# Inject the specified managedcluster scenario
-# krkn_lib
-def inject_managedcluster_scenario(action, managedcluster_scenario, managedcluster_scenario_object, kubecli: KrknKubernetes):
-    # Get the managedcluster scenario configurations
-    run_kill_count = get_yaml_item_value(
-        managedcluster_scenario, "runs", 1
-    )
-    instance_kill_count = get_yaml_item_value(
-        managedcluster_scenario, "instance_count", 1
-    )
-    managedcluster_name = get_yaml_item_value(
-        managedcluster_scenario, "managedcluster_name", ""
-    )
-    label_selector = get_yaml_item_value(
-        managedcluster_scenario, "label_selector", ""
-    )
-    timeout = get_yaml_item_value(managedcluster_scenario, "timeout", 120)
-    # Get the managedcluster to apply the scenario
-    if managedcluster_name:
-        managedcluster_name_list = managedcluster_name.split(",")
-    else:
-        managedcluster_name_list = [managedcluster_name]
-    for single_managedcluster_name in managedcluster_name_list:
-        managedclusters = common_managedcluster_functions.get_managedcluster(single_managedcluster_name, label_selector, instance_kill_count, kubecli)
-        for single_managedcluster in managedclusters:
-            if action == "managedcluster_start_scenario":
-                managedcluster_scenario_object.managedcluster_start_scenario(run_kill_count, single_managedcluster, timeout)
-            elif action == "managedcluster_stop_scenario":
-                managedcluster_scenario_object.managedcluster_stop_scenario(run_kill_count, single_managedcluster, timeout)
-            elif action == "managedcluster_stop_start_scenario":
-                managedcluster_scenario_object.managedcluster_stop_start_scenario(run_kill_count, single_managedcluster, timeout)
-            elif action == "managedcluster_termination_scenario":
-                managedcluster_scenario_object.managedcluster_termination_scenario(run_kill_count, single_managedcluster, timeout)
-            elif action == "managedcluster_reboot_scenario":
-                managedcluster_scenario_object.managedcluster_reboot_scenario(run_kill_count, single_managedcluster, timeout)
-            elif action == "stop_start_klusterlet_scenario":
-                managedcluster_scenario_object.stop_start_klusterlet_scenario(run_kill_count, single_managedcluster, timeout)
-            elif action == "start_klusterlet_scenario":
-                managedcluster_scenario_object.stop_klusterlet_scenario(run_kill_count, single_managedcluster, timeout)    
-            elif action == "stop_klusterlet_scenario":
-                managedcluster_scenario_object.stop_klusterlet_scenario(run_kill_count, single_managedcluster, timeout)
-            elif action == "managedcluster_crash_scenario":
-                managedcluster_scenario_object.managedcluster_crash_scenario(run_kill_count, single_managedcluster, timeout)
-            else:
-                logging.info("There is no managedcluster action that matches %s, skipping scenario" % action)

kraken/network_chaos/actions.py

@@ -1,210 +0,0 @@
-import yaml
-import logging
-import time
-import os
-import random
-import kraken.cerberus.setup as cerberus
-import kraken.node_actions.common_node_functions as common_node_functions
-from jinja2 import Environment, FileSystemLoader
-from krkn_lib.k8s import KrknKubernetes
-from krkn_lib.telemetry.k8s import KrknTelemetryKubernetes
-from krkn_lib.models.telemetry import ScenarioTelemetry
-from krkn_lib.utils.functions import get_yaml_item_value, log_exception
-
-
-# krkn_lib
-# Reads the scenario config and introduces traffic variations in Node's host network interface.
-def run(scenarios_list, config, wait_duration, kubecli: KrknKubernetes, telemetry: KrknTelemetryKubernetes) -> (list[str], list[ScenarioTelemetry]):
-    failed_post_scenarios = ""
-    logging.info("Runing the Network Chaos tests")
-    failed_post_scenarios = ""
-    scenario_telemetries: list[ScenarioTelemetry] = []
-    failed_scenarios = []
-    for net_config in scenarios_list:
-        scenario_telemetry = ScenarioTelemetry()
-        scenario_telemetry.scenario = net_config
-        scenario_telemetry.start_timestamp = time.time()
-        telemetry.set_parameters_base64(scenario_telemetry, net_config)
-        try:
-            with open(net_config, "r") as file:
-                param_lst = ["latency", "loss", "bandwidth"]
-                test_config = yaml.safe_load(file)
-                test_dict = test_config["network_chaos"]
-                test_duration = int(
-                    get_yaml_item_value(test_dict, "duration", 300)
-                )
-                test_interface = get_yaml_item_value(
-                    test_dict, "interfaces", []
-                )
-                test_node = get_yaml_item_value(test_dict, "node_name", "")
-                test_node_label = get_yaml_item_value(
-                    test_dict, "label_selector",
-                    "node-role.kubernetes.io/master"
-                )
-                test_execution = get_yaml_item_value(
-                    test_dict, "execution", "serial"
-                )
-                test_instance_count = get_yaml_item_value(
-                    test_dict, "instance_count", 1
-                )
-                test_egress = get_yaml_item_value(
-                    test_dict, "egress", {"bandwidth": "100mbit"}
-                )
-                if test_node:
-                    node_name_list = test_node.split(",")
-                else:
-                    node_name_list = [test_node]
-                nodelst = []
-                for single_node_name in node_name_list:
-                    nodelst.extend(common_node_functions.get_node(single_node_name, test_node_label, test_instance_count, kubecli))
-                file_loader = FileSystemLoader(os.path.abspath(os.path.dirname(__file__)))
-                env = Environment(loader=file_loader, autoescape=True)
-                pod_template = env.get_template("pod.j2")
-                test_interface = verify_interface(test_interface, nodelst, pod_template, kubecli)
-                joblst = []
-                egress_lst = [i for i in param_lst if i in test_egress]
-                chaos_config = {
-                    "network_chaos": {
-                        "duration": test_duration,
-                        "interfaces": test_interface,
-                        "node_name": ",".join(nodelst),
-                        "execution": test_execution,
-                        "instance_count": test_instance_count,
-                        "egress": test_egress,
-                    }
-                }
-                logging.info("Executing network chaos with config \n %s" % yaml.dump(chaos_config))
-                job_template = env.get_template("job.j2")
-                try:
-                    for i in egress_lst:
-                        for node in nodelst:
-                            exec_cmd = get_egress_cmd(
-                                test_execution, test_interface, i, test_dict["egress"], duration=test_duration
-                            )
-                            logging.info("Executing %s on node %s" % (exec_cmd, node))
-                            job_body = yaml.safe_load(
-                                job_template.render(jobname=i + str(hash(node))[:5], nodename=node, cmd=exec_cmd)
-                            )
-                            joblst.append(job_body["metadata"]["name"])
-                            api_response = kubecli.create_job(job_body)
-                            if api_response is None:
-                                raise Exception("Error creating job")
-                        if test_execution == "serial":
-                            logging.info("Waiting for serial job to finish")
-                            start_time = int(time.time())
-                            wait_for_job(joblst[:], kubecli, test_duration + 300)
-                            logging.info("Waiting for wait_duration %s" % wait_duration)
-                            time.sleep(wait_duration)
-                            end_time = int(time.time())
-                            cerberus.publish_kraken_status(config, failed_post_scenarios, start_time, end_time)
-                        if test_execution == "parallel":
-                            break
-                    if test_execution == "parallel":
-                        logging.info("Waiting for parallel job to finish")
-                        start_time = int(time.time())
-                        wait_for_job(joblst[:], kubecli, test_duration + 300)
-                        logging.info("Waiting for wait_duration %s" % wait_duration)
-                        time.sleep(wait_duration)
-                        end_time = int(time.time())
-                        cerberus.publish_kraken_status(config, failed_post_scenarios, start_time, end_time)
-                except Exception as e:
-                    logging.error("Network Chaos exiting due to Exception %s" % e)
-                    raise RuntimeError()
-                finally:
-                    logging.info("Deleting jobs")
-                    delete_job(joblst[:], kubecli)
-        except (RuntimeError, Exception):
-            scenario_telemetry.exit_status = 1
-            failed_scenarios.append(net_config)
-            log_exception(net_config)
-        else:
-            scenario_telemetry.exit_status = 0
-        scenario_telemetries.append(scenario_telemetry)
-    return failed_scenarios, scenario_telemetries
-
-
-# krkn_lib
-def verify_interface(test_interface, nodelst, template, kubecli: KrknKubernetes):
-    pod_index = random.randint(0, len(nodelst) - 1)
-    pod_body = yaml.safe_load(template.render(nodename=nodelst[pod_index]))
-    logging.info("Creating pod to query interface on node %s" % nodelst[pod_index])
-    kubecli.create_pod(pod_body, "default", 300)
-    try:
-        if test_interface == []:
-            cmd = "ip r | grep default | awk '/default/ {print $5}'"
-            output = kubecli.exec_cmd_in_pod(cmd, "fedtools", "default")
-            test_interface = [output.replace("\n", "")]
-        else:
-            cmd = "ip -br addr show|awk -v ORS=',' '{print $1}'"
-            output = kubecli.exec_cmd_in_pod(cmd, "fedtools", "default")
-            interface_lst = output[:-1].split(",")
-            for interface in test_interface:
-                if interface not in interface_lst:
-                    logging.error("Interface %s not found in node %s interface list %s" % (interface, nodelst[pod_index], interface_lst))
-                    #sys.exit(1)
-                    raise RuntimeError()
-        return test_interface
-    finally:
-        logging.info("Deleteing pod to query interface on node")
-        kubecli.delete_pod("fedtools", "default")
-
-
-# krkn_lib
-def get_job_pods(api_response, kubecli: KrknKubernetes):
-    controllerUid = api_response.metadata.labels["controller-uid"]
-    pod_label_selector = "controller-uid=" + controllerUid
-    pods_list = kubecli.list_pods(label_selector=pod_label_selector, namespace="default")
-    return pods_list[0]
-
-
-# krkn_lib
-def wait_for_job(joblst, kubecli: KrknKubernetes, timeout=300):
-    waittime = time.time() + timeout
-    count = 0
-    joblen = len(joblst)
-    while count != joblen:
-        for jobname in joblst:
-            try:
-                api_response = kubecli.get_job_status(jobname, namespace="default")
-                if api_response.status.succeeded is not None or api_response.status.failed is not None:
-                    count += 1
-                    joblst.remove(jobname)
-            except Exception:
-                logging.warning("Exception in getting job status")
-            if time.time() > waittime:
-                raise Exception("Starting pod failed")
-            time.sleep(5)
-
-
-# krkn_lib
-def delete_job(joblst, kubecli: KrknKubernetes):
-    for jobname in joblst:
-        try:
-            api_response = kubecli.get_job_status(jobname, namespace="default")
-            if api_response.status.failed is not None:
-                pod_name = get_job_pods(api_response, kubecli)
-                pod_stat = kubecli.read_pod(name=pod_name, namespace="default")
-                logging.error(pod_stat.status.container_statuses)
-                pod_log_response = kubecli.get_pod_log(name=pod_name, namespace="default")
-                pod_log = pod_log_response.data.decode("utf-8")
-                logging.error(pod_log)
-        except Exception:
-            logging.warning("Exception in getting job status")
-        kubecli.delete_job(name=jobname, namespace="default")
-
-
-def get_egress_cmd(execution, test_interface, mod, vallst, duration=30):
-    tc_set = tc_unset = tc_ls = ""
-    param_map = {"latency": "delay", "loss": "loss", "bandwidth": "rate"}
-    for i in test_interface:
-        tc_set = "{0} tc qdisc add dev {1} root netem".format(tc_set, i)
-        tc_unset = "{0} tc qdisc del dev {1} root ;".format(tc_unset, i)
-        tc_ls = "{0} tc qdisc ls dev {1} ;".format(tc_ls, i)
-        if execution == "parallel":
-            for val in vallst.keys():
-                tc_set += " {0} {1} ".format(param_map[val], vallst[val])
-            tc_set += ";"
-        else:
-            tc_set += " {0} {1} ;".format(param_map[mod], vallst[mod])
-    exec_cmd = "{0} {1} sleep {2};{3} sleep 20;{4}".format(tc_set, tc_ls, duration, tc_unset, tc_ls)
-    return exec_cmd

kraken/node_actions/abstract_node_scenarios.py

@@ -1,85 +0,0 @@
-import sys
-import logging
-import time
-import kraken.invoke.command as runcommand
-import kraken.node_actions.common_node_functions as nodeaction
-from krkn_lib.k8s import KrknKubernetes
-
-# krkn_lib
-class abstract_node_scenarios:
-    kubecli: KrknKubernetes
-    def __init__(self, kubecli: KrknKubernetes):
-        self.kubecli = kubecli
-    # Node scenario to start the node
-    def node_start_scenario(self, instance_kill_count, node, timeout):
-        pass
-
-    # Node scenario to stop the node
-    def node_stop_scenario(self, instance_kill_count, node, timeout):
-        pass
-
-    # Node scenario to stop and then start the node
-    def node_stop_start_scenario(self, instance_kill_count, node, timeout, duration):
-        logging.info("Starting node_stop_start_scenario injection")
-        self.node_stop_scenario(instance_kill_count, node, timeout)
-        logging.info("Waiting for %s seconds before starting the node" % (duration))
-        time.sleep(duration)
-        self.node_start_scenario(instance_kill_count, node, timeout)
-        logging.info("node_stop_start_scenario has been successfully injected!")
-
-    def helper_node_stop_start_scenario(self, instance_kill_count, node, timeout):
-        logging.info("Starting helper_node_stop_start_scenario injection")
-        self.helper_node_stop_scenario(instance_kill_count, node, timeout)
-        self.helper_node_start_scenario(instance_kill_count, node, timeout)
-        logging.info("helper_node_stop_start_scenario has been successfully injected!")
-
-    # Node scenario to terminate the node
-    def node_termination_scenario(self, instance_kill_count, node, timeout):
-        pass
-
-    # Node scenario to reboot the node
-    def node_reboot_scenario(self, instance_kill_count, node, timeout):
-        pass
-
-    # Node scenario to stop the kubelet
-    def stop_kubelet_scenario(self, instance_kill_count, node, timeout):
-        for _ in range(instance_kill_count):
-            try:
-                logging.info("Starting stop_kubelet_scenario injection")
-                logging.info("Stopping the kubelet of the node %s" % (node))
-                runcommand.run("oc debug node/" + node + " -- chroot /host systemctl stop kubelet")
-                nodeaction.wait_for_unknown_status(node, timeout, self.kubecli)
-                logging.info("The kubelet of the node %s has been stopped" % (node))
-                logging.info("stop_kubelet_scenario has been successfuly injected!")
-            except Exception as e:
-                logging.error(
-                    "Failed to stop the kubelet of the node. Encountered following " "exception: %s. Test Failed" % (e)
-                )
-                logging.error("stop_kubelet_scenario injection failed!")
-                sys.exit(1)
-
-    # Node scenario to stop and start the kubelet
-    def stop_start_kubelet_scenario(self, instance_kill_count, node, timeout):
-        logging.info("Starting stop_start_kubelet_scenario injection")
-        self.stop_kubelet_scenario(instance_kill_count, node, timeout)
-        self.node_reboot_scenario(instance_kill_count, node, timeout)
-        logging.info("stop_start_kubelet_scenario has been successfully injected!")
-
-    # Node scenario to crash the node
-    def node_crash_scenario(self, instance_kill_count, node, timeout):
-        for _ in range(instance_kill_count):
-            try:
-                logging.info("Starting node_crash_scenario injection")
-                logging.info("Crashing the node %s" % (node))
-                runcommand.invoke(
-                    "oc debug node/" + node + " -- chroot /host " "dd if=/dev/urandom of=/proc/sysrq-trigger"
-                )
-                logging.info("node_crash_scenario has been successfuly injected!")
-            except Exception as e:
-                logging.error("Failed to crash the node. Encountered following exception: %s. " "Test Failed" % (e))
-                logging.error("node_crash_scenario injection failed!")
-                sys.exit(1)
-
-    # Node scenario to check service status on helper node
-    def node_service_status(self, node, service, ssh_private_key, timeout):
-        pass

kraken/node_actions/aws_node_scenarios.py

@@ -1,258 +0,0 @@
-import sys
-import time
-import boto3
-import logging
-import kraken.node_actions.common_node_functions as nodeaction
-from kraken.node_actions.abstract_node_scenarios import abstract_node_scenarios
-from krkn_lib.k8s import KrknKubernetes
-
-class AWS:
-    def __init__(self):
-        self.boto_client = boto3.client("ec2")
-        self.boto_instance = boto3.resource("ec2").Instance("id")
-
-    # Get the instance ID of the node
-    def get_instance_id(self, node):
-        return self.boto_client.describe_instances(Filters=[{"Name": "private-dns-name", "Values": [node]}])[
-            "Reservations"
-        ][0]["Instances"][0]["InstanceId"]
-
-    # Start the node instance
-    def start_instances(self, instance_id):
-        try:
-            self.boto_client.start_instances(InstanceIds=[instance_id])
-            logging.info("EC2 instance: " + str(instance_id) + " started")
-        except Exception as e:
-            logging.error(
-                "Failed to start node instance %s. Encountered following " "exception: %s." % (instance_id, e)
-            )
-            # removed_exit
-            # sys.exit(1)
-            raise RuntimeError()
-
-    # Stop the node instance
-    def stop_instances(self, instance_id):
-        try:
-            self.boto_client.stop_instances(InstanceIds=[instance_id])
-            logging.info("EC2 instance: " + str(instance_id) + " stopped")
-        except Exception as e:
-            logging.error("Failed to stop node instance %s. Encountered following " "exception: %s." % (instance_id, e))
-            # removed_exit
-            # sys.exit(1)
-            raise RuntimeError()
-
-    # Terminate the node instance
-    def terminate_instances(self, instance_id):
-        try:
-            self.boto_client.terminate_instances(InstanceIds=[instance_id])
-            logging.info("EC2 instance: " + str(instance_id) + " terminated")
-        except Exception as e:
-            logging.error(
-                "Failed to terminate node instance %s. Encountered following " "exception: %s." % (instance_id, e)
-            )
-            # removed_exit
-            # sys.exit(1)
-            raise RuntimeError()
-
-    # Reboot the node instance
-    def reboot_instances(self, instance_id):
-        try:
-            self.boto_client.reboot_instances(InstanceIds=[instance_id])
-            logging.info("EC2 instance " + str(instance_id) + " rebooted")
-        except Exception as e:
-            logging.error(
-                "Failed to reboot node instance %s. Encountered following " "exception: %s." % (instance_id, e)
-            )
-            # removed_exit
-            # sys.exit(1)
-            raise RuntimeError()
-
-    # Below functions poll EC2.Client.describe_instances() every 15 seconds
-    # until a successful state is reached. An error is returned after 40 failed checks
-    # Setting timeout for consistency with other cloud functions
-    # Wait until the node instance is running
-    def wait_until_running(self, instance_id, timeout=600):
-        try:
-            self.boto_instance.wait_until_running(InstanceIds=[instance_id])
-            return True
-        except Exception as e:
-            logging.error("Failed to get status waiting for %s to be running %s" % (instance_id, e))
-            return False
-
-    # Wait until the node instance is stopped
-    def wait_until_stopped(self, instance_id, timeout=600):
-        try:
-            self.boto_instance.wait_until_stopped(InstanceIds=[instance_id])
-            return True
-        except Exception as e:
-            logging.error("Failed to get status waiting for %s to be stopped %s" % (instance_id, e))
-            return False
-
-    # Wait until the node instance is terminated
-    def wait_until_terminated(self, instance_id, timeout=600):
-        try:
-            self.boto_instance.wait_until_terminated(InstanceIds=[instance_id])
-            return True
-        except Exception as e:
-            logging.error("Failed to get status waiting for %s to be terminated %s" % (instance_id, e))
-            return False
-
-    # Creates a deny network acl and returns the id
-    def create_default_network_acl(self, vpc_id):
-        try:
-            logging.info("Trying to create a default deny network acl")
-            response = self.boto_client.create_network_acl(VpcId=vpc_id)
-            acl_id = response["NetworkAcl"]["NetworkAclId"]
-            logging.info("Created a network acl, id=%s" % acl_id)
-        except Exception as e:
-            logging.error(
-                "Failed to create the default network_acl: %s"
-                "Make sure you have aws cli configured on the host and set for the region of your vpc/subnet" % (e)
-            )
-            # removed_exit
-            # sys.exit(1)
-            raise RuntimeError()
-        return acl_id
-
-    # Replace network acl association
-    def replace_network_acl_association(self, association_id, acl_id):
-        try:
-            logging.info("Replacing the network acl associated with the subnet")
-            status = self.boto_client.replace_network_acl_association(AssociationId=association_id, NetworkAclId=acl_id)
-            logging.info(status)
-            new_association_id = status["NewAssociationId"]
-        except Exception as e:
-            logging.error("Failed to replace network acl association: %s" % (e))
-            # removed_exit
-            # sys.exit(1)
-            raise RuntimeError()
-        return new_association_id
-
-    # Describe network acl
-    def describe_network_acls(self, vpc_id, subnet_id):
-        try:
-            response = self.boto_client.describe_network_acls(
-                Filters=[
-                    {"Name": "vpc-id", "Values": [vpc_id]},
-                    {"Name": "association.subnet-id", "Values": [subnet_id]},
-                ]
-            )
-        except Exception as e:
-            logging.error(
-                "Failed to describe network acl: %s."
-                "Make sure you have aws cli configured on the host and set for the region of your vpc/subnet" % (e)
-            )
-            # removed_exit
-            # sys.exit(1)
-            raise RuntimeError()
-        associations = response["NetworkAcls"][0]["Associations"]
-        # grab the current network_acl in use
-        original_acl_id = response["NetworkAcls"][0]["Associations"][0]["NetworkAclId"]
-        return associations, original_acl_id
-
-    # Delete network acl
-    def delete_network_acl(self, acl_id):
-        try:
-            logging.info("Deleting the network acl: %s" % (acl_id))
-            self.boto_client.delete_network_acl(NetworkAclId=acl_id)
-        except Exception as e:
-            logging.error(
-                "Failed to delete network_acl %s: %s"
-                "Make sure you have aws cli configured on the host and set for the region of your vpc/subnet"
-                % (acl_id, e)
-            )
-            # removed_exit
-            # sys.exit(1)
-            raise RuntimeError()
-
-# krkn_lib
-class aws_node_scenarios(abstract_node_scenarios):
-    def __init__(self, kubecli: KrknKubernetes):
-        super().__init__(kubecli)
-        self.aws = AWS()
-
-    # Node scenario to start the node
-    def node_start_scenario(self, instance_kill_count, node, timeout):
-        for _ in range(instance_kill_count):
-            try:
-                logging.info("Starting node_start_scenario injection")
-                instance_id = self.aws.get_instance_id(node)
-                logging.info("Starting the node %s with instance ID: %s " % (node, instance_id))
-                self.aws.start_instances(instance_id)
-                self.aws.wait_until_running(instance_id)
-                nodeaction.wait_for_ready_status(node, timeout, self.kubecli)
-                logging.info("Node with instance ID: %s is in running state" % (instance_id))
-                logging.info("node_start_scenario has been successfully injected!")
-            except Exception as e:
-                logging.error(
-                    "Failed to start node instance. Encountered following " "exception: %s. Test Failed" % (e)
-                )
-                logging.error("node_start_scenario injection failed!")
-                # removed_exit
-                # sys.exit(1)
-                raise RuntimeError()
-
-    # Node scenario to stop the node
-    def node_stop_scenario(self, instance_kill_count, node, timeout):
-        for _ in range(instance_kill_count):
-            try:
-                logging.info("Starting node_stop_scenario injection")
-                instance_id = self.aws.get_instance_id(node)
-                logging.info("Stopping the node %s with instance ID: %s " % (node, instance_id))
-                self.aws.stop_instances(instance_id)
-                self.aws.wait_until_stopped(instance_id)
-                logging.info("Node with instance ID: %s is in stopped state" % (instance_id))
-                nodeaction.wait_for_unknown_status(node, timeout, self.kubecli)
-            except Exception as e:
-                logging.error("Failed to stop node instance. Encountered following exception: %s. " "Test Failed" % (e))
-                logging.error("node_stop_scenario injection failed!")
-                # removed_exit
-                # sys.exit(1)
-                raise RuntimeError()
-
-    # Node scenario to terminate the node
-    def node_termination_scenario(self, instance_kill_count, node, timeout):
-        for _ in range(instance_kill_count):
-            try:
-                logging.info("Starting node_termination_scenario injection")
-                instance_id = self.aws.get_instance_id(node)
-                logging.info("Terminating the node %s with instance ID: %s " % (node, instance_id))
-                self.aws.terminate_instances(instance_id)
-                self.aws.wait_until_terminated(instance_id)
-                for _ in range(timeout):
-                    if node not in self.kubecli.list_nodes():
-                        break
-                    time.sleep(1)
-                if node in self.kubecli.list_nodes():
-                    raise Exception("Node could not be terminated")
-                logging.info("Node with instance ID: %s has been terminated" % (instance_id))
-                logging.info("node_termination_scenario has been successfuly injected!")
-            except Exception as e:
-                logging.error(
-                    "Failed to terminate node instance. Encountered following exception:" " %s. Test Failed" % (e)
-                )
-                logging.error("node_termination_scenario injection failed!")
-                # removed_exit
-                # sys.exit(1)
-                raise RuntimeError()
-
-    # Node scenario to reboot the node
-    def node_reboot_scenario(self, instance_kill_count, node, timeout):
-        for _ in range(instance_kill_count):
-            try:
-                logging.info("Starting node_reboot_scenario injection" + str(node))
-                instance_id = self.aws.get_instance_id(node)
-                logging.info("Rebooting the node %s with instance ID: %s " % (node, instance_id))
-                self.aws.reboot_instances(instance_id)
-                nodeaction.wait_for_unknown_status(node, timeout, self.kubecli)
-                nodeaction.wait_for_ready_status(node, timeout, self.kubecli)
-                logging.info("Node with instance ID: %s has been rebooted" % (instance_id))
-                logging.info("node_reboot_scenario has been successfuly injected!")
-            except Exception as e:
-                logging.error(
-                    "Failed to reboot node instance. Encountered following exception:" " %s. Test Failed" % (e)
-                )
-                logging.error("node_reboot_scenario injection failed!")
-                # removed_exit
-                # sys.exit(1)
-                raise RuntimeError()

kraken/node_actions/az_node_scenarios.py

@@ -1,224 +0,0 @@
-
-import time
-import os
-import kraken.invoke.command as runcommand
-import logging
-import kraken.node_actions.common_node_functions as nodeaction
-from kraken.node_actions.abstract_node_scenarios import abstract_node_scenarios
-from azure.mgmt.compute import ComputeManagementClient
-from azure.identity import DefaultAzureCredential
-from krkn_lib.k8s import KrknKubernetes
-
-
-
-class Azure:
-    def __init__(self):
-        logging.info("azure " + str(self))
-        # Acquire a credential object using CLI-based authentication.
-        credentials = DefaultAzureCredential()
-        logging.info("credential " + str(credentials))
-        # az_account = runcommand.invoke("az account list -o yaml")
-        # az_account_yaml = yaml.safe_load(az_account, Loader=yaml.FullLoader)
-        subscription_id = os.getenv("AZURE_SUBSCRIPTION_ID")
-        self.compute_client = ComputeManagementClient(credentials, subscription_id)
-
-    # Get the instance ID of the node
-    def get_instance_id(self, node_name):
-        vm_list = self.compute_client.virtual_machines.list_all()
-        for vm in vm_list:
-            array = vm.id.split("/")
-            resource_group = array[4]
-            vm_name = array[-1]
-            if node_name == vm_name:
-                return vm_name, resource_group
-        logging.error("Couldn't find vm with name " + str(node_name))
-
-    # Start the node instance
-    def start_instances(self, group_name, vm_name):
-        try:
-            self.compute_client.virtual_machines.begin_start(group_name, vm_name)
-            logging.info("vm name " + str(vm_name) + " started")
-        except Exception as e:
-            logging.error("Failed to start node instance %s. Encountered following " "exception: %s." % (vm_name, e))
-            # removed_exit
-            # sys.exit(1)
-            raise RuntimeError()
-
-    # Stop the node instance
-    def stop_instances(self, group_name, vm_name):
-        try:
-            self.compute_client.virtual_machines.begin_power_off(group_name, vm_name)
-            logging.info("vm name " + str(vm_name) + " stopped")
-        except Exception as e:
-            logging.error("Failed to stop node instance %s. Encountered following " "exception: %s." % (vm_name, e))
-            # removed_exit
-            # sys.exit(1)
-            raise RuntimeError()
-
-    # Terminate the node instance
-    def terminate_instances(self, group_name, vm_name):
-        try:
-            self.compute_client.virtual_machines.begin_delete(group_name, vm_name)
-            logging.info("vm name " + str(vm_name) + " terminated")
-        except Exception as e:
-            logging.error(
-                "Failed to terminate node instance %s. Encountered following " "exception: %s." % (vm_name, e)
-            )
-            # removed_exit
-            # sys.exit(1)
-            raise RuntimeError()
-
-    # Reboot the node instance
-    def reboot_instances(self, group_name, vm_name):
-        try:
-            self.compute_client.virtual_machines.begin_restart(group_name, vm_name)
-            logging.info("vm name " + str(vm_name) + " rebooted")
-        except Exception as e:
-            logging.error("Failed to reboot node instance %s. Encountered following " "exception: %s." % (vm_name, e))
-            # removed_exit
-            # sys.exit(1)
-            raise RuntimeError()
-
-    def get_vm_status(self, resource_group, vm_name):
-        statuses = self.compute_client.virtual_machines.instance_view(resource_group, vm_name).statuses
-        status = len(statuses) >= 2 and statuses[1]
-        return status
-
-    # Wait until the node instance is running
-    def wait_until_running(self, resource_group, vm_name, timeout):
-        time_counter = 0
-        status = self.get_vm_status(resource_group, vm_name)
-        while status and status.code != "PowerState/running":
-            status = self.get_vm_status(resource_group, vm_name)
-            logging.info("Vm %s is still not running, sleeping for 5 seconds" % vm_name)
-            time.sleep(5)
-            time_counter += 5
-            if time_counter >= timeout:
-                logging.info("Vm %s is still not ready in allotted time" % vm_name)
-                return False
-        return True
-
-    # Wait until the node instance is stopped
-    def wait_until_stopped(self, resource_group, vm_name, timeout):
-        time_counter = 0
-        status = self.get_vm_status(resource_group, vm_name)
-        while status and status.code != "PowerState/stopped":
-            status = self.get_vm_status(resource_group, vm_name)
-            logging.info("Vm %s is still stopping, sleeping for 5 seconds" % vm_name)
-            time.sleep(5)
-            time_counter += 5
-            if time_counter >= timeout:
-                logging.info("Vm %s is still not stopped in allotted time" % vm_name)
-                return False
-        return True
-
-    # Wait until the node instance is terminated
-    def wait_until_terminated(self, resource_group, vm_name, timeout):
-        statuses = self.compute_client.virtual_machines.instance_view(resource_group, vm_name).statuses[0]
-        logging.info("vm status " + str(statuses))
-        time_counter = 0
-        while statuses.code == "ProvisioningState/deleting":
-            try:
-                statuses = self.compute_client.virtual_machines.instance_view(resource_group, vm_name).statuses[0]
-                logging.info("Vm %s is still deleting, waiting 10 seconds" % vm_name)
-                time.sleep(10)
-                time_counter += 10
-                if time_counter >= timeout:
-                    logging.info("Vm %s was not terminated in allotted time" % vm_name)
-                    return False
-            except Exception:
-                logging.info("Vm %s is terminated" % vm_name)
-                return True
-
-# krkn_lib
-class azure_node_scenarios(abstract_node_scenarios):
-    def __init__(self, kubecli: KrknKubernetes):
-        super().__init__(kubecli)
-        logging.info("init in azure")
-        self.azure = Azure()
-
-    # Node scenario to start the node
-    def node_start_scenario(self, instance_kill_count, node, timeout):
-        for _ in range(instance_kill_count):
-            try:
-                logging.info("Starting node_start_scenario injection")
-                vm_name, resource_group = self.azure.get_instance_id(node)
-                logging.info("Starting the node %s with instance ID: %s " % (vm_name, resource_group))
-                self.azure.start_instances(resource_group, vm_name)
-                self.azure.wait_until_running(resource_group, vm_name, timeout)
-                nodeaction.wait_for_ready_status(vm_name, timeout,self.kubecli)
-                logging.info("Node with instance ID: %s is in running state" % node)
-                logging.info("node_start_scenario has been successfully injected!")
-            except Exception as e:
-                logging.error(
-                    "Failed to start node instance. Encountered following " "exception: %s. Test Failed" % (e)
-                )
-                logging.error("node_start_scenario injection failed!")
-                # removed_exit
-                # sys.exit(1)
-                raise RuntimeError()
-
-    # Node scenario to stop the node
-    def node_stop_scenario(self, instance_kill_count, node, timeout):
-        for _ in range(instance_kill_count):
-            try:
-                logging.info("Starting node_stop_scenario injection")
-                vm_name, resource_group = self.azure.get_instance_id(node)
-                logging.info("Stopping the node %s with instance ID: %s " % (vm_name, resource_group))
-                self.azure.stop_instances(resource_group, vm_name)
-                self.azure.wait_until_stopped(resource_group, vm_name, timeout)
-                logging.info("Node with instance ID: %s is in stopped state" % vm_name)
-                nodeaction.wait_for_unknown_status(vm_name, timeout, self.kubecli)
-            except Exception as e:
-                logging.error("Failed to stop node instance. Encountered following exception: %s. " "Test Failed" % e)
-                logging.error("node_stop_scenario injection failed!")
-                # removed_exit
-                # sys.exit(1)
-                raise RuntimeError()
-
-    # Node scenario to terminate the node
-    def node_termination_scenario(self, instance_kill_count, node, timeout):
-        for _ in range(instance_kill_count):
-            try:
-                logging.info("Starting node_termination_scenario injection")
-                vm_name, resource_group = self.azure.get_instance_id(node)
-                logging.info("Terminating the node %s with instance ID: %s " % (vm_name, resource_group))
-                self.azure.terminate_instances(resource_group, vm_name)
-                self.azure.wait_until_terminated(resource_group, vm_name, timeout)
-                for _ in range(timeout):
-                    if vm_name not in self.kubecli.list_nodes():
-                        break
-                    time.sleep(1)
-                if vm_name in self.kubecli.list_nodes():
-                    raise Exception("Node could not be terminated")
-                logging.info("Node with instance ID: %s has been terminated" % node)
-                logging.info("node_termination_scenario has been successfully injected!")
-            except Exception as e:
-                logging.error(
-                    "Failed to terminate node instance. Encountered following exception:" " %s. Test Failed" % (e)
-                )
-                logging.error("node_termination_scenario injection failed!")
-                # removed_exit
-                # sys.exit(1)
-                raise RuntimeError()
-
-    # Node scenario to reboot the node
-    def node_reboot_scenario(self, instance_kill_count, node, timeout):
-        for _ in range(instance_kill_count):
-            try:
-                logging.info("Starting node_reboot_scenario injection")
-                vm_name, resource_group = self.azure.get_instance_id(node)
-                logging.info("Rebooting the node %s with instance ID: %s " % (vm_name, resource_group))
-                self.azure.reboot_instances(resource_group, vm_name)
-                nodeaction.wait_for_unknown_status(vm_name, timeout, self.kubecli)
-                nodeaction.wait_for_ready_status(vm_name, timeout, self.kubecli)
-                logging.info("Node with instance ID: %s has been rebooted" % (vm_name))
-                logging.info("node_reboot_scenario has been successfully injected!")
-            except Exception as e:
-                logging.error(
-                    "Failed to reboot node instance. Encountered following exception:" " %s. Test Failed" % (e)
-                )
-                logging.error("node_reboot_scenario injection failed!")
-                # removed_exit
-                # sys.exit(1)
-                raise RuntimeError()

kraken/node_actions/gcp_node_scenarios.py

@@ -1,245 +0,0 @@
-import os
-import sys
-import time
-import logging
-import json
-import kraken.node_actions.common_node_functions as nodeaction
-from kraken.node_actions.abstract_node_scenarios import abstract_node_scenarios
-from googleapiclient import discovery
-from oauth2client.client import GoogleCredentials
-import kraken.invoke.command as runcommand
-from krkn_lib.k8s import KrknKubernetes
-
-class GCP:
-    def __init__(self):
-        try: 
-            gapp_creds = os.getenv("GOOGLE_APPLICATION_CREDENTIALS")
-            with open(gapp_creds, "r") as f:
-                f_str = f.read()
-                self.project = json.loads(f_str)['project_id']
-            #self.project = runcommand.invoke("gcloud config get-value project").split("/n")[0].strip()
-            logging.info("project " + str(self.project) + "!")
-            credentials = GoogleCredentials.get_application_default()
-            self.client = discovery.build("compute", "v1", credentials=credentials, cache_discovery=False)
-
-        except Exception as e: 
-            logging.error("Error on setting up GCP connection: " + str(e))
-            sys.exit(1)
-
-    # Get the instance ID of the node
-    def get_instance_id(self, node):
-        zone_request = self.client.zones().list(project=self.project)
-        while zone_request is not None:
-            zone_response = zone_request.execute()
-            for zone in zone_response["items"]:
-                instances_request = self.client.instances().list(project=self.project, zone=zone["name"])
-                while instances_request is not None:
-                    instance_response = instances_request.execute()
-                    if "items" in instance_response.keys():
-                        for instance in instance_response["items"]:
-                            if instance["name"] in node:
-                                return instance["name"], zone["name"]
-                    instances_request = self.client.zones().list_next(
-                        previous_request=instances_request, previous_response=instance_response
-                    )
-            zone_request = self.client.zones().list_next(previous_request=zone_request, previous_response=zone_response)
-        logging.info("no instances ")
-
-    # Start the node instance
-    def start_instances(self, zone, instance_id):
-        try:
-            self.client.instances().start(project=self.project, zone=zone, instance=instance_id).execute()
-            logging.info("vm name " + str(instance_id) + " started")
-        except Exception as e:
-            logging.error(
-                "Failed to start node instance %s. Encountered following " "exception: %s." % (instance_id, e)
-            )
-            # removed_exit
-            # sys.exit(1)
-            raise RuntimeError()
-
-    # Stop the node instance
-    def stop_instances(self, zone, instance_id):
-        try:
-            self.client.instances().stop(project=self.project, zone=zone, instance=instance_id).execute()
-            logging.info("vm name " + str(instance_id) + " stopped")
-        except Exception as e:
-            logging.error("Failed to stop node instance %s. Encountered following " "exception: %s." % (instance_id, e))
-            # removed_exit
-            # sys.exit(1)
-            raise RuntimeError()
-
-    # Start the node instance
-    def suspend_instances(self, zone, instance_id):
-        try:
-            self.client.instances().suspend(project=self.project, zone=zone, instance=instance_id).execute()
-            logging.info("vm name " + str(instance_id) + " suspended")
-        except Exception as e:
-            logging.error(
-                "Failed to suspend node instance %s. Encountered following " "exception: %s." % (instance_id, e)
-            )
-            # removed_exit
-            # sys.exit(1)
-            raise RuntimeError()
-
-    # Terminate the node instance
-    def terminate_instances(self, zone, instance_id):
-        try:
-            self.client.instances().delete(project=self.project, zone=zone, instance=instance_id).execute()
-            logging.info("vm name " + str(instance_id) + " terminated")
-        except Exception as e:
-            logging.error(
-                "Failed to start node instance %s. Encountered following " "exception: %s." % (instance_id, e)
-            )
-            # removed_exit
-            # sys.exit(1)
-            raise RuntimeError()
-
-    # Reboot the node instance
-    def reboot_instances(self, zone, instance_id):
-        try:
-            self.client.instances().reset(project=self.project, zone=zone, instance=instance_id).execute()
-            logging.info("vm name " + str(instance_id) + " rebooted")
-        except Exception as e:
-            logging.error(
-                "Failed to start node instance %s. Encountered following " "exception: %s." % (instance_id, e)
-            )
-            # removed_exit
-            # sys.exit(1)
-            raise RuntimeError()
-
-    # Get instance status
-    def get_instance_status(self, zone, instance_id, expected_status, timeout):
-        # statuses: PROVISIONING, STAGING, RUNNING, STOPPING, SUSPENDING, SUSPENDED, REPAIRING,
-        # and TERMINATED.
-        i = 0
-        sleeper = 5
-        while i <= timeout:
-            instStatus = self.client.instances().get(project=self.project, zone=zone, instance=instance_id).execute()
-            logging.info("Status of vm " + str(instStatus["status"]))
-            if instStatus["status"] == expected_status:
-                return True
-            time.sleep(sleeper)
-            i += sleeper
-        logging.error("Status of %s was not %s in %s seconds" % (instance_id, expected_status, timeout))
-        return False
-
-    # Wait until the node instance is suspended
-    def wait_until_suspended(self, zone, instance_id, timeout):
-        return self.get_instance_status(zone, instance_id, "SUSPENDED", timeout)
-
-    # Wait until the node instance is running
-    def wait_until_running(self, zone, instance_id, timeout):
-        return self.get_instance_status(zone, instance_id, "RUNNING", timeout)
-
-    # Wait until the node instance is stopped
-    def wait_until_stopped(self, zone, instance_id, timeout):
-        return self.get_instance_status(zone, instance_id, "TERMINATED", timeout)
-
-    # Wait until the node instance is terminated
-    def wait_until_terminated(self, zone, instance_id, timeout):
-        try:
-            i = 0
-            sleeper = 5
-            while i <= timeout:
-                instStatus = (
-                    self.client.instances().get(project=self.project, zone=zone, instance=instance_id).execute()
-                )
-                logging.info("Status of vm " + str(instStatus["status"]))
-                time.sleep(sleeper)
-        except Exception as e:
-            logging.info("here " + str(e))
-            return True
-
-
-# krkn_lib
-class gcp_node_scenarios(abstract_node_scenarios):
-    def __init__(self, kubecli: KrknKubernetes):
-        super().__init__(kubecli)
-        self.gcp = GCP()
-
-    # Node scenario to start the node
-    def node_start_scenario(self, instance_kill_count, node, timeout):
-        for _ in range(instance_kill_count):
-            try:
-                logging.info("Starting node_start_scenario injection")
-                instance_id, zone = self.gcp.get_instance_id(node)
-                logging.info("Starting the node %s with instance ID: %s " % (node, instance_id))
-                self.gcp.start_instances(zone, instance_id)
-                self.gcp.wait_until_running(zone, instance_id, timeout)
-                nodeaction.wait_for_ready_status(node, timeout, self.kubecli)
-                logging.info("Node with instance ID: %s is in running state" % instance_id)
-                logging.info("node_start_scenario has been successfully injected!")
-            except Exception as e:
-                logging.error(
-                    "Failed to start node instance. Encountered following " "exception: %s. Test Failed" % (e)
-                )
-                logging.error("node_start_scenario injection failed!")
-                # removed_exit
-                # sys.exit(1)
-                raise RuntimeError()
-
-    # Node scenario to stop the node
-    def node_stop_scenario(self, instance_kill_count, node, timeout):
-        logging.info("stop scenario")
-        for _ in range(instance_kill_count):
-            try:
-                logging.info("Starting node_stop_scenario injection")
-                instance_id, zone = self.gcp.get_instance_id(node)
-                logging.info("Stopping the node %s with instance ID: %s " % (node, instance_id))
-                self.gcp.stop_instances(zone, instance_id)
-                self.gcp.wait_until_stopped(zone, instance_id, timeout)
-                logging.info("Node with instance ID: %s is in stopped state" % instance_id)
-                nodeaction.wait_for_unknown_status(node, timeout, self.kubecli)
-            except Exception as e:
-                logging.error("Failed to stop node instance. Encountered following exception: %s. " "Test Failed" % (e))
-                logging.error("node_stop_scenario injection failed!")
-                # removed_exit
-                # sys.exit(1)
-                raise RuntimeError()
-
-    # Node scenario to terminate the node
-    def node_termination_scenario(self, instance_kill_count, node, timeout):
-        for _ in range(instance_kill_count):
-            try:
-                logging.info("Starting node_termination_scenario injection")
-                instance_id, zone = self.gcp.get_instance_id(node)
-                logging.info("Terminating the node %s with instance ID: %s " % (node, instance_id))
-                self.gcp.terminate_instances(zone, instance_id)
-                self.gcp.wait_until_terminated(zone, instance_id, timeout)
-                for _ in range(timeout):
-                    if node not in self.kubecli.list_nodes():
-                        break
-                    time.sleep(1)
-                if node in self.kubecli.list_nodes():
-                    raise Exception("Node could not be terminated")
-                logging.info("Node with instance ID: %s has been terminated" % instance_id)
-                logging.info("node_termination_scenario has been successfuly injected!")
-            except Exception as e:
-                logging.error(
-                    "Failed to terminate node instance. Encountered following exception:" " %s. Test Failed" % e
-                )
-                logging.error("node_termination_scenario injection failed!")
-                # removed_exit
-                # sys.exit(1)
-                raise RuntimeError()
-
-    # Node scenario to reboot the node
-    def node_reboot_scenario(self, instance_kill_count, node, timeout):
-        for _ in range(instance_kill_count):
-            try:
-                logging.info("Starting node_reboot_scenario injection")
-                instance_id, zone = self.gcp.get_instance_id(node)
-                logging.info("Rebooting the node %s with instance ID: %s " % (node, instance_id))
-                self.gcp.reboot_instances(zone, instance_id)
-                nodeaction.wait_for_ready_status(node, timeout, self.kubecli)
-                logging.info("Node with instance ID: %s has been rebooted" % instance_id)
-                logging.info("node_reboot_scenario has been successfuly injected!")
-            except Exception as e:
-                logging.error(
-                    "Failed to reboot node instance. Encountered following exception:" " %s. Test Failed" % (e)
-                )
-                logging.error("node_reboot_scenario injection failed!")
-                # removed_exit
-                # sys.exit(1)
-                raise RuntimeError()

kraken/node_actions/general_cloud_node_scenarios.py

@@ -1,29 +0,0 @@
-import logging
-from kraken.node_actions.abstract_node_scenarios import abstract_node_scenarios
-from krkn_lib.k8s import KrknKubernetes
-
-class GENERAL:
-    def __init__(self):
-        pass
-
-# krkn_lib
-class general_node_scenarios(abstract_node_scenarios):
-    def __init__(self, kubecli: KrknKubernetes):
-        super().__init__(kubecli)
-        self.general = GENERAL()
-
-    # Node scenario to start the node
-    def node_start_scenario(self, instance_kill_count, node, timeout):
-        logging.info("Node start is not set up yet for this cloud type, " "no action is going to be taken")
-
-    # Node scenario to stop the node
-    def node_stop_scenario(self, instance_kill_count, node, timeout):
-        logging.info("Node stop is not set up yet for this cloud type," " no action is going to be taken")
-
-    # Node scenario to terminate the node
-    def node_termination_scenario(self, instance_kill_count, node, timeout):
-        logging.info("Node termination is not set up yet for this cloud type, " "no action is going to be taken")
-
-    # Node scenario to reboot the node
-    def node_reboot_scenario(self, instance_kill_count, node, timeout):
-        logging.info("Node reboot is not set up yet for this cloud type," " no action is going to be taken")

kraken/node_actions/run.py

@@ -1,154 +0,0 @@
-import yaml
-import logging
-import sys
-import time
-from kraken.node_actions.aws_node_scenarios import aws_node_scenarios
-from kraken.node_actions.general_cloud_node_scenarios import general_node_scenarios
-from kraken.node_actions.az_node_scenarios import azure_node_scenarios
-from kraken.node_actions.gcp_node_scenarios import gcp_node_scenarios
-from kraken.node_actions.openstack_node_scenarios import openstack_node_scenarios
-from kraken.node_actions.alibaba_node_scenarios import alibaba_node_scenarios
-from kraken.node_actions.bm_node_scenarios import bm_node_scenarios
-from kraken.node_actions.docker_node_scenarios import docker_node_scenarios
-import kraken.node_actions.common_node_functions as common_node_functions
-import kraken.cerberus.setup as cerberus
-from krkn_lib.k8s import KrknKubernetes
-from krkn_lib.telemetry.k8s import KrknTelemetryKubernetes
-from krkn_lib.models.telemetry import ScenarioTelemetry
-from krkn_lib.utils.functions import get_yaml_item_value, log_exception
-
-node_general = False
-
-
-# Get the node scenarios object of specfied cloud type
-# krkn_lib
-def get_node_scenario_object(node_scenario, kubecli: KrknKubernetes):
-    if "cloud_type" not in node_scenario.keys() or node_scenario["cloud_type"] == "generic":
-        global node_general
-        node_general = True
-        return general_node_scenarios(kubecli)
-    if node_scenario["cloud_type"] == "aws":
-        return aws_node_scenarios(kubecli)
-    elif node_scenario["cloud_type"] == "gcp":
-        return gcp_node_scenarios(kubecli)
-    elif node_scenario["cloud_type"] == "openstack":
-        return openstack_node_scenarios(kubecli)
-    elif node_scenario["cloud_type"] == "azure" or node_scenario["cloud_type"] == "az":
-        return azure_node_scenarios(kubecli)
-    elif node_scenario["cloud_type"] == "alibaba" or node_scenario["cloud_type"] == "alicloud":
-        return alibaba_node_scenarios(kubecli)
-    elif node_scenario["cloud_type"] == "bm":
-        return bm_node_scenarios(
-            node_scenario.get("bmc_info"), node_scenario.get("bmc_user", None), node_scenario.get("bmc_password", None),
-            kubecli
-        )
-    elif node_scenario["cloud_type"] == "docker":
-        return docker_node_scenarios(kubecli)
-    else:
-        logging.error(
-            "Cloud type " + node_scenario["cloud_type"] + " is not currently supported; "
-            "try using 'generic' if wanting to stop/start kubelet or fork bomb on any "
-            "cluster"
-        )
-        sys.exit(1)
-
-
-# Run defined scenarios
-# krkn_lib
-def run(scenarios_list, config, wait_duration, kubecli: KrknKubernetes, telemetry: KrknTelemetryKubernetes) -> (list[str], list[ScenarioTelemetry]):
-    scenario_telemetries: list[ScenarioTelemetry] = []
-    failed_scenarios = []
-    for node_scenario_config in scenarios_list:
-        scenario_telemetry = ScenarioTelemetry()
-        scenario_telemetry.scenario = node_scenario_config
-        scenario_telemetry.start_timestamp = time.time()
-        telemetry.set_parameters_base64(scenario_telemetry, node_scenario_config)
-        with open(node_scenario_config, "r") as f:
-            node_scenario_config = yaml.full_load(f)
-            for node_scenario in node_scenario_config["node_scenarios"]:
-                node_scenario_object = get_node_scenario_object(node_scenario, kubecli)
-                if node_scenario["actions"]:
-                    for action in node_scenario["actions"]:
-                        start_time = int(time.time())
-                        try:
-                            inject_node_scenario(action, node_scenario, node_scenario_object, kubecli)
-                            logging.info("Waiting for the specified duration: %s" % (wait_duration))
-                            time.sleep(wait_duration)
-                            end_time = int(time.time())
-                            cerberus.get_status(config, start_time, end_time)
-                            logging.info("")
-                        except (RuntimeError, Exception) as e:
-                            scenario_telemetry.exit_status = 1
-                            failed_scenarios.append(node_scenario_config)
-                            log_exception(node_scenario_config)
-                        else:
-                            scenario_telemetry.exit_status = 0
-
-                        scenario_telemetry.end_timestamp = time.time()
-                        scenario_telemetries.append(scenario_telemetry)
-
-    return failed_scenarios, scenario_telemetries
-
-
-# Inject the specified node scenario
-def inject_node_scenario(action, node_scenario, node_scenario_object, kubecli: KrknKubernetes):
-    generic_cloud_scenarios = ("stop_kubelet_scenario", "node_crash_scenario")
-    # Get the node scenario configurations
-    run_kill_count = get_yaml_item_value(node_scenario, "runs", 1)
-    instance_kill_count = get_yaml_item_value(
-        node_scenario, "instance_count", 1
-    )
-    node_name = get_yaml_item_value(node_scenario, "node_name", "")
-    label_selector = get_yaml_item_value(node_scenario, "label_selector", "")
-    if action == "node_stop_start_scenario":
-        duration = get_yaml_item_value(node_scenario, "duration", 120)
-    timeout = get_yaml_item_value(node_scenario, "timeout", 120)
-    service = get_yaml_item_value(node_scenario, "service", "")
-    ssh_private_key = get_yaml_item_value(
-        node_scenario, "ssh_private_key", "~/.ssh/id_rsa"
-    )
-    # Get the node to apply the scenario
-    if node_name:
-        node_name_list = node_name.split(",")
-    else:
-        node_name_list = [node_name]
-    for single_node_name in node_name_list:
-        nodes = common_node_functions.get_node(single_node_name, label_selector, instance_kill_count, kubecli)
-        for single_node in nodes:
-            if node_general and action not in generic_cloud_scenarios:
-                logging.info("Scenario: " + action + " is not set up for generic cloud type, skipping action")
-            else:
-                if action == "node_start_scenario":
-                    node_scenario_object.node_start_scenario(run_kill_count, single_node, timeout)
-                elif action == "node_stop_scenario":
-                    node_scenario_object.node_stop_scenario(run_kill_count, single_node, timeout)
-                elif action == "node_stop_start_scenario":
-                    node_scenario_object.node_stop_start_scenario(run_kill_count, single_node, timeout, duration)
-                elif action == "node_termination_scenario":
-                    node_scenario_object.node_termination_scenario(run_kill_count, single_node, timeout)
-                elif action == "node_reboot_scenario":
-                    node_scenario_object.node_reboot_scenario(run_kill_count, single_node, timeout)
-                elif action == "stop_start_kubelet_scenario":
-                    node_scenario_object.stop_start_kubelet_scenario(run_kill_count, single_node, timeout)
-                elif action == "stop_kubelet_scenario":
-                    node_scenario_object.stop_kubelet_scenario(run_kill_count, single_node, timeout)
-                elif action == "node_crash_scenario":
-                    node_scenario_object.node_crash_scenario(run_kill_count, single_node, timeout)
-                elif action == "stop_start_helper_node_scenario":
-                    if node_scenario["cloud_type"] != "openstack":
-                        logging.error(
-                            "Scenario: " + action + " is not supported for "
-                            "cloud type " + node_scenario["cloud_type"] + ", skipping action"
-                        )
-                    else:
-                        if not node_scenario["helper_node_ip"]:
-                            logging.error("Helper node IP address is not provided")
-                            sys.exit(1)
-                        node_scenario_object.helper_node_stop_start_scenario(
-                            run_kill_count, node_scenario["helper_node_ip"], timeout
-                        )
-                        node_scenario_object.helper_node_service_status(
-                            node_scenario["helper_node_ip"], service, ssh_private_key, timeout
-                        )
-                else:
-                    logging.info("There is no node action that matches %s, skipping scenario" % action)

kraken/plugins/__init__.py

@@ -1,320 +0,0 @@
-import dataclasses
-import json
-import logging
-from os.path import abspath
-from typing import List, Dict, Any
-import time
-
-from arcaflow_plugin_sdk import schema, serialization, jsonschema
-from arcaflow_plugin_kill_pod import kill_pods, wait_for_pods
-from krkn_lib.k8s import KrknKubernetes
-from krkn_lib.k8s.pods_monitor_pool import PodsMonitorPool
-
-import kraken.plugins.node_scenarios.vmware_plugin as vmware_plugin
-import kraken.plugins.node_scenarios.ibmcloud_plugin as ibmcloud_plugin
-from kraken.plugins.run_python_plugin import run_python_file
-from kraken.plugins.network.ingress_shaping import network_chaos
-from kraken.plugins.pod_network_outage.pod_network_outage_plugin import pod_outage
-from kraken.plugins.pod_network_outage.pod_network_outage_plugin import pod_egress_shaping
-from krkn_lib.telemetry.k8s import KrknTelemetryKubernetes
-from kraken.plugins.pod_network_outage.pod_network_outage_plugin import pod_ingress_shaping
-from krkn_lib.models.telemetry import ScenarioTelemetry
-from krkn_lib.utils.functions import log_exception
-
-
-@dataclasses.dataclass
-class PluginStep:
-    schema: schema.StepSchema
-    error_output_ids: List[str]
-
-    def render_output(self, output_id: str, output_data) -> str:
-        return json.dumps({
-            "output_id": output_id,
-            "output_data": self.schema.outputs[output_id].serialize(output_data),
-        }, indent='\t')
-
-
-class Plugins:
-    """
-    Plugins is a class that can run plugins sequentially. The output is rendered to the standard output and the process
-    is aborted if a step fails.
-    """
-    steps_by_id: Dict[str, PluginStep]
-
-    def __init__(self, steps: List[PluginStep]):
-        self.steps_by_id = dict()
-        for step in steps:
-            if step.schema.id in self.steps_by_id:
-                raise Exception(
-                    "Duplicate step ID: {}".format(step.schema.id)
-                )
-            self.steps_by_id[step.schema.id] = step
-
-    def unserialize_scenario(self, file: str) -> Any:
-        return serialization.load_from_file(abspath(file))
-
-    def run(self, file: str, kubeconfig_path: str, kraken_config: str, run_uuid:str):
-        """
-        Run executes a series of steps
-        """
-        data = self.unserialize_scenario(abspath(file))
-        if not isinstance(data, list):
-            raise Exception(
-                "Invalid scenario configuration file: {} expected list, found {}".format(file, type(data).__name__)
-            )
-        i = 0
-        for entry in data:
-            if not isinstance(entry, dict):
-                raise Exception(
-                    "Invalid scenario configuration file: {} expected a list of dict's, found {} on step {}".format(
-                        file,
-                        type(entry).__name__,
-                        i
-                    )
-                )
-            if "id" not in entry:
-                raise Exception(
-                    "Invalid scenario configuration file: {} missing 'id' field on step {}".format(
-                        file,
-                        i,
-                    )
-                )
-            if "config" not in entry:
-                raise Exception(
-                    "Invalid scenario configuration file: {} missing 'config' field on step {}".format(
-                        file,
-                        i,
-                    )
-                )
-
-            if entry["id"] not in self.steps_by_id:
-                raise Exception(
-                    "Invalid step {} in {} ID: {} expected one of: {}".format(
-                        i,
-                        file,
-                        entry["id"],
-                        ', '.join(self.steps_by_id.keys())
-                    )
-                )
-            step = self.steps_by_id[entry["id"]]
-            unserialized_input = step.schema.input.unserialize(entry["config"])
-            if "kubeconfig_path" in step.schema.input.properties:
-                unserialized_input.kubeconfig_path = kubeconfig_path
-            if "kraken_config" in step.schema.input.properties:
-                unserialized_input.kraken_config = kraken_config
-            output_id, output_data = step.schema(params=unserialized_input, run_id=run_uuid)
-
-            logging.info(step.render_output(output_id, output_data) + "\n")
-            if output_id in step.error_output_ids:
-                raise Exception(
-                    "Step {} in {} ({}) failed".format(i, file, step.schema.id)
-                )
-            i = i + 1
-
-    def json_schema(self):
-        """
-        This function generates a JSON schema document and renders it from the steps passed.
-        """
-        result = {
-            "$id": "https://github.com/redhat-chaos/krkn/",
-            "$schema": "https://json-schema.org/draft/2020-12/schema",
-            "title": "Kraken Arcaflow scenarios",
-            "description": "Serial execution of Arcaflow Python plugins. See https://github.com/arcaflow for details.",
-            "type": "array",
-            "minContains": 1,
-            "items": {
-                "oneOf": [
-
-                ]
-            }
-        }
-        for step_id in self.steps_by_id.keys():
-            step = self.steps_by_id[step_id]
-            step_input = jsonschema.step_input(step.schema)
-            del step_input["$id"]
-            del step_input["$schema"]
-            del step_input["title"]
-            del step_input["description"]
-            result["items"]["oneOf"].append({
-                "type": "object",
-                "properties": {
-                    "id": {
-                        "type": "string",
-                        "const": step_id,
-                    },
-                    "config": step_input,
-                },
-                "required": [
-                    "id",
-                    "config",
-                ]
-            })
-        return json.dumps(result, indent="\t")
-
-
-PLUGINS = Plugins(
-    [
-        PluginStep(
-            kill_pods,
-            [
-                "error",
-            ]
-        ),
-        PluginStep(
-            wait_for_pods,
-            [
-                "error"
-            ]
-        ),
-        PluginStep(
-            run_python_file,
-            [
-                "error"
-            ]
-        ),
-        PluginStep(
-            vmware_plugin.node_start,
-            [
-                "error"
-            ]
-        ),
-        PluginStep(
-            vmware_plugin.node_stop,
-            [
-                "error"
-            ]
-        ),
-        PluginStep(
-            vmware_plugin.node_reboot,
-            [
-                "error"
-            ]
-        ),
-        PluginStep(
-            vmware_plugin.node_terminate,
-            [
-                "error"
-            ]
-        ),
-        PluginStep(
-            ibmcloud_plugin.node_start,
-            [
-                "error"
-            ]
-        ),
-        PluginStep(
-            ibmcloud_plugin.node_stop,
-            [
-                "error"
-            ]
-        ),
-        PluginStep(
-            ibmcloud_plugin.node_reboot,
-            [
-                "error"
-            ]
-        ),
-        PluginStep(
-            ibmcloud_plugin.node_terminate,
-            [
-                "error"
-            ]
-        ),
-        PluginStep(
-            network_chaos,
-            [
-                "error"
-            ]
-        ),        
-        PluginStep(
-            pod_outage,
-            [
-                "error"
-            ]
-        ),
-         PluginStep(
-            pod_egress_shaping,
-            [
-                "error"
-            ]
-        ),
-         PluginStep(
-            pod_ingress_shaping,
-            [
-                "error"
-            ]
-        )                  
-    ]
-)
-
-
-def run(scenarios: List[str],
-        kubeconfig_path: str,
-        kraken_config: str,
-        failed_post_scenarios: List[str],
-        wait_duration: int,
-        telemetry: KrknTelemetryKubernetes,
-        kubecli: KrknKubernetes,
-        run_uuid: str
-        ) -> (List[str], list[ScenarioTelemetry]):
-
-    scenario_telemetries: list[ScenarioTelemetry] = []
-    for scenario in scenarios:
-        scenario_telemetry = ScenarioTelemetry()
-        scenario_telemetry.scenario = scenario
-        scenario_telemetry.start_timestamp = time.time()
-        telemetry.set_parameters_base64(scenario_telemetry, scenario)
-        logging.info('scenario ' + str(scenario))
-        pool = PodsMonitorPool(kubecli)
-        kill_scenarios = [kill_scenario for kill_scenario in PLUGINS.unserialize_scenario(scenario) if kill_scenario["id"] == "kill-pods"]
-
-        try:
-            start_monitoring(pool, kill_scenarios)
-            PLUGINS.run(scenario, kubeconfig_path, kraken_config, run_uuid)
-            result = pool.join()
-            scenario_telemetry.affected_pods = result
-            if result.error:
-                raise Exception(f"unrecovered pods: {result.error}")
-
-        except Exception as e:
-            logging.error(f"scenario exception: {str(e)}")
-            scenario_telemetry.exit_status = 1
-            pool.cancel()
-            failed_post_scenarios.append(scenario)
-            log_exception(scenario)
-        else:
-            scenario_telemetry.exit_status = 0
-            logging.info("Waiting for the specified duration: %s" % (wait_duration))
-            time.sleep(wait_duration)
-        scenario_telemetries.append(scenario_telemetry)
-        scenario_telemetry.end_timestamp = time.time()
-
-    return failed_post_scenarios, scenario_telemetries
-
-
-def start_monitoring(pool: PodsMonitorPool, scenarios: list[Any]):
-    for kill_scenario in scenarios:
-        recovery_time = kill_scenario["config"]["krkn_pod_recovery_time"]
-        if ("namespace_pattern" in kill_scenario["config"] and
-                "label_selector" in kill_scenario["config"]):
-            namespace_pattern = kill_scenario["config"]["namespace_pattern"]
-            label_selector = kill_scenario["config"]["label_selector"]
-            pool.select_and_monitor_by_namespace_pattern_and_label(
-                namespace_pattern=namespace_pattern,
-                label_selector=label_selector,
-                max_timeout=recovery_time)
-            logging.info(
-                f"waiting {recovery_time} seconds for pod recovery, "
-                f"pod label selector: {label_selector} namespace pattern: {namespace_pattern}")
-
-        elif ("namespace_pattern" in kill_scenario["config"] and
-              "name_pattern" in kill_scenario["config"]):
-            namespace_pattern = kill_scenario["config"]["namespace_pattern"]
-            name_pattern = kill_scenario["config"]["name_pattern"]
-            pool.select_and_monitor_by_name_pattern_and_namespace_pattern(pod_name_pattern=name_pattern,
-                                                                          namespace_pattern=namespace_pattern,
-                                                                          max_timeout=recovery_time)
-            logging.info(f"waiting {recovery_time} seconds for pod recovery, "
-                         f"pod name pattern: {name_pattern} namespace pattern: {namespace_pattern}")
-        else:
-            raise Exception(f"impossible to determine monitor parameters, check {kill_scenario} configuration")

kraken/plugins/__main__.py

@@ -1,4 +0,0 @@
-from kraken.plugins import PLUGINS
-
-if __name__ == "__main__":
-    print(PLUGINS.json_schema())

kraken/plugins/node_scenarios/ibmcloud_plugin.py

@@ -1,563 +0,0 @@
-#!/usr/bin/env python
-import sys
-import time
-import typing
-from os import environ
-from dataclasses import dataclass, field
-import random
-from traceback import format_exc
-import logging
-from kraken.plugins.node_scenarios import kubernetes_functions as kube_helper
-from arcaflow_plugin_sdk import validation, plugin
-from kubernetes import client, watch
-from ibm_vpc import VpcV1
-from ibm_cloud_sdk_core.authenticators import IAMAuthenticator
-from ibm_cloud_sdk_core import ApiException
-import requests
-import sys
-
-
-class IbmCloud:
-    def __init__(self):
-        """
-        Initialize the ibm cloud client by using the the env variables:
-            'IBMC_APIKEY' 'IBMC_URL'
-        """
-        apiKey = environ.get("IBMC_APIKEY")
-        service_url = environ.get("IBMC_URL")
-        if not apiKey:
-            raise Exception(
-                "Environmental variable 'IBMC_APIKEY' is not set"
-            )
-        if not service_url:
-            raise Exception(
-                "Environmental variable 'IBMC_URL' is not set"
-            )
-        try: 
-            authenticator = IAMAuthenticator(apiKey)
-            self.service = VpcV1(authenticator=authenticator)
-
-            self.service.set_service_url(service_url)
-        except Exception as e: 
-            logging.error("error authenticating" + str(e))
-            sys.exit(1)
-
-    def delete_instance(self, instance_id):
-        """
-        Deletes the Instance whose name is given by 'instance_id'
-        """
-        try: 
-            self.service.delete_instance(instance_id)
-            logging.info("Deleted Instance -- '{}'".format(instance_id))
-        except Exception as e:
-            logging.info(
-                "Instance '{}' could not be deleted. ".format(
-                    instance_id
-                )
-            )
-            return False
-
-    def reboot_instances(self, instance_id):
-        """
-        Reboots the Instance whose name is given by 'instance_id'. Returns True if successful, or
-        returns False if the Instance is not powered on
-        """
-
-        try:
-            self.service.create_instance_action(
-                    instance_id,
-                    type='reboot',
-                )
-            logging.info("Reset Instance -- '{}'".format(instance_id))
-            return True
-        except Exception as e:
-            logging.info(
-                "Instance '{}' could not be rebooted".format(
-                    instance_id
-                )
-            )
-            return False
-
-    def stop_instances(self, instance_id):
-        """
-        Stops the Instance whose name is given by 'instance_id'. Returns True if successful, or
-        returns False if the Instance is already stopped
-        """
-
-        try:
-            self.service.create_instance_action(
-                    instance_id,
-                    type='stop',
-                )
-            logging.info("Stopped Instance -- '{}'".format(instance_id))
-            return True
-        except Exception as e:
-            logging.info(
-                "Instance '{}' could not be stopped".format(instance_id)
-            )
-            logging.info("error" + str(e))
-            return False
-
-    def start_instances(self, instance_id):
-        """
-        Stops the Instance whose name is given by 'instance_id'. Returns True if successful, or
-        returns False if the Instance is already running
-        """
-
-        try:
-            self.service.create_instance_action(
-                    instance_id,
-                    type='start',
-                )
-            logging.info("Started Instance -- '{}'".format(instance_id))
-            return True
-        except Exception as e:
-            logging.info("Instance '{}' could not start running".format(instance_id))
-            return False
-
-    def list_instances(self):
-        """
-        Returns a list of Instances present in the datacenter
-        """
-        instance_names = []
-        try: 
-            instances_result = self.service.list_instances().get_result()
-            instances_list = instances_result['instances']
-            for vpc in instances_list:
-                instance_names.append({"vpc_name": vpc['name'], "vpc_id": vpc['id']})
-            starting_count = instances_result['total_count']
-            while instances_result['total_count'] == instances_result['limit']: 
-                instances_result = self.service.list_instances(start=starting_count).get_result()
-                instances_list = instances_result['instances']
-                starting_count += instances_result['total_count']
-                for vpc in instances_list:
-                    instance_names.append({"vpc_name": vpc.name, "vpc_id": vpc.id})
-        except Exception as e: 
-            logging.error("Error listing out instances: " + str(e))
-            sys.exit(1)
-        return instance_names
-    
-    def find_id_in_list(self, name, vpc_list): 
-        for vpc in vpc_list:
-            if vpc['vpc_name'] == name: 
-                return vpc['vpc_id']
-
-    def get_instance_status(self, instance_id):
-        """
-        Returns the status of the Instance whose name is given by 'instance_id'
-        """
-
-        try:
-            instance = self.service.get_instance(instance_id).get_result()
-            state = instance['status']
-            return state
-        except Exception as e:
-            logging.error(
-                "Failed to get node instance status %s. Encountered following "
-                "exception: %s." % (instance_id, e)
-            )
-            return None
-
-    def wait_until_deleted(self, instance_id, timeout):
-        """
-        Waits until the instance is deleted or until the timeout. Returns True if
-        the instance is successfully deleted, else returns False
-        """
-
-        time_counter = 0
-        vpc = self.get_instance_status(instance_id)
-        while vpc is not None:
-            vpc = self.get_instance_status(instance_id)
-            logging.info(
-                "Instance %s is still being deleted, sleeping for 5 seconds" % instance_id
-            )
-            time.sleep(5)
-            time_counter += 5
-            if time_counter >= timeout:
-                logging.info(
-                    "Instance %s is still not deleted in allotted time" % instance_id
-                )
-                return False
-        return True
-
-    def wait_until_running(self, instance_id, timeout):
-        """
-        Waits until the Instance switches to running state or until the timeout.
-        Returns True if the Instance switches to running, else returns False
-        """
-
-        time_counter = 0
-        status = self.get_instance_status(instance_id)
-        while status != "running":
-            status = self.get_instance_status(instance_id)
-            logging.info(
-                "Instance %s is still not running, sleeping for 5 seconds" % instance_id
-            )
-            time.sleep(5)
-            time_counter += 5
-            if time_counter >= timeout:
-                logging.info("Instance %s is still not ready in allotted time" % instance_id)
-                return False
-        return True
-
-    def wait_until_stopped(self, instance_id, timeout):
-        """
-        Waits until the Instance switches to stopped state or until the timeout.
-        Returns True if the Instance switches to stopped, else returns False
-        """
-
-        time_counter = 0
-        status = self.get_instance_status(instance_id)
-        while status != "stopped":
-            status = self.get_instance_status(instance_id)
-            logging.info(
-                "Instance %s is still not stopped, sleeping for 5 seconds" % instance_id
-            )
-            time.sleep(5)
-            time_counter += 5
-            if time_counter >= timeout:
-                logging.info("Instance %s is still not stopped in allotted time" % instance_id)
-                return False
-        return True
-
-    def wait_until_rebooted(self, instance_id, timeout):
-        """
-        Waits until the Instance switches to restarting state and then running state or until the timeout.
-        Returns True if the Instance switches back to running, else returns False
-        """
-
-        time_counter = 0
-        status = self.get_instance_status(instance_id)
-        while status == "starting":
-            status = self.get_instance_status(instance_id)
-            logging.info(
-                "Instance %s is still restarting, sleeping for 5 seconds" % instance_id
-            )
-            time.sleep(5)
-            time_counter += 5
-            if time_counter >= timeout:
-                logging.info("Instance %s is still restarting after allotted time" % instance_id)
-                return False
-        self.wait_until_running(instance_id, timeout)
-        return True
-
-
-@dataclass
-class Node:
-    name: str
-
-
-@dataclass
-class NodeScenarioSuccessOutput:
-
-    nodes: typing.Dict[int, Node] = field(
-        metadata={
-            "name": "Nodes started/stopped/terminated/rebooted",
-            "description": """Map between timestamps and the pods started/stopped/terminated/rebooted.
-                        The timestamp is provided in nanoseconds""",
-        }
-    )
-    action: kube_helper.Actions = field(
-        metadata={
-            "name": "The action performed on the node",
-            "description": """The action performed or attempted to be performed on the node. Possible values
-                        are : Start, Stop, Terminate, Reboot""",
-        }
-    )
-
-
-@dataclass
-class NodeScenarioErrorOutput:
-
-    error: str
-    action: kube_helper.Actions = field(
-        metadata={
-            "name": "The action performed on the node",
-            "description": """The action attempted to be performed on the node. Possible values are : Start
-                        Stop, Terminate, Reboot""",
-        }
-    )
-
-
-@dataclass
-class NodeScenarioConfig:
-
-    name: typing.Annotated[
-        typing.Optional[str],
-        validation.required_if_not("label_selector"),
-        validation.required_if("skip_openshift_checks"),
-    ] = field(
-        default=None,
-        metadata={
-            "name": "Name",
-            "description": "Name(s) for target nodes. Required if label_selector is not set.",
-        },
-    )
-
-    runs: typing.Annotated[typing.Optional[int], validation.min(1)] = field(
-        default=1,
-        metadata={
-            "name": "Number of runs per node",
-            "description": "Number of times to inject each scenario under actions (will perform on same node each time)",
-        },
-    )
-
-    label_selector: typing.Annotated[
-        typing.Optional[str], 
-        validation.min(1),
-        validation.required_if_not("name")
-    ] = field(
-        default=None,
-        metadata={
-            "name": "Label selector",
-            "description": "Kubernetes label selector for the target nodes. Required if name is not set.\n"
-            "See https://kubernetes.io/docs/concepts/overview/working-with-objects/labels/ for details.",
-        },
-    )
-
-    timeout: typing.Annotated[typing.Optional[int], validation.min(1)] = field(
-        default=180,
-        metadata={
-            "name": "Timeout",
-            "description": "Timeout to wait for the target pod(s) to be removed in seconds.",
-        },
-    )
-
-    instance_count: typing.Annotated[typing.Optional[int], validation.min(1)] = field(
-        default=1,
-        metadata={
-            "name": "Instance Count",
-            "description": "Number of nodes to perform action/select that match the label selector.",
-        },
-    )
-
-    skip_openshift_checks: typing.Optional[bool] = field(
-        default=False,
-        metadata={
-            "name": "Skip Openshift Checks",
-            "description": "Skip checking the status of the openshift nodes.",
-        },
-    )
-
-    kubeconfig_path: typing.Optional[str] = field(
-        default=None,
-        metadata={
-            "name": "Kubeconfig path",
-            "description": "Path to your Kubeconfig file. Defaults to ~/.kube/config.\n"
-            "See https://kubernetes.io/docs/concepts/configuration/organize-cluster-access-kubeconfig/ for "
-            "details.",
-        },
-    )
-
-
-@plugin.step(
-    id="ibmcloud-node-start",
-    name="Start the node",
-    description="Start the node(s) by starting the Ibmcloud Instance on which the node is configured",
-    outputs={"success": NodeScenarioSuccessOutput, "error": NodeScenarioErrorOutput},
-)
-def node_start(
-    cfg: NodeScenarioConfig,
-) -> typing.Tuple[
-    str, typing.Union[NodeScenarioSuccessOutput, NodeScenarioErrorOutput]
-]:
-    with kube_helper.setup_kubernetes(None) as cli:
-        ibmcloud = IbmCloud()
-        core_v1 = client.CoreV1Api(cli)
-        watch_resource = watch.Watch()
-        node_list = kube_helper.get_node_list(cfg, kube_helper.Actions.START, core_v1)
-        node_name_id_list = ibmcloud.list_instances()
-        nodes_started = {}
-        for name in node_list:
-            try:
-                for _ in range(cfg.runs):
-                    logging.info("Starting node_start_scenario injection")
-                    logging.info("Starting the node %s " % (name))
-                    instance_id = ibmcloud.find_id_in_list(name, node_name_id_list)
-                    if instance_id: 
-                        vm_started = ibmcloud.start_instances(instance_id)
-                        if vm_started:
-                            ibmcloud.wait_until_running(instance_id, cfg.timeout)
-                            if not cfg.skip_openshift_checks:
-                                kube_helper.wait_for_ready_status(
-                                    name, cfg.timeout, watch_resource, core_v1
-                                )
-                            nodes_started[int(time.time_ns())] = Node(name=name)
-                        logging.info("Node with instance ID: %s is in running state" % name)
-                        logging.info("node_start_scenario has been successfully injected!")
-                    else: 
-                        logging.error("Failed to find node that matched instances on ibm cloud in region")
-                        return "error", NodeScenarioErrorOutput(
-                            "No matching vpc with node name " + name, kube_helper.Actions.START
-                        )
-            except Exception as e:
-                logging.error("Failed to start node instance. Test Failed")
-                logging.error("node_start_scenario injection failed!")
-                return "error", NodeScenarioErrorOutput(
-                    format_exc(), kube_helper.Actions.START
-                )
-
-    return "success", NodeScenarioSuccessOutput(
-        nodes_started, kube_helper.Actions.START
-    )
-
-
-@plugin.step(
-    id="ibmcloud-node-stop",
-    name="Stop the node",
-    description="Stop the node(s) by starting the Ibmcloud Instance on which the node is configured",
-    outputs={"success": NodeScenarioSuccessOutput, "error": NodeScenarioErrorOutput},
-)
-def node_stop(
-    cfg: NodeScenarioConfig,
-) -> typing.Tuple[
-    str, typing.Union[NodeScenarioSuccessOutput, NodeScenarioErrorOutput]
-]:
-    with kube_helper.setup_kubernetes(None) as cli:
-        ibmcloud = IbmCloud()
-        core_v1 = client.CoreV1Api(cli)
-        watch_resource = watch.Watch()
-        logging.info('set up done')
-        node_list = kube_helper.get_node_list(cfg, kube_helper.Actions.STOP, core_v1)
-        logging.info("set node list" + str(node_list))
-        node_name_id_list = ibmcloud.list_instances()
-        logging.info('node names' + str(node_name_id_list))
-        nodes_stopped = {}
-        for name in node_list:
-            try:
-                for _ in range(cfg.runs):
-                    logging.info("Starting node_stop_scenario injection")
-                    logging.info("Stopping the node %s " % (name))
-                    instance_id = ibmcloud.find_id_in_list(name, node_name_id_list)
-                    if instance_id:
-                        vm_stopped = ibmcloud.stop_instances(instance_id)
-                        if vm_stopped:
-                            ibmcloud.wait_until_stopped(instance_id, cfg.timeout)
-                            if not cfg.skip_openshift_checks:
-                                kube_helper.wait_for_ready_status(
-                                    name, cfg.timeout, watch_resource, core_v1
-                                )
-                            nodes_stopped[int(time.time_ns())] = Node(name=name)
-                        logging.info("Node with instance ID: %s is in stopped state" % name)
-                        logging.info("node_stop_scenario has been successfully injected!")
-                    else: 
-                        logging.error("Failed to find node that matched instances on ibm cloud in region")
-                        return "error", NodeScenarioErrorOutput(
-                            "No matching vpc with node name " + name, kube_helper.Actions.STOP
-                        )
-            except Exception as e:
-                logging.error("Failed to stop node instance. Test Failed")
-                logging.error("node_stop_scenario injection failed!")
-                return "error", NodeScenarioErrorOutput(
-                    format_exc(), kube_helper.Actions.STOP
-                )
-
-        return "success", NodeScenarioSuccessOutput(
-            nodes_stopped, kube_helper.Actions.STOP
-        )
-
-
-@plugin.step(
-    id="ibmcloud-node-reboot",
-    name="Reboot Ibmcloud Instance",
-    description="Reboot the node(s) by starting the Ibmcloud Instance on which the node is configured",
-    outputs={"success": NodeScenarioSuccessOutput, "error": NodeScenarioErrorOutput},
-)
-def node_reboot(
-    cfg: NodeScenarioConfig,
-) -> typing.Tuple[
-    str, typing.Union[NodeScenarioSuccessOutput, NodeScenarioErrorOutput]
-]:
-    with kube_helper.setup_kubernetes(None) as cli:
-        ibmcloud = IbmCloud()
-        core_v1 = client.CoreV1Api(cli)
-        watch_resource = watch.Watch()
-        node_list = kube_helper.get_node_list(cfg, kube_helper.Actions.REBOOT, core_v1)
-        node_name_id_list = ibmcloud.list_instances()
-        nodes_rebooted = {}
-        for name in node_list:
-            try:
-                for _ in range(cfg.runs):
-                    logging.info("Starting node_reboot_scenario injection")
-                    logging.info("Rebooting the node %s " % (name))
-                    instance_id = ibmcloud.find_id_in_list(name, node_name_id_list)
-                    if instance_id:
-                        ibmcloud.reboot_instances(instance_id)
-                        ibmcloud.wait_until_rebooted(instance_id, cfg.timeout)
-                        if not cfg.skip_openshift_checks:
-                            kube_helper.wait_for_unknown_status(
-                                name, cfg.timeout, watch_resource, core_v1
-                            )
-                            kube_helper.wait_for_ready_status(
-                                name, cfg.timeout, watch_resource, core_v1
-                            )
-                        nodes_rebooted[int(time.time_ns())] = Node(name=name)
-                        logging.info(
-                            "Node with instance ID: %s has rebooted successfully" % name
-                        )
-                        logging.info("node_reboot_scenario has been successfully injected!")
-                    else: 
-                        logging.error("Failed to find node that matched instances on ibm cloud in region")
-                        return "error", NodeScenarioErrorOutput(
-                            "No matching vpc with node name " + name, kube_helper.Actions.REBOOT
-                        )
-            except Exception as e:
-                logging.error("Failed to reboot node instance. Test Failed")
-                logging.error("node_reboot_scenario injection failed!")
-                return "error", NodeScenarioErrorOutput(
-                    format_exc(), kube_helper.Actions.REBOOT
-                )
-
-    return "success", NodeScenarioSuccessOutput(
-        nodes_rebooted, kube_helper.Actions.REBOOT
-    )
-
-
-@plugin.step(
-    id="ibmcloud-node-terminate",
-    name="Reboot Ibmcloud Instance",
-    description="Wait for node to be deleted",
-    outputs={"success": NodeScenarioSuccessOutput, "error": NodeScenarioErrorOutput},
-)
-def node_terminate(
-    cfg: NodeScenarioConfig,
-) -> typing.Tuple[
-    str, typing.Union[NodeScenarioSuccessOutput, NodeScenarioErrorOutput]
-]:
-    with kube_helper.setup_kubernetes(None) as cli:
-        ibmcloud = IbmCloud()
-        core_v1 = client.CoreV1Api(cli)
-        node_list = kube_helper.get_node_list(
-            cfg, kube_helper.Actions.TERMINATE, core_v1
-        )
-        node_name_id_list = ibmcloud.list_instances()
-        nodes_terminated = {}
-        for name in node_list:
-            try:
-                for _ in range(cfg.runs):
-                    logging.info(
-                        "Starting node_termination_scenario injection by first stopping the node"
-                    )
-                    instance_id = ibmcloud.find_id_in_list(name, node_name_id_list)
-                    logging.info("Deleting the node with instance ID: %s " % (name))
-                    if instance_id: 
-                        ibmcloud.delete_instance(instance_id)
-                        ibmcloud.wait_until_released(name, cfg.timeout)
-                        nodes_terminated[int(time.time_ns())] = Node(name=name)
-                        logging.info("Node with instance ID: %s has been released" % name)
-                        logging.info("node_terminate_scenario has been successfully injected!")
-                    else: 
-                        logging.error("Failed to find instances that matched the node specifications on ibm cloud in the set region")
-                        return "error", NodeScenarioErrorOutput(
-                            "No matching vpc with node name " + name, kube_helper.Actions.TERMINATE
-                        )
-            except Exception as e:
-                logging.error("Failed to terminate node instance. Test Failed")
-                logging.error("node_terminate_scenario injection failed!")
-                return "error", NodeScenarioErrorOutput(
-                    format_exc(), kube_helper.Actions.TERMINATE
-                )
-
-    return "success", NodeScenarioSuccessOutput(
-        nodes_terminated, kube_helper.Actions.TERMINATE
-    )

kraken/plugins/node_scenarios/kubernetes_functions.py

@@ -1,179 +0,0 @@
-from kubernetes import config, client
-from kubernetes.client.rest import ApiException
-import logging
-import random
-from enum import Enum
-
-
-class Actions(Enum):
-    """
-    This enumeration indicates different kinds of node operations
-    """
-
-    START = "Start"
-    STOP = "Stop"
-    TERMINATE = "Terminate"
-    REBOOT = "Reboot"
-
-
-def setup_kubernetes(kubeconfig_path):
-    """
-    Sets up the Kubernetes client
-    """
-
-    if kubeconfig_path is None:
-        kubeconfig_path = config.KUBE_CONFIG_DEFAULT_LOCATION
-    kubeconfig = config.kube_config.KubeConfigMerger(kubeconfig_path)
-
-    if kubeconfig.config is None:
-        raise Exception(
-            "Invalid kube-config file: %s. " "No configuration found." % kubeconfig_path
-        )
-    loader = config.kube_config.KubeConfigLoader(
-        config_dict=kubeconfig.config,
-    )
-    client_config = client.Configuration()
-    loader.load_and_set(client_config)
-    return client.ApiClient(configuration=client_config)
-
-
-def list_killable_nodes(core_v1, label_selector=None):
-    """
-    Returns a list of nodes that can be stopped/reset/released
-    """
-
-    nodes = []
-    try:
-        if label_selector:
-            ret = core_v1.list_node(pretty=True, label_selector=label_selector)
-        else:
-            ret = core_v1.list_node(pretty=True)
-    except ApiException as e:
-        logging.error("Exception when calling CoreV1Api->list_node: %s\n" % e)
-        raise e
-    for node in ret.items:
-        for cond in node.status.conditions:
-            if str(cond.type) == "Ready" and str(cond.status) == "True":
-                nodes.append(node.metadata.name)
-    return nodes
-
-
-def list_startable_nodes(core_v1, label_selector=None):
-    """
-    Returns a list of nodes that can be started
-    """
-
-    nodes = []
-    try:
-        if label_selector:
-            ret = core_v1.list_node(pretty=True, label_selector=label_selector)
-        else:
-            ret = core_v1.list_node(pretty=True)
-    except ApiException as e:
-        logging.error("Exception when calling CoreV1Api->list_node: %s\n" % e)
-        raise e
-    for node in ret.items:
-        for cond in node.status.conditions:
-            if str(cond.type) == "Ready" and str(cond.status) != "True":
-                nodes.append(node.metadata.name)
-    return nodes
-
-
-def get_node_list(cfg, action, core_v1):
-    """
-    Returns a list of nodes to be used in the node scenarios. The list returned is constructed as follows:
-        - If the key 'name' is present in the node scenario config, the value is extracted and split into
-          a list
-        - Each node in the list is fed to the get_node function which checks if the node is killable or
-          fetches the node using the label selector
-    """
-
-    def get_node(node_name, label_selector, instance_kill_count, action, core_v1):
-        list_nodes_func = (
-            list_startable_nodes if action == Actions.START else list_killable_nodes
-        )
-        if node_name in list_nodes_func(core_v1):
-            return [node_name]
-        elif node_name:
-            logging.info(
-                "Node with provided node_name does not exist or the node might "
-                "be in NotReady state."
-            )
-        nodes = list_nodes_func(core_v1, label_selector)
-        if not nodes:
-            raise Exception("Ready nodes with the provided label selector do not exist")
-        logging.info(
-            "Ready nodes with the label selector %s: %s" % (label_selector, nodes)
-        )
-        number_of_nodes = len(nodes)
-        if instance_kill_count == number_of_nodes:
-            return nodes
-        nodes_to_return = []
-        for i in range(instance_kill_count):
-            node_to_add = nodes[random.randint(0, len(nodes) - 1)]
-            nodes_to_return.append(node_to_add)
-            nodes.remove(node_to_add)
-        return nodes_to_return
-
-    if cfg.name:
-        input_nodes = cfg.name.split(",")
-    else:
-        input_nodes = [""]
-    scenario_nodes = set()
-
-    if cfg.skip_openshift_checks:
-        scenario_nodes = input_nodes
-    else:
-        for node in input_nodes:
-            nodes = get_node(
-                node, cfg.label_selector, cfg.instance_count, action, core_v1
-            )
-            scenario_nodes.update(nodes)
-
-    return list(scenario_nodes)
-
-
-def watch_node_status(node, status, timeout, watch_resource, core_v1):
-    """
-    Monitor the status of a node for change
-    """
-    count = timeout
-    for event in watch_resource.stream(
-        core_v1.list_node,
-        field_selector=f"metadata.name={node}",
-        timeout_seconds=timeout,
-    ):
-        conditions = [
-            status
-            for status in event["object"].status.conditions
-            if status.type == "Ready"
-        ]
-        if conditions[0].status == status:
-            watch_resource.stop()
-            break
-        else:
-            count -= 1
-            logging.info("Status of node " + node + ": " + str(conditions[0].status))
-        if not count:
-            watch_resource.stop()
-
-
-def wait_for_ready_status(node, timeout, watch_resource, core_v1):
-    """
-    Wait until the node status becomes Ready
-    """
-    watch_node_status(node, "True", timeout, watch_resource, core_v1)
-
-
-def wait_for_not_ready_status(node, timeout, watch_resource, core_v1):
-    """
-    Wait until the node status becomes Not Ready
-    """
-    watch_node_status(node, "False", timeout, watch_resource, core_v1)
-
-
-def wait_for_unknown_status(node, timeout, watch_resource, core_v1):
-    """
-    Wait until the node status becomes Unknown
-    """
-    watch_node_status(node, "Unknown", timeout, watch_resource, core_v1)

kraken/plugins/node_scenarios/vmware_plugin.py

@@ -1,761 +0,0 @@
-#!/usr/bin/env python
-import logging
-import random
-import sys
-import time
-import typing
-from dataclasses import dataclass, field
-from os import environ
-from traceback import format_exc
-import requests
-from arcaflow_plugin_sdk import plugin, validation
-from com.vmware.vapi.std.errors_client import (AlreadyInDesiredState,
-                                               NotAllowedInCurrentState)
-from com.vmware.vcenter.vm_client import Power
-from com.vmware.vcenter_client import VM, ResourcePool
-from kubernetes import client, watch
-from vmware.vapi.vsphere.client import create_vsphere_client
-
-from kraken.plugins.node_scenarios import kubernetes_functions as kube_helper
-
-
-class vSphere:
-    def __init__(self, verify=True):
-        """
-        Initialize the vSphere client by using the the env variables:
-            'VSPHERE_IP', 'VSPHERE_USERNAME', 'VSPHERE_PASSWORD'
-        """
-        self.server = environ.get("VSPHERE_IP")
-        self.username = environ.get("VSPHERE_USERNAME")
-        self.password = environ.get("VSPHERE_PASSWORD")
-        session = self.get_unverified_session() if not verify else None
-        self.credentials_present = (
-            True if self.server and self.username and self.password else False
-        )
-        if not self.credentials_present:
-            raise Exception(
-                "Environmental variables "
-                "'VSPHERE_IP', 'VSPHERE_USERNAME', "
-                "'VSPHERE_PASSWORD' are not set"
-            )
-        self.client = create_vsphere_client(
-            server=self.server,
-            username=self.username,
-            password=self.password,
-            session=session,
-        )
-
-    def get_unverified_session(self):
-        """
-        Returns an unverified session object
-        """
-
-        session = requests.session()
-        session.verify = False
-        requests.packages.urllib3.disable_warnings()
-        return session
-
-    def get_vm(self, instance_id):
-        """
-        Returns the VM ID corresponding to the VM Name (instance_id)
-        If there are multiple matches, this only returns the first one
-        """
-
-        names = set([instance_id])
-        vms = self.client.vcenter.VM.list(VM.FilterSpec(names=names))
-
-        if len(vms) == 0:
-            logging.info("VM with name ({}) not found", instance_id)
-            return None
-        vm = vms[0].vm
-
-        return vm
-
-    def release_instances(self, instance_id):
-        """
-        Deletes the VM whose name is given by 'instance_id'
-        """
-
-        vm = self.get_vm(instance_id)
-        if not vm:
-            raise Exception(
-                "VM with the name ({}) does not exist."
-                "Please create the vm first.".format(instance_id)
-            )
-        state = self.client.vcenter.vm.Power.get(vm)
-        if state == Power.Info(state=Power.State.POWERED_ON):
-            self.client.vcenter.vm.Power.stop(vm)
-        elif state == Power.Info(state=Power.State.SUSPENDED):
-            self.client.vcenter.vm.Power.start(vm)
-            self.client.vcenter.vm.Power.stop(vm)
-        self.client.vcenter.VM.delete(vm)
-        logging.info("Deleted VM -- '{}-({})'", instance_id, vm)
-
-    def reboot_instances(self, instance_id):
-        """
-        Reboots the VM whose name is given by 'instance_id'.
-        @Returns: True if successful, or False if the VM is not powered on
-        """
-
-        vm = self.get_vm(instance_id)
-        try:
-            self.client.vcenter.vm.Power.reset(vm)
-            logging.info("Reset VM -- '{}-({})'", instance_id, vm)
-            return True
-        except NotAllowedInCurrentState:
-            logging.info(
-                "VM '{}'-'({})' is not Powered On. Cannot reset it",
-                instance_id,
-                vm
-            )
-            return False
-
-    def stop_instances(self, instance_id):
-        """
-        Stops the VM whose name is given by 'instance_id'.
-        @Returns: True if successful, or False if the VM is already powered off
-        """
-
-        vm = self.get_vm(instance_id)
-        try:
-            self.client.vcenter.vm.Power.stop(vm)
-            logging.info(f"Stopped VM -- '{instance_id}-({vm})'")
-            return True
-        except AlreadyInDesiredState:
-            logging.info(
-                f"VM '{instance_id}'-'({vm})' is already Powered Off"
-            )
-            return False
-
-    def start_instances(self, instance_id):
-        """
-        Stops the VM whose name is given by 'instance_id'.
-        @Returns: True if successful, or False if the VM is already powered on
-        """
-
-        vm = self.get_vm(instance_id)
-        try:
-            self.client.vcenter.vm.Power.start(vm)
-            logging.info(f"Started VM -- '{instance_id}-({vm})'")
-            return True
-        except AlreadyInDesiredState:
-            logging.info(
-                f"VM '{instance_id}'-'({vm})' is already Powered On"
-            )
-            return False
-
-    def list_instances(self, datacenter):
-        """
-        @Returns: a list of VMs present in the datacenter
-        """
-
-        datacenter_filter = self.client.vcenter.Datacenter.FilterSpec(
-            names=set([datacenter])
-        )
-        datacenter_summaries = self.client.vcenter.Datacenter.list(
-            datacenter_filter
-        )
-        try:
-            datacenter_id = datacenter_summaries[0].datacenter
-        except IndexError:
-            logging.error("Datacenter '{}' doesn't exist", datacenter)
-            sys.exit(1)
-
-        vm_filter = self.client.vcenter.VM.FilterSpec(
-            datacenters={datacenter_id}
-        )
-        vm_summaries = self.client.vcenter.VM.list(vm_filter)
-        vm_names = []
-        for vm in vm_summaries:
-            vm_names.append({"vm_name": vm.name, "vm_id": vm.vm})
-        return vm_names
-
-    def get_datacenter_list(self):
-        """
-        Returns a dictionary containing all the datacenter names and IDs
-        """
-
-        datacenter_summaries = self.client.vcenter.Datacenter.list()
-        datacenter_names = [
-            {
-                "datacenter_id": datacenter.datacenter,
-                "datacenter_name": datacenter.name
-            }
-            for datacenter in datacenter_summaries
-        ]
-        return datacenter_names
-
-    def get_datastore_list(self, datacenter=None):
-        """
-        @Returns: a dictionary containing all the datastore names and
-                  IDs belonging to a specific datacenter
-        """
-
-        datastore_filter = self.client.vcenter.Datastore.FilterSpec(
-            datacenters={datacenter}
-        )
-        datastore_summaries = self.client.vcenter.Datastore.list(
-            datastore_filter
-        )
-        datastore_names = []
-        for datastore in datastore_summaries:
-            datastore_names.append(
-                {
-                    "datastore_name": datastore.name,
-                    "datastore_id": datastore.datastore
-                }
-            )
-        return datastore_names
-
-    def get_folder_list(self, datacenter=None):
-        """
-        @Returns: a dictionary containing all the folder names and
-                  IDs belonging to a specific datacenter
-        """
-
-        folder_filter = self.client.vcenter.Folder.FilterSpec(
-            datacenters={datacenter}
-        )
-        folder_summaries = self.client.vcenter.Folder.list(folder_filter)
-        folder_names = []
-        for folder in folder_summaries:
-            folder_names.append(
-                {"folder_name": folder.name, "folder_id": folder.folder}
-            )
-        return folder_names
-
-    def get_resource_pool(self, datacenter, resource_pool_name=None):
-        """
-        Returns the identifier of the resource pool with the given name or the
-        first resource pool in the datacenter if the name is not provided.
-        """
-
-        names = set([resource_pool_name]) if resource_pool_name else None
-        filter_spec = ResourcePool.FilterSpec(
-            datacenters=set([datacenter]), names=names
-        )
-        resource_pool_summaries = self.client.vcenter.ResourcePool.list(
-            filter_spec
-        )
-        if len(resource_pool_summaries) > 0:
-            resource_pool = resource_pool_summaries[0].resource_pool
-            return resource_pool
-        else:
-            logging.error(
-                "ResourcePool not found in Datacenter '{}'",
-                datacenter
-            )
-            return None
-
-    def create_default_vm(self, guest_os="RHEL_7_64", max_attempts=10):
-        """
-        Creates a default VM with 2 GB memory, 1 CPU and 16 GB disk space in a
-        random datacenter. Accepts the guest OS as a parameter. Since the VM
-        placement is random, it might fail due to resource constraints.
-        So, this function tries for upto 'max_attempts' to create the VM
-        """
-
-        def create_vm(vm_name, resource_pool, folder, datastore, guest_os):
-            """
-            Creates a VM and returns its ID and name. Requires the VM name,
-            resource pool name, folder name, datastore and the guest OS
-            """
-
-            placement_spec = VM.PlacementSpec(
-                folder=folder, resource_pool=resource_pool, datastore=datastore
-            )
-            vm_create_spec = VM.CreateSpec(
-                name=vm_name, guest_os=guest_os, placement=placement_spec
-            )
-
-            vm_id = self.client.vcenter.VM.create(vm_create_spec)
-            return vm_id
-
-        for _ in range(max_attempts):
-            try:
-                datacenter_list = self.get_datacenter_list()
-                # random  generator not used for
-                # security/cryptographic purposes in this loop
-                datacenter = random.choice(datacenter_list)  # nosec
-                resource_pool = self.get_resource_pool(
-                    datacenter["datacenter_id"]
-                )
-                folder = random.choice(  # nosec
-                    self.get_folder_list(datacenter["datacenter_id"])
-                )["folder_id"]
-                datastore = random.choice(  # nosec
-                    self.get_datastore_list(datacenter["datacenter_id"])
-                )["datastore_id"]
-                vm_name = "Test-" + str(time.time_ns())
-                return (
-                    create_vm(
-                        vm_name,
-                        resource_pool,
-                        folder,
-                        datastore,
-                        guest_os
-                    ),
-                    vm_name,
-                )
-            except Exception as e:
-                logging.error(
-                    "Default VM could not be created, retrying. "
-                    "Error was: %s",
-                    str(e)
-                )
-        logging.error(
-            "Default VM could not be created in %s attempts. "
-            "Check your VMware resources",
-            max_attempts
-        )
-        return None, None
-
-    def get_vm_status(self, instance_id):
-        """
-        Returns the status of the VM whose name is given by 'instance_id'
-        """
-
-        try:
-            vm = self.get_vm(instance_id)
-            state = self.client.vcenter.vm.Power.get(vm).state
-            logging.info(f"Check instance {instance_id} status")
-            return state
-        except Exception as e:
-            logging.error(
-                f"Failed to get node instance status {instance_id}. Encountered following "
-                f"exception: {str(e)}. "
-            )
-            return None
-
-    def wait_until_released(self, instance_id, timeout):
-        """
-        Waits until the VM is deleted or until the timeout. Returns True if
-        the VM is successfully deleted, else returns False
-        """
-
-        time_counter = 0
-        vm = self.get_vm(instance_id)
-        while vm is not None:
-            vm = self.get_vm(instance_id)
-            logging.info(
-                f"VM {instance_id} is still being deleted, "
-                f"sleeping for 5 seconds"
-            )
-            time.sleep(5)
-            time_counter += 5
-            if time_counter >= timeout:
-                logging.info(
-                    f"VM {instance_id} is still not deleted in allotted time"
-                )
-                return False
-        return True
-
-    def wait_until_running(self, instance_id, timeout):
-        """
-        Waits until the VM switches to POWERED_ON state or until the timeout.
-        Returns True if the VM switches to POWERED_ON, else returns False
-        """
-
-        time_counter = 0
-        status = self.get_vm_status(instance_id)
-        while status != Power.State.POWERED_ON:
-            status = self.get_vm_status(instance_id)
-            logging.info(
-                "VM %s is still not running, "
-                "sleeping for 5 seconds",
-                instance_id
-            )
-            time.sleep(5)
-            time_counter += 5
-            if time_counter >= timeout:
-                logging.info(
-                    f"VM {instance_id} is still not ready in allotted time"
-                )
-                return False
-        return True
-
-    def wait_until_stopped(self, instance_id, timeout):
-        """
-        Waits until the VM switches to POWERED_OFF state or until the timeout.
-        Returns True if the VM switches to POWERED_OFF, else returns False
-        """
-
-        time_counter = 0
-        status = self.get_vm_status(instance_id)
-        while status != Power.State.POWERED_OFF:
-            status = self.get_vm_status(instance_id)
-            logging.info(
-                f"VM {instance_id} is still not running, "
-                f"sleeping for 5 seconds"
-            )
-            time.sleep(5)
-            time_counter += 5
-            if time_counter >= timeout:
-                logging.info(
-                    f"VM {instance_id} is still not ready in allotted time"
-                )
-                return False
-        return True
-
-
-@dataclass
-class Node:
-    name: str
-
-
-@dataclass
-class NodeScenarioSuccessOutput:
-
-    nodes: typing.Dict[int, Node] = field(
-        metadata={
-            "name": "Nodes started/stopped/terminated/rebooted",
-            "description": "Map between timestamps and the pods "
-                           "started/stopped/terminated/rebooted. "
-                           "The timestamp is provided in nanoseconds",
-        }
-    )
-    action: kube_helper.Actions = field(
-        metadata={
-            "name": "The action performed on the node",
-            "description": "The action performed or attempted to be "
-                           "performed on the node. Possible values"
-                           "are : Start, Stop, Terminate, Reboot",
-        }
-    )
-
-
-@dataclass
-class NodeScenarioErrorOutput:
-
-    error: str
-    action: kube_helper.Actions = field(
-        metadata={
-            "name": "The action performed on the node",
-            "description": "The action attempted to be performed on the node. "
-            "Possible values are : Start Stop, Terminate, Reboot",
-        }
-    )
-
-
-@dataclass
-class NodeScenarioConfig:
-
-    name: typing.Annotated[
-        typing.Optional[str],
-        validation.required_if_not("label_selector"),
-        validation.required_if("skip_openshift_checks"),
-    ] = field(
-        default=None,
-        metadata={
-            "name": "Name",
-            "description": "Name(s) for target nodes. "
-                           "Required if label_selector is not set.",
-        },
-    )
-
-    runs: typing.Annotated[typing.Optional[int], validation.min(1)] = field(
-        default=1,
-        metadata={
-            "name": "Number of runs per node",
-            "description": "Number of times to inject each scenario under "
-                           "actions (will perform on same node each time)",
-        },
-    )
-
-    label_selector: typing.Annotated[
-        typing.Optional[str],
-        validation.min(1),
-        validation.required_if_not("name")
-    ] = field(
-        default=None,
-        metadata={
-            "name": "Label selector",
-            "description": "Kubernetes label selector for the target nodes. "
-                           "Required if name is not set.\n"
-            "See https://kubernetes.io/docs/concepts/overview/working-with-objects/labels/ "  # noqa
-            "for details.",
-        },
-    )
-
-    timeout: typing.Annotated[typing.Optional[int], validation.min(1)] = field(
-        default=180,
-        metadata={
-            "name": "Timeout",
-            "description": "Timeout to wait for the target pod(s) "
-                           "to be removed in seconds.",
-        },
-    )
-
-    instance_count: typing.Annotated[
-        typing.Optional[int],
-        validation.min(1)
-    ] = field(
-        default=1,
-        metadata={
-            "name": "Instance Count",
-            "description": "Number of nodes to perform action/select "
-                           "that match the label selector.",
-        },
-    )
-
-    skip_openshift_checks: typing.Optional[bool] = field(
-        default=False,
-        metadata={
-            "name": "Skip Openshift Checks",
-            "description": "Skip checking the status of the openshift nodes.",
-        },
-    )
-
-    verify_session: bool = field(
-        default=True,
-        metadata={
-            "name": "Verify API Session",
-            "description": "Verifies the vSphere client session. "
-                           "It is enabled by default",
-        },
-    )
-
-    kubeconfig_path: typing.Optional[str] = field(
-        default=None,
-        metadata={
-            "name": "Kubeconfig path",
-            "description": "Path to your Kubeconfig file. "
-                           "Defaults to ~/.kube/config.\n"
-            "See https://kubernetes.io/docs/concepts/configuration/organize-cluster-access-kubeconfig/ "  # noqa
-            "for details.",
-        },
-    )
-
-
-@plugin.step(
-    id="vmware-node-start",
-    name="Start the node",
-    description="Start the node(s) by starting the VMware VM "
-                "on which the node is configured",
-    outputs={
-        "success": NodeScenarioSuccessOutput,
-        "error": NodeScenarioErrorOutput
-    },
-)
-def node_start(
-    cfg: NodeScenarioConfig,
-) -> typing.Tuple[
-    str, typing.Union[NodeScenarioSuccessOutput, NodeScenarioErrorOutput]
-]:
-    with kube_helper.setup_kubernetes(None) as cli:
-        vsphere = vSphere(verify=cfg.verify_session)
-        core_v1 = client.CoreV1Api(cli)
-        watch_resource = watch.Watch()
-        node_list = kube_helper.get_node_list(
-            cfg,
-            kube_helper.Actions.START,
-            core_v1
-        )
-        nodes_started = {}
-        for name in node_list:
-            try:
-                for _ in range(cfg.runs):
-                    logging.info("Starting node_start_scenario injection")
-                    logging.info(f"Starting the node {name} ")
-                    vm_started = vsphere.start_instances(name)
-                    if vm_started:
-                        vsphere.wait_until_running(name, cfg.timeout)
-                        if not cfg.skip_openshift_checks:
-                            kube_helper.wait_for_ready_status(
-                                name, cfg.timeout, watch_resource, core_v1
-                            )
-                        nodes_started[int(time.time_ns())] = Node(name=name)
-                    logging.info(
-                        f"Node with instance ID: {name} is in running state"
-                    )
-                    logging.info(
-                        "node_start_scenario has been successfully injected!"
-                    )
-            except Exception as e:
-                logging.error("Failed to start node instance. Test Failed")
-                logging.error(
-                    f"node_start_scenario injection failed! "
-                    f"Error was: {str(e)}"
-                )
-                return "error", NodeScenarioErrorOutput(
-                    format_exc(), kube_helper.Actions.START
-                )
-
-    return "success", NodeScenarioSuccessOutput(
-        nodes_started, kube_helper.Actions.START
-    )
-
-
-@plugin.step(
-    id="vmware-node-stop",
-    name="Stop the node",
-    description="Stop the node(s) by starting the VMware VM "
-                "on which the node is configured",
-    outputs={
-        "success": NodeScenarioSuccessOutput,
-        "error": NodeScenarioErrorOutput
-    },
-)
-def node_stop(
-    cfg: NodeScenarioConfig,
-) -> typing.Tuple[
-    str, typing.Union[NodeScenarioSuccessOutput, NodeScenarioErrorOutput]
-]:
-    with kube_helper.setup_kubernetes(None) as cli:
-        vsphere = vSphere(verify=cfg.verify_session)
-        core_v1 = client.CoreV1Api(cli)
-        watch_resource = watch.Watch()
-        node_list = kube_helper.get_node_list(
-            cfg,
-            kube_helper.Actions.STOP,
-            core_v1
-        )
-        nodes_stopped = {}
-        for name in node_list:
-            try:
-                for _ in range(cfg.runs):
-                    logging.info("Starting node_stop_scenario injection")
-                    logging.info(f"Stopping the node {name} ")
-                    vm_stopped = vsphere.stop_instances(name)
-                    if vm_stopped:
-                        vsphere.wait_until_stopped(name, cfg.timeout)
-                        if not cfg.skip_openshift_checks:
-                            kube_helper.wait_for_ready_status(
-                                name, cfg.timeout, watch_resource, core_v1
-                            )
-                        nodes_stopped[int(time.time_ns())] = Node(name=name)
-                    logging.info(
-                        f"Node with instance ID: {name} is in stopped state"
-                    )
-                    logging.info(
-                        "node_stop_scenario has been successfully injected!"
-                    )
-            except Exception as e:
-                logging.error("Failed to stop node instance. Test Failed")
-                logging.error(
-                    f"node_stop_scenario injection failed! "
-                    f"Error was: {str(e)}"
-                )
-                return "error", NodeScenarioErrorOutput(
-                    format_exc(), kube_helper.Actions.STOP
-                )
-
-        return "success", NodeScenarioSuccessOutput(
-            nodes_stopped, kube_helper.Actions.STOP
-        )
-
-
-@plugin.step(
-    id="vmware-node-reboot",
-    name="Reboot VMware VM",
-    description="Reboot the node(s) by starting the VMware VM "
-                "on which the node is configured",
-    outputs={
-        "success": NodeScenarioSuccessOutput,
-        "error": NodeScenarioErrorOutput
-    },
-)
-def node_reboot(
-    cfg: NodeScenarioConfig,
-) -> typing.Tuple[
-    str, typing.Union[NodeScenarioSuccessOutput, NodeScenarioErrorOutput]
-]:
-    with kube_helper.setup_kubernetes(None) as cli:
-        vsphere = vSphere(verify=cfg.verify_session)
-        core_v1 = client.CoreV1Api(cli)
-        watch_resource = watch.Watch()
-        node_list = kube_helper.get_node_list(
-            cfg,
-            kube_helper.Actions.REBOOT,
-            core_v1
-        )
-        nodes_rebooted = {}
-        for name in node_list:
-            try:
-                for _ in range(cfg.runs):
-                    logging.info("Starting node_reboot_scenario injection")
-                    logging.info(f"Rebooting the node {name} ")
-                    vsphere.reboot_instances(name)
-                    if not cfg.skip_openshift_checks:
-                        kube_helper.wait_for_unknown_status(
-                            name, cfg.timeout, watch_resource, core_v1
-                        )
-                        kube_helper.wait_for_ready_status(
-                            name, cfg.timeout, watch_resource, core_v1
-                        )
-                    nodes_rebooted[int(time.time_ns())] = Node(name=name)
-                    logging.info(
-                        f"Node with instance ID: {name} has rebooted "
-                        "successfully"
-                    )
-                    logging.info(
-                        "node_reboot_scenario has been successfully injected!"
-                    )
-            except Exception as e:
-                logging.error("Failed to reboot node instance. Test Failed")
-                logging.error(
-                    f"node_reboot_scenario injection failed! "
-                    f"Error was: {str(e)}"
-                )
-                return "error", NodeScenarioErrorOutput(
-                    format_exc(), kube_helper.Actions.REBOOT
-                )
-
-    return "success", NodeScenarioSuccessOutput(
-        nodes_rebooted, kube_helper.Actions.REBOOT
-    )
-
-
-@plugin.step(
-    id="vmware-node-terminate",
-    name="Reboot VMware VM",
-    description="Wait for the node to be terminated",
-    outputs={"success": NodeScenarioSuccessOutput, "error": NodeScenarioErrorOutput},
-)
-def node_terminate(
-    cfg: NodeScenarioConfig,
-) -> typing.Tuple[
-    str, typing.Union[NodeScenarioSuccessOutput, NodeScenarioErrorOutput]
-]:
-    with kube_helper.setup_kubernetes(None) as cli:
-        vsphere = vSphere(verify=cfg.verify_session)
-        core_v1 = client.CoreV1Api(cli)
-        node_list = kube_helper.get_node_list(
-            cfg, kube_helper.Actions.TERMINATE, core_v1
-        )
-        nodes_terminated = {}
-        for name in node_list:
-            try:
-                for _ in range(cfg.runs):
-                    logging.info(
-                        "Starting node_termination_scenario injection "
-                        "by first stopping the node"
-                    )
-                    vsphere.stop_instances(name)
-                    vsphere.wait_until_stopped(name, cfg.timeout)
-                    logging.info(
-                        f"Releasing the node with instance ID: {name} "
-                    )
-                    vsphere.release_instances(name)
-                    vsphere.wait_until_released(name, cfg.timeout)
-                    nodes_terminated[int(time.time_ns())] = Node(name=name)
-                    logging.info(
-                        f"Node with instance ID: {name} has been released"
-                    )
-                    logging.info(
-                        "node_terminate_scenario has been "
-                        "successfully injected!"
-                    )
-            except Exception as e:
-                logging.error("Failed to terminate node instance. Test Failed")
-                logging.error(
-                    f"node_terminate_scenario injection failed! "
-                    f"Error was: {str(e)}"
-                )
-                return "error", NodeScenarioErrorOutput(
-                    format_exc(), kube_helper.Actions.TERMINATE
-                )
-
-    return "success", NodeScenarioSuccessOutput(
-        nodes_terminated, kube_helper.Actions.TERMINATE
-    )

kraken/pod_scenarios/setup.py

@@ -1,256 +0,0 @@
-import logging
-import time
-from typing import Any
-
-import yaml
-import sys
-import random
-import arcaflow_plugin_kill_pod
-from krkn_lib.k8s.pods_monitor_pool import PodsMonitorPool
-
-import kraken.cerberus.setup as cerberus
-import kraken.post_actions.actions as post_actions
-from krkn_lib.k8s import KrknKubernetes
-from krkn_lib.telemetry.k8s import KrknTelemetryKubernetes
-from krkn_lib.models.telemetry import ScenarioTelemetry
-from arcaflow_plugin_sdk import serialization
-from krkn_lib.utils.functions import get_yaml_item_value, log_exception
-
-
-# Run pod based scenarios
-def run(kubeconfig_path, scenarios_list, config, failed_post_scenarios, wait_duration):
-    # Loop to run the scenarios starts here
-    for pod_scenario in scenarios_list:
-        if len(pod_scenario) > 1:
-            pre_action_output = post_actions.run(kubeconfig_path, pod_scenario[1])
-        else:
-            pre_action_output = ""
-        try:
-            # capture start time
-            start_time = int(time.time())
-
-            input = serialization.load_from_file(pod_scenario)
-
-            s = arcaflow_plugin_kill_pod.get_schema()
-            input_data: arcaflow_plugin_kill_pod.KillPodConfig = s.unserialize_input("pod", input)
-
-            if kubeconfig_path is not None:
-                input_data.kubeconfig_path = kubeconfig_path
-
-            output_id, output_data = s.call_step("pod", input_data)
-
-            if output_id == "error":
-                data: arcaflow_plugin_kill_pod.PodErrorOutput = output_data
-                logging.error("Failed to run pod scenario: {}".format(data.error))
-            else:
-                data: arcaflow_plugin_kill_pod.PodSuccessOutput = output_data
-                for pod in data.pods:
-                    print("Deleted pod {} in namespace {}\n".format(pod.pod_name, pod.pod_namespace))
-        except Exception as e:
-            logging.error(
-                "Failed to run scenario: %s. Encountered the following " "exception: %s" % (pod_scenario[0], e)
-            )
-            sys.exit(1)
-
-        logging.info("Scenario: %s has been successfully injected!" % (pod_scenario[0]))
-        logging.info("Waiting for the specified duration: %s" % (wait_duration))
-        time.sleep(wait_duration)
-
-        try:
-            failed_post_scenarios = post_actions.check_recovery(
-                kubeconfig_path, pod_scenario, failed_post_scenarios, pre_action_output
-            )
-        except Exception as e:
-            logging.error("Failed to run post action checks: %s" % e)
-            sys.exit(1)
-
-        # capture end time
-        end_time = int(time.time())
-
-        # publish cerberus status
-        cerberus.publish_kraken_status(config, failed_post_scenarios, start_time, end_time)
-    return failed_post_scenarios
-
-
-# krkn_lib
-def container_run(kubeconfig_path,
-                  scenarios_list,
-                  config,
-                  failed_post_scenarios,
-                  wait_duration,
-                  kubecli: KrknKubernetes,
-                  telemetry: KrknTelemetryKubernetes) -> (list[str], list[ScenarioTelemetry]):
-
-    failed_scenarios = []
-    scenario_telemetries: list[ScenarioTelemetry] = []
-    pool = PodsMonitorPool(kubecli)
-
-    for container_scenario_config in scenarios_list:
-        scenario_telemetry = ScenarioTelemetry()
-        scenario_telemetry.scenario = container_scenario_config[0]
-        scenario_telemetry.start_timestamp = time.time()
-        telemetry.set_parameters_base64(scenario_telemetry, container_scenario_config[0])
-        if len(container_scenario_config) > 1:
-            pre_action_output = post_actions.run(kubeconfig_path, container_scenario_config[1])
-        else:
-            pre_action_output = ""
-        with open(container_scenario_config[0], "r") as f:
-            cont_scenario_config = yaml.full_load(f)
-            start_monitoring(kill_scenarios=cont_scenario_config["scenarios"], pool=pool)
-            for cont_scenario in cont_scenario_config["scenarios"]:
-                # capture start time
-                start_time = int(time.time())
-                try:
-                    killed_containers = container_killing_in_pod(cont_scenario, kubecli)
-                    logging.info(f"killed containers: {str(killed_containers)}")
-                    result = pool.join()
-                    if result.error:
-                        raise Exception(f"pods failed to recovery: {result.error}")
-                    scenario_telemetry.affected_pods = result
-                    logging.info("Waiting for the specified duration: %s" % (wait_duration))
-                    time.sleep(wait_duration)
-
-                    # capture end time
-                    end_time = int(time.time())
-
-                    # publish cerberus status
-                    cerberus.publish_kraken_status(config, failed_post_scenarios, start_time, end_time)
-                except (RuntimeError, Exception):
-                    pool.cancel()
-                    failed_scenarios.append(container_scenario_config[0])
-                    log_exception(container_scenario_config[0])
-                    scenario_telemetry.exit_status = 1
-                    # removed_exit
-                    # sys.exit(1)
-                else:
-                    scenario_telemetry.exit_status = 0
-                scenario_telemetry.end_timestamp = time.time()
-                scenario_telemetries.append(scenario_telemetry)
-
-    return failed_scenarios, scenario_telemetries
-
-def start_monitoring(kill_scenarios: list[Any], pool: PodsMonitorPool):
-    for kill_scenario in kill_scenarios:
-        namespace_pattern = f"^{kill_scenario['namespace']}$"
-        label_selector = kill_scenario["label_selector"]
-        recovery_time = kill_scenario["expected_recovery_time"]
-        pool.select_and_monitor_by_namespace_pattern_and_label(
-            namespace_pattern=namespace_pattern,
-            label_selector=label_selector,
-            max_timeout=recovery_time)
-
-
-def container_killing_in_pod(cont_scenario, kubecli: KrknKubernetes):
-    scenario_name = get_yaml_item_value(cont_scenario, "name", "")
-    namespace = get_yaml_item_value(cont_scenario, "namespace", "*")
-    label_selector = get_yaml_item_value(cont_scenario, "label_selector", None)
-    pod_names = get_yaml_item_value(cont_scenario, "pod_names", [])
-    container_name = get_yaml_item_value(cont_scenario, "container_name", "")
-    kill_action = get_yaml_item_value(cont_scenario, "action", 1)
-    kill_count = get_yaml_item_value(cont_scenario, "count", 1)
-    if not isinstance(kill_action, int):
-        logging.error("Please make sure the action parameter defined in the "
-                      "config is an integer")
-        raise RuntimeError()
-    if (kill_action < 1) or (kill_action > 15):
-        logging.error("Only 1-15 kill signals are supported.")
-        raise RuntimeError()
-    kill_action = "kill " + str(kill_action)
-    if type(pod_names) != list:
-        logging.error("Please make sure your pod_names are in a list format")
-        # removed_exit
-        # sys.exit(1)
-        raise RuntimeError()
-    if len(pod_names) == 0:
-        if namespace == "*":
-            # returns double array of pod name and namespace
-            pods = kubecli.get_all_pods(label_selector)
-        else:
-            # Only returns pod names
-            pods = kubecli.list_pods(namespace, label_selector)
-    else:
-        if namespace == "*":
-            logging.error("You must specify the namespace to kill a container in a specific pod")
-            logging.error("Scenario " + scenario_name + " failed")
-            # removed_exit
-            # sys.exit(1)
-            raise RuntimeError()
-        pods = pod_names
-    # get container and pod name
-    container_pod_list = []
-    for pod in pods:
-        if type(pod) == list:
-            pod_output = kubecli.get_pod_info(pod[0], pod[1])
-            container_names = [container.name for container in pod_output.containers]
-
-            container_pod_list.append([pod[0], pod[1], container_names])
-        else:
-            pod_output = kubecli.get_pod_info(pod, namespace)
-            container_names = [container.name for container in pod_output.containers]
-            container_pod_list.append([pod, namespace, container_names])
-
-    killed_count = 0
-    killed_container_list = []
-    while killed_count < kill_count:
-        if len(container_pod_list) == 0:
-            logging.error("Trying to kill more containers than were found, try lowering kill count")
-            logging.error("Scenario " + scenario_name + " failed")
-            # removed_exit
-            # sys.exit(1)
-            raise RuntimeError()
-        selected_container_pod = container_pod_list[random.randint(0, len(container_pod_list) - 1)]
-        for c_name in selected_container_pod[2]:
-            if container_name != "":
-                if c_name == container_name:
-                    killed_container_list.append([selected_container_pod[0], selected_container_pod[1], c_name])
-                    retry_container_killing(kill_action, selected_container_pod[0], selected_container_pod[1], c_name, kubecli)
-                    break
-            else:
-                killed_container_list.append([selected_container_pod[0], selected_container_pod[1], c_name])
-                retry_container_killing(kill_action, selected_container_pod[0], selected_container_pod[1], c_name, kubecli)
-                break
-        container_pod_list.remove(selected_container_pod)
-        killed_count += 1
-    logging.info("Scenario " + scenario_name + " successfully injected")
-    return killed_container_list
-
-
-def retry_container_killing(kill_action, podname, namespace, container_name, kubecli: KrknKubernetes):
-    i = 0
-    while i < 5:
-        logging.info("Killing container %s in pod %s (ns %s)" % (str(container_name), str(podname), str(namespace)))
-        response = kubecli.exec_cmd_in_pod(kill_action, podname, namespace, container_name)
-        i += 1
-        # Blank response means it is done
-        if not response:
-            break
-        elif "unauthorized" in response.lower() or "authorization" in response.lower():
-            time.sleep(2)
-            continue
-        else:
-            logging.warning(response)
-            continue
-
-
-def check_failed_containers(killed_container_list, wait_time, kubecli: KrknKubernetes):
-
-    container_ready = []
-    timer = 0
-    while timer <= wait_time:
-        for killed_container in killed_container_list:
-            # pod namespace contain name
-            pod_output = kubecli.get_pod_info(killed_container[0], killed_container[1])
-
-            for container in pod_output.containers:
-                if container.name == killed_container[2]:
-                    if container.ready:
-                        container_ready.append(killed_container)
-        if len(container_ready) != 0:
-            for item in container_ready:
-                killed_container_list = killed_container_list.remove(item)
-        if killed_container_list is None or len(killed_container_list) == 0:
-            return []
-        timer += 5
-        logging.info("Waiting 5 seconds for containers to become ready")
-        time.sleep(5)
-    return killed_container_list

kraken/post_actions/actions.py

@@ -1,48 +0,0 @@
-import logging
-import kraken.invoke.command as runcommand
-
-
-def run(kubeconfig_path, scenario, pre_action_output=""):
-
-    if scenario.endswith(".yaml") or scenario.endswith(".yml"):
-        logging.error("Powerfulseal support has recently been removed. Please switch to using plugins instead.")
-    elif scenario.endswith(".py"):
-        action_output = runcommand.invoke("python3 " + scenario).strip()
-        if pre_action_output:
-            if pre_action_output == action_output:
-                logging.info(scenario + " post action checks passed")
-            else:
-                logging.info(scenario + " post action response did not match pre check output")
-                logging.info("Pre action output: " + str(pre_action_output) + "\n")
-                logging.info("Post action output: " + str(action_output))
-                return False
-    elif scenario != "":
-        # invoke custom bash script
-        action_output = runcommand.invoke(scenario).strip()
-        if pre_action_output:
-            if pre_action_output == action_output:
-                logging.info(scenario + " post action checks passed")
-            else:
-                logging.info(scenario + " post action response did not match pre check output")
-                return False
-
-    return action_output
-
-
-# Perform the post scenario actions to see if components recovered
-def check_recovery(kubeconfig_path, scenario, failed_post_scenarios, pre_action_output):
-    if failed_post_scenarios:
-        for failed_scenario in failed_post_scenarios:
-            post_action_output = run(kubeconfig_path, failed_scenario[0], failed_scenario[1])
-            if post_action_output is not False:
-                failed_post_scenarios.remove(failed_scenario)
-            else:
-                logging.info("Post action scenario " + str(failed_scenario) + "is still failing")
-
-    # check post actions
-    if len(scenario) > 1:
-        post_action_output = run(kubeconfig_path, scenario[1], pre_action_output)
-        if post_action_output is False:
-            failed_post_scenarios.append([scenario[1], pre_action_output])
-
-    return failed_post_scenarios

kraken/prometheus/client.py

@@ -1,88 +0,0 @@
-import datetime
-import os.path
-from typing import Optional
-
-import urllib3
-import logging
-import sys
-
-import yaml
-from krkn_lib.models.krkn import ChaosRunAlertSummary, ChaosRunAlert
-from krkn_lib.prometheus.krkn_prometheus import KrknPrometheus
-urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
-def alerts(prom_cli: KrknPrometheus, start_time, end_time, alert_profile):
-
-    if alert_profile is None or os.path.exists(alert_profile) is False:
-        logging.error(f"{alert_profile} alert profile does not exist")
-        sys.exit(1)
-
-    with open(alert_profile) as profile:
-        profile_yaml = yaml.safe_load(profile)
-        if not isinstance(profile_yaml, list):
-            logging.error(f"{alert_profile} wrong file format, alert profile must be "
-                          f"a valid yaml file containing a list of items with 3 properties: "
-                          f"expr, description, severity" )
-            sys.exit(1)
-
-        for alert in profile_yaml:
-            if list(alert.keys()).sort() != ["expr", "description", "severity"].sort():
-                logging.error(f"wrong alert {alert}, skipping")
-
-            prom_cli.process_alert(alert,
-                                   datetime.datetime.fromtimestamp(start_time),
-                                   datetime.datetime.fromtimestamp(end_time))
-
-
-def critical_alerts(prom_cli: KrknPrometheus,
-                    summary: ChaosRunAlertSummary,
-                    run_id,
-                    scenario,
-                    start_time,
-                    end_time):
-    summary.scenario = scenario
-    summary.run_id = run_id
-    query = r"""ALERTS{severity="critical"}"""
-    logging.info("Checking for critical alerts firing post chaos")
-
-    during_critical_alerts = prom_cli.process_prom_query_in_range(
-        query,
-        start_time=datetime.datetime.fromtimestamp(start_time),
-        end_time=end_time
-
-    )
-
-    for alert in during_critical_alerts:
-        if "metric" in alert:
-            alertname = alert["metric"]["alertname"] if "alertname" in alert["metric"] else "none"
-            alertstate = alert["metric"]["alertstate"] if "alertstate" in alert["metric"] else "none"
-            namespace = alert["metric"]["namespace"] if "namespace" in alert["metric"] else "none"
-            severity = alert["metric"]["severity"] if "severity" in alert["metric"] else "none"
-            alert = ChaosRunAlert(alertname, alertstate, namespace, severity)
-            summary.chaos_alerts.append(alert)
-
-
-    post_critical_alerts = prom_cli.process_query(
-        query
-    )
-
-    for alert in post_critical_alerts:
-        if "metric" in alert:
-            alertname = alert["metric"]["alertname"] if "alertname" in alert["metric"] else "none"
-            alertstate = alert["metric"]["alertstate"] if "alertstate" in alert["metric"] else "none"
-            namespace = alert["metric"]["namespace"] if "namespace" in alert["metric"] else "none"
-            severity = alert["metric"]["severity"] if "severity" in alert["metric"] else "none"
-            alert = ChaosRunAlert(alertname, alertstate, namespace, severity)
-            summary.post_chaos_alerts.append(alert)
-
-    during_critical_alerts_count = len(during_critical_alerts)
-    post_critical_alerts_count = len(post_critical_alerts)
-    firing_alerts = False
-
-    if during_critical_alerts_count > 0:
-        firing_alerts = True
-
-    if post_critical_alerts_count > 0:
-        firing_alerts = True
-
-    if not firing_alerts:
-        logging.info("No critical alerts are firing!!")

kraken/pvc/pvc_scenario.py

@@ -1,374 +0,0 @@
-import logging
-import random
-import re
-import time
-import yaml
-from ..cerberus import setup as cerberus
-from krkn_lib.k8s import KrknKubernetes
-from krkn_lib.telemetry.k8s import KrknTelemetryKubernetes
-from krkn_lib.models.telemetry import ScenarioTelemetry
-from krkn_lib.utils.functions import get_yaml_item_value, log_exception
-
-
-# krkn_lib
-def run(scenarios_list, config, wait_duration, kubecli: KrknKubernetes, telemetry: KrknTelemetryKubernetes) -> (list[str], list[ScenarioTelemetry]):
-    """
-    Reads the scenario config and creates a temp file to fill up the PVC
-    """
-    failed_post_scenarios = ""
-    scenario_telemetries: list[ScenarioTelemetry] = []
-    failed_scenarios = []
-    for app_config in scenarios_list:
-        scenario_telemetry = ScenarioTelemetry()
-        scenario_telemetry.scenario = app_config
-        scenario_telemetry.start_timestamp = time.time()
-        telemetry.set_parameters_base64(scenario_telemetry, app_config)
-        try:
-            if len(app_config) > 1:
-                with open(app_config, "r") as f:
-                    config_yaml = yaml.full_load(f)
-                    scenario_config = config_yaml["pvc_scenario"]
-                    pvc_name = get_yaml_item_value(
-                        scenario_config, "pvc_name", ""
-                    )
-                    pod_name = get_yaml_item_value(
-                        scenario_config, "pod_name", ""
-                    )
-                    namespace = get_yaml_item_value(
-                        scenario_config, "namespace", ""
-                    )
-                    target_fill_percentage = get_yaml_item_value(
-                        scenario_config, "fill_percentage", "50"
-                    )
-                    duration = get_yaml_item_value(
-                        scenario_config, "duration", 60
-                    )
-
-                    logging.info(
-                        "Input params:\n"
-                        "pvc_name: '%s'\n"
-                        "pod_name: '%s'\n"
-                        "namespace: '%s'\n"
-                        "target_fill_percentage: '%s%%'\nduration: '%ss'"
-                        % (
-                            str(pvc_name),
-                            str(pod_name),
-                            str(namespace),
-                            str(target_fill_percentage),
-                            str(duration)
-                        )
-                    )
-
-                    # Check input params
-                    if namespace is None:
-                        logging.error(
-                            "You must specify the namespace where the PVC is"
-                        )
-                        #sys.exit(1)
-                        raise RuntimeError()
-                    if pvc_name is None and pod_name is None:
-                        logging.error(
-                            "You must specify the pvc_name or the pod_name"
-                        )
-                        # sys.exit(1)
-                        raise RuntimeError()
-                    if pvc_name and pod_name:
-                        logging.info(
-                            "pod_name will be ignored, pod_name used will be "
-                            "a retrieved from the pod used in the pvc_name"
-                        )
-
-                    # Get pod name
-                    if pvc_name:
-                        if pod_name:
-                            logging.info(
-                                "pod_name '%s' will be overridden with one of "
-                                "the pods mounted in the PVC" % (str(pod_name))
-                            )
-                        pvc = kubecli.get_pvc_info(pvc_name, namespace)
-                        try:
-                            # random generator not used for
-                            # security/cryptographic purposes.
-                            pod_name = random.choice(pvc.podNames)  # nosec
-                            logging.info("Pod name: %s" % pod_name)
-                        except Exception:
-                            logging.error(
-                                "Pod associated with %s PVC, on namespace %s, "
-                                "not found" % (str(pvc_name), str(namespace))
-                            )
-                            # sys.exit(1)
-                            raise RuntimeError()
-
-                    # Get volume name
-                    pod = kubecli.get_pod_info(name=pod_name, namespace=namespace)
-
-                    if pod is None:
-                        logging.error(
-                            "Exiting as pod '%s' doesn't exist "
-                            "in namespace '%s'" % (
-                                str(pod_name),
-                                str(namespace)
-                            )
-                        )
-                        # sys.exit(1)
-                        raise RuntimeError()
-
-                    for volume in pod.volumes:
-                        if volume.pvcName is not None:
-                            volume_name = volume.name
-                            pvc_name = volume.pvcName
-                            pvc = kubecli.get_pvc_info(pvc_name, namespace)
-                            break
-                    if 'pvc' not in locals():
-                        logging.error(
-                            "Pod '%s' in namespace '%s' does not use a pvc" % (
-                                str(pod_name),
-                                str(namespace)
-                            )
-                        )
-                        # sys.exit(1)
-                        raise RuntimeError()
-                    logging.info("Volume name: %s" % volume_name)
-                    logging.info("PVC name: %s" % pvc_name)
-
-                    # Get container name and mount path
-                    for container in pod.containers:
-                        for vol in container.volumeMounts:
-                            if vol.name == volume_name:
-                                mount_path = vol.mountPath
-                                container_name = container.name
-                                break
-                    logging.info("Container path: %s" % container_name)
-                    logging.info("Mount path: %s" % mount_path)
-
-                    # Get PVC capacity and used bytes
-                    command = "df %s -B 1024 | sed 1d" % (str(mount_path))
-                    command_output = (
-                        kubecli.exec_cmd_in_pod(
-                            command,
-                            pod_name,
-                            namespace,
-                            container_name
-                        )
-                    ).split()
-                    pvc_used_kb = int(command_output[2])
-                    pvc_capacity_kb = pvc_used_kb + int(command_output[3])
-                    logging.info("PVC used: %s KB" % pvc_used_kb)
-                    logging.info("PVC capacity: %s KB" % pvc_capacity_kb)
-
-                    # Check valid fill percentage
-                    current_fill_percentage = pvc_used_kb / pvc_capacity_kb
-                    if not (
-                        current_fill_percentage * 100
-                        < float(target_fill_percentage)
-                        <= 99
-                    ):
-                        logging.error(
-                            "Target fill percentage (%.2f%%) is lower than "
-                            "current fill percentage (%.2f%%) "
-                            "or higher than 99%%" % (
-                                target_fill_percentage,
-                                current_fill_percentage * 100
-                            )
-                        )
-                        # sys.exit(1)
-                        raise RuntimeError()
-
-                    # Calculate file size
-                    file_size_kb = int(
-                        (
-                            float(
-                                target_fill_percentage / 100
-                            ) * float(pvc_capacity_kb)
-                        ) - float(pvc_used_kb)
-                    )
-                    logging.debug("File size: %s KB" % file_size_kb)
-
-                    file_name = "kraken.tmp"
-                    logging.info(
-                        "Creating %s file, %s KB size, in pod %s at %s (ns %s)"
-                        % (
-                            str(file_name),
-                            str(file_size_kb),
-                            str(pod_name),
-                            str(mount_path),
-                            str(namespace)
-                        )
-                    )
-
-                    start_time = int(time.time())
-                    # Create temp file in the PVC
-                    full_path = "%s/%s" % (str(mount_path), str(file_name))
-                    command = "fallocate -l $((%s*1024)) %s" % (
-                        str(file_size_kb),
-                        str(full_path)
-                    )
-                    logging.debug(
-                        "Create temp file in the PVC command:\n %s" % command
-                    )
-                    kubecli.exec_cmd_in_pod(
-                        command,
-                        pod_name,
-                        namespace,
-                        container_name,
-                    )
-
-                    # Check if file is created
-                    command = "ls -lh %s" % (str(mount_path))
-                    logging.debug("Check file is created command:\n %s" % command)
-                    response = kubecli.exec_cmd_in_pod(
-                        command, pod_name, namespace, container_name
-                    )
-                    logging.info("\n" + str(response))
-                    if str(file_name).lower() in str(response).lower():
-                        logging.info(
-                            "%s file successfully created" % (str(full_path))
-                        )
-                    else:
-                        logging.error(
-                            "Failed to create tmp file with %s size" % (
-                                str(file_size_kb)
-                            )
-                        )
-                        remove_temp_file(
-                            file_name,
-                            full_path,
-                            pod_name,
-                            namespace,
-                            container_name,
-                            mount_path,
-                            file_size_kb,
-                            kubecli
-                        )
-                        # sys.exit(1)
-                        raise RuntimeError()
-
-                # Calculate file size
-                file_size_kb = int(
-                    (
-                        float(
-                            target_fill_percentage / 100
-                        ) * float(pvc_capacity_kb)
-                    ) - float(pvc_used_kb)
-                )
-                logging.debug("File size: %s KB" % file_size_kb)
-
-                file_name = "kraken.tmp"
-                logging.info(
-                    "Creating %s file, %s KB size, in pod %s at %s (ns %s)"
-                    % (
-                        str(file_name),
-                        str(file_size_kb),
-                        str(pod_name),
-                        str(mount_path),
-                        str(namespace)
-                    )
-                )
-
-                start_time = int(time.time())
-                # Create temp file in the PVC
-                full_path = "%s/%s" % (str(mount_path), str(file_name))
-                command = "fallocate -l $((%s*1024)) %s" % (
-                    str(file_size_kb),
-                    str(full_path)
-                )
-                logging.debug(
-                    "Create temp file in the PVC command:\n %s" % command
-                )
-                kubecli.exec_cmd_in_pod(
-                    command, pod_name, namespace, container_name
-                )
-
-                # Check if file is created
-                command = "ls -lh %s" % (str(mount_path))
-                logging.debug("Check file is created command:\n %s" % command)
-                response = kubecli.exec_cmd_in_pod(
-                    command, pod_name, namespace, container_name
-                )
-                logging.info("\n" + str(response))
-                if str(file_name).lower() in str(response).lower():
-                    logging.info(
-                        "Waiting for the specified duration in the config: %ss" % (
-                            duration
-                        )
-                    )
-                    time.sleep(duration)
-                    logging.info("Finish waiting")
-
-                    remove_temp_file(
-                        file_name,
-                        full_path,
-                        pod_name,
-                        namespace,
-                        container_name,
-                        mount_path,
-                        file_size_kb,
-                        kubecli
-                    )
-                    logging.info("End of scenario. Waiting for the specified duration: %s" % (wait_duration))
-                    time.sleep(wait_duration)
-                    
-                    end_time = int(time.time())
-                    cerberus.publish_kraken_status(
-                        config,
-                        failed_post_scenarios,
-                        start_time,
-                        end_time
-                    )
-        except (RuntimeError, Exception):
-            scenario_telemetry.exit_status = 1
-            failed_scenarios.append(app_config)
-            log_exception(app_config)
-        else:
-            scenario_telemetry.exit_status = 0
-        scenario_telemetries.append(scenario_telemetry)
-
-    return failed_scenarios, scenario_telemetries
-
-
-
-
-# krkn_lib
-def remove_temp_file(
-    file_name,
-    full_path,
-    pod_name,
-    namespace,
-    container_name,
-    mount_path,
-    file_size_kb,
-    kubecli: KrknKubernetes
-):
-    command = "rm -f %s" % (str(full_path))
-    logging.debug("Remove temp file from the PVC command:\n %s" % command)
-    kubecli.exec_cmd_in_pod(command, pod_name, namespace, container_name)
-    command = "ls -lh %s" % (str(mount_path))
-    logging.debug("Check temp file is removed command:\n %s" % command)
-    response = kubecli.exec_cmd_in_pod(
-        command,
-        pod_name,
-        namespace,
-        container_name
-    )
-    logging.info("\n" + str(response))
-    if not (str(file_name).lower() in str(response).lower()):
-        logging.info("Temp file successfully removed")
-    else:
-        logging.error(
-            "Failed to delete tmp file with %s size" % (str(file_size_kb))
-        )
-        raise RuntimeError()
-
-
-def toKbytes(value):
-    if not re.match("^[0-9]+[K|M|G|T]i$", value):
-        logging.error(
-            "PVC capacity %s does not match expression "
-            "regexp '^[0-9]+[K|M|G|T]i$'"
-        )
-        raise RuntimeError()
-    unit = {"K": 0, "M": 1, "G": 2, "T": 3}
-    base = 1024 if ("i" in value) else 1000
-    exp = unit[value[-2:-1]]
-    res = int(value[:-2]) * (base**exp)
-    return res

kraken/service_disruption/common_service_disruption_functions.py

@@ -1,325 +0,0 @@
-import time
-import random
-import logging
-import kraken.cerberus.setup as cerberus
-import kraken.post_actions.actions as post_actions
-import yaml
-from krkn_lib.k8s import KrknKubernetes
-from krkn_lib.telemetry.k8s import KrknTelemetryKubernetes
-from krkn_lib.models.telemetry import ScenarioTelemetry
-from krkn_lib.utils.functions import get_yaml_item_value, log_exception
-
-
-def delete_objects(kubecli, namespace):
-
-    services = delete_all_services_namespace(kubecli, namespace)
-    daemonsets = delete_all_daemonset_namespace(kubecli, namespace)
-    statefulsets = delete_all_statefulsets_namespace(kubecli, namespace)
-    replicasets = delete_all_replicaset_namespace(kubecli, namespace)
-    deployments = delete_all_deployment_namespace(kubecli, namespace)
-
-    objects = { "daemonsets": daemonsets,
-                "deployments": deployments,
-                "replicasets": replicasets,
-                "statefulsets": statefulsets,
-                "services": services
-                }
-
-    return objects
-
-
-def get_list_running_pods(kubecli: KrknKubernetes, namespace: str):
-    running_pods = []
-    pods = kubecli.list_pods(namespace)
-    for pod in pods:
-        pod_status = kubecli.get_pod_info(pod, namespace)
-        if pod_status and pod_status.status == "Running":
-            running_pods.append(pod)
-    logging.info('all running pods ' + str(running_pods))
-    return running_pods
-
-
-def delete_all_deployment_namespace(kubecli: KrknKubernetes, namespace: str):
-    """
-    Delete all the deployments in the specified namespace
-
-    :param kubecli: krkn kubernetes python package
-    :param namespace: namespace
-    """
-    try:
-        deployments = kubecli.get_deployment_ns(namespace)
-        for deployment in deployments:
-            logging.info("Deleting deployment" + deployment)
-            kubecli.delete_deployment(deployment, namespace)
-    except Exception as e:
-        logging.error(
-            "Exception when calling delete_all_deployment_namespace: %s\n",
-            str(e),
-        )
-        raise e
-
-    return deployments
-
-
-def delete_all_daemonset_namespace(kubecli: KrknKubernetes, namespace: str):
-    """
-    Delete all the daemonset in the specified namespace
-
-    :param kubecli: krkn kubernetes python package
-    :param namespace: namespace
-    """
-    try:
-        daemonsets = kubecli.get_daemonset(namespace)
-        for daemonset in daemonsets:
-            logging.info("Deleting daemonset" + daemonset)
-            kubecli.delete_daemonset(daemonset, namespace)
-    except Exception as e:
-        logging.error(
-            "Exception when calling delete_all_daemonset_namespace: %s\n",
-            str(e),
-        )
-        raise e
-
-    return daemonsets
-
-
-def delete_all_statefulsets_namespace(kubecli: KrknKubernetes, namespace: str):
-    """
-    Delete all the statefulsets in the specified namespace
-
-
-    :param kubecli: krkn kubernetes python package
-    :param namespace: namespace
-    """
-    try:
-        statefulsets = kubecli.get_all_statefulset(namespace)
-        for statefulset in statefulsets:
-            logging.info("Deleting statefulsets" + statefulsets)
-            kubecli.delete_statefulset(statefulset, namespace)
-    except Exception as e:
-        logging.error(
-            "Exception when calling delete_all_statefulsets_namespace: %s\n",
-            str(e),
-        )
-        raise e
-
-    return statefulsets
-
-
-def delete_all_replicaset_namespace(kubecli: KrknKubernetes, namespace: str):
-    """
-    Delete all the replicasets in the specified namespace
-
-    :param kubecli: krkn kubernetes python package
-    :param namespace: namespace
-    """
-    try:
-        replicasets = kubecli.get_all_replicasets(namespace)
-        for replicaset in replicasets:
-            logging.info("Deleting replicaset" + replicaset)
-            kubecli.delete_replicaset(replicaset, namespace)
-    except Exception as e:
-        logging.error(
-            "Exception when calling delete_all_replicaset_namespace: %s\n",
-            str(e),
-        )
-        raise e
-
-    return replicasets
-
-def delete_all_services_namespace(kubecli: KrknKubernetes, namespace: str):
-    """
-    Delete all the services in the specified namespace
-
-
-    :param kubecli: krkn kubernetes python package
-    :param namespace: namespace
-    """
-    try:
-        services = kubecli.get_all_services(namespace)
-        for service in services:
-            logging.info("Deleting services" + service)
-            kubecli.delete_services(service, namespace)
-    except Exception as e:
-        logging.error(
-            "Exception when calling delete_all_services_namespace: %s\n",
-            str(e),
-        )
-        raise e
-
-    return services
-
-
-# krkn_lib
-def run(
-        scenarios_list,
-        config,
-        wait_duration,
-        failed_post_scenarios,
-        kubeconfig_path,
-        kubecli: KrknKubernetes,
-        telemetry: KrknTelemetryKubernetes
-) -> (list[str], list[ScenarioTelemetry]):
-    scenario_telemetries: list[ScenarioTelemetry] = []
-    failed_scenarios = []
-    for scenario_config in scenarios_list:
-        scenario_telemetry = ScenarioTelemetry()
-        scenario_telemetry.scenario = scenario_config[0]
-        scenario_telemetry.start_timestamp = time.time()
-        telemetry.set_parameters_base64(scenario_telemetry, scenario_config[0])
-        try:
-            if len(scenario_config) > 1:
-                pre_action_output = post_actions.run(kubeconfig_path, scenario_config[1])
-            else:
-                pre_action_output = ""
-            with open(scenario_config[0], "r") as f:
-                scenario_config_yaml = yaml.full_load(f)
-                for scenario in scenario_config_yaml["scenarios"]:
-                    scenario_namespace = get_yaml_item_value(
-                        scenario, "namespace", ""
-                    )
-                    scenario_label = get_yaml_item_value(
-                        scenario, "label_selector", ""
-                    )
-                    if scenario_namespace is not None and scenario_namespace.strip() != "":
-                        if scenario_label is not None and scenario_label.strip() != "":
-                            logging.error("You can only have namespace or label set in your namespace scenario")
-                            logging.error(
-                                "Current scenario config has namespace '%s' and label selector '%s'"
-                                % (scenario_namespace, scenario_label)
-                            )
-                            logging.error(
-                                "Please set either namespace to blank ('') or label_selector to blank ('') to continue"
-                            )
-                            # removed_exit
-                            # sys.exit(1)
-                            raise RuntimeError()
-                    delete_count = get_yaml_item_value(
-                        scenario, "delete_count", 1
-                    )
-                    run_count = get_yaml_item_value(scenario, "runs", 1)
-                    run_sleep = get_yaml_item_value(scenario, "sleep", 10)
-                    wait_time = get_yaml_item_value(scenario, "wait_time", 30)
-
-                    logging.info(str(scenario_namespace) + str(scenario_label) + str(delete_count) + str(run_count) + str(run_sleep) + str(wait_time))
-                    logging.info("done")
-                    start_time = int(time.time())
-                    for i in range(run_count):
-                        killed_namespaces = {}
-                        namespaces = kubecli.check_namespaces([scenario_namespace], scenario_label)
-                        for j in range(delete_count):
-                            if len(namespaces) == 0:
-                                logging.error(
-                                    "Couldn't delete %s namespaces, not enough namespaces matching %s with label %s"
-                                    % (str(run_count), scenario_namespace, str(scenario_label))
-                                )
-                                # removed_exit
-                                # sys.exit(1)
-                                raise RuntimeError()
-                            selected_namespace = namespaces[random.randint(0, len(namespaces) - 1)]
-                            logging.info('Delete objects in selected namespace: ' + selected_namespace )
-                            try:
-                                # delete all pods in namespace
-                                objects = delete_objects(kubecli,selected_namespace)
-                                killed_namespaces[selected_namespace] = objects
-                                logging.info("Deleted all objects in namespace %s was successful" % str(selected_namespace))
-                            except Exception as e:
-                                logging.info("Delete all objects in namespace %s was unsuccessful" % str(selected_namespace))
-                                logging.info("Namespace action error: " + str(e))
-                                raise RuntimeError()
-                            namespaces.remove(selected_namespace)
-                            logging.info("Waiting %s seconds between namespace deletions" % str(run_sleep))
-                            time.sleep(run_sleep)
-
-                        logging.info("Waiting for the specified duration: %s" % wait_duration)
-                        time.sleep(wait_duration)
-                        if len(scenario_config) > 1:
-                            try:
-                                failed_post_scenarios = post_actions.check_recovery(
-                                    kubeconfig_path, scenario_config, failed_post_scenarios, pre_action_output
-                                )
-                            except Exception as e:
-                                logging.error("Failed to run post action checks: %s" % e)
-                                # removed_exit
-                                # sys.exit(1)
-                                raise RuntimeError()
-                        else:
-                            failed_post_scenarios = check_all_running_deployment(killed_namespaces, wait_time, kubecli)
-
-                    end_time = int(time.time())
-                    cerberus.publish_kraken_status(config, failed_post_scenarios, start_time, end_time)
-        except (Exception, RuntimeError):
-            scenario_telemetry.exit_status = 1
-            failed_scenarios.append(scenario_config[0])
-            log_exception(scenario_config[0])
-        else:
-            scenario_telemetry.exit_status = 0
-        scenario_telemetry.end_timestamp = time.time()
-        scenario_telemetries.append(scenario_telemetry)
-    return failed_scenarios, scenario_telemetries
-
-
-def check_all_running_pods(kubecli: KrknKubernetes, namespace_name, wait_time):
-
-    timer = 0
-    while timer < wait_time:
-        pod_list = kubecli.list_pods(namespace_name)
-        pods_running = 0
-        for pod in pod_list:
-            pod_info = kubecli.get_pod_info(pod, namespace_name)
-            if pod_info.status != "Running" and pod_info.status != "Succeeded":
-                logging.info("Pods %s still not running or completed" % pod_info.name)
-                break
-            pods_running += 1
-        if len(pod_list) == pods_running:
-            break
-        timer += 5
-        time.sleep(5)
-        logging.info("Waiting 5 seconds for pods to become active")
-
-# krkn_lib
-def check_all_running_deployment(killed_namespaces, wait_time, kubecli: KrknKubernetes):
-
-    timer = 0
-    while timer < wait_time and killed_namespaces:
-        still_missing_ns = killed_namespaces.copy()
-        for namespace_name, objects in killed_namespaces.items():
-            still_missing_obj = objects.copy()
-            for obj_name, obj_list in objects.items():
-                if "deployments" == obj_name:
-                    deployments = kubecli.get_deployment_ns(namespace_name)
-                    if len(obj_list) == len(deployments):
-                        still_missing_obj.pop(obj_name)
-                elif "replicasets" == obj_name:
-                    replicasets = kubecli.get_all_replicasets(namespace_name)
-                    if len(obj_list) == len(replicasets):
-                        still_missing_obj.pop(obj_name)
-                elif "statefulsets" == obj_name:
-                    statefulsets = kubecli.get_all_statefulset(namespace_name)
-                    if len(obj_list) == len(statefulsets):
-                        still_missing_obj.pop(obj_name)
-                elif "services" == obj_name:
-                    services = kubecli.get_all_services(namespace_name)
-                    if len(obj_list) == len(services):
-                        still_missing_obj.pop(obj_name)
-                elif "daemonsets" == obj_name:
-                    daemonsets = kubecli.get_daemonset(namespace_name)
-                    if len(obj_list) == len(daemonsets):
-                        still_missing_obj.pop(obj_name)
-            logging.info("Still missing objects " + str(still_missing_obj))
-            killed_namespaces[namespace_name] = still_missing_obj.copy()
-            if len(killed_namespaces[namespace_name].keys()) == 0:
-                logging.info("Wait for pods to become running for namespace: " + namespace_name)
-                check_all_running_pods(kubecli, namespace_name, wait_time)
-                still_missing_ns.pop(namespace_name)
-        killed_namespaces = still_missing_ns
-        if len(killed_namespaces.keys()) == 0:
-            return []
-
-        timer += 10
-        time.sleep(10)
-        logging.info("Waiting 10 seconds for objects in namespaces to become active")
-
-    logging.error("Objects are still not ready after waiting " + str(wait_time) + "seconds")
-    logging.error("Non active namespaces " + str(killed_namespaces))
-    return killed_namespaces

kraken/service_hijacking/service_hijacking.py

@@ -1,90 +0,0 @@
-import logging
-import time
-
-import yaml
-from krkn_lib.k8s import KrknKubernetes
-from krkn_lib.models.telemetry import ScenarioTelemetry
-from krkn_lib.telemetry.k8s import KrknTelemetryKubernetes
-
-
-def run(scenarios_list: list[str],wait_duration: int,  krkn_lib: KrknKubernetes, telemetry: KrknTelemetryKubernetes) -> (list[str], list[ScenarioTelemetry]):
-    scenario_telemetries= list[ScenarioTelemetry]()
-    failed_post_scenarios = []
-    for scenario in scenarios_list:
-        scenario_telemetry = ScenarioTelemetry()
-        scenario_telemetry.scenario = scenario
-        scenario_telemetry.start_timestamp = time.time()
-        telemetry.set_parameters_base64(scenario_telemetry, scenario)
-        with open(scenario) as stream:
-            scenario_config = yaml.safe_load(stream)
-
-        service_name = scenario_config['service_name']
-        service_namespace = scenario_config['service_namespace']
-        plan = scenario_config["plan"]
-        image = scenario_config["image"]
-        target_port = scenario_config["service_target_port"]
-        chaos_duration = scenario_config["chaos_duration"]
-
-        logging.info(f"checking service {service_name} in namespace: {service_namespace}")
-        if not krkn_lib.service_exists(service_name, service_namespace):
-            logging.error(f"service: {service_name} not found in namespace: {service_namespace}, failed to run scenario.")
-            fail(scenario_telemetry, scenario_telemetries)
-            failed_post_scenarios.append(scenario)
-            break
-        try:
-            logging.info(f"service: {service_name} found in namespace: {service_namespace}")
-            logging.info(f"creating webservice and initializing test plan...")
-            # both named ports and port numbers can be used
-            if isinstance(target_port, int):
-                logging.info(f"webservice will listen on port {target_port}")
-                webservice = krkn_lib.deploy_service_hijacking(service_namespace, plan, image, port_number=target_port)
-            else:
-                logging.info(f"traffic will be redirected to named port: {target_port}")
-                webservice = krkn_lib.deploy_service_hijacking(service_namespace, plan, image, port_name=target_port)
-            logging.info(f"successfully deployed pod: {webservice.pod_name} "
-                         f"in namespace:{service_namespace} with selector {webservice.selector}!"
-                         )
-            logging.info(f"patching service: {service_name} to hijack traffic towards: {webservice.pod_name}")
-            original_service = krkn_lib.replace_service_selector([webservice.selector], service_name, service_namespace)
-            if original_service is None:
-                logging.error(f"failed to patch service: {service_name}, namespace: {service_namespace} with selector {webservice.selector}")
-                fail(scenario_telemetry, scenario_telemetries)
-                failed_post_scenarios.append(scenario)
-                break
-
-            logging.info(f"service: {service_name} successfully patched!")
-            logging.info(f"original service manifest:\n\n{yaml.dump(original_service)}")
-            logging.info(f"waiting {chaos_duration} before restoring the service")
-            time.sleep(chaos_duration)
-            selectors = ["=".join([key, original_service["spec"]["selector"][key]]) for key in original_service["spec"]["selector"].keys()]
-            logging.info(f"restoring the service selectors {selectors}")
-            original_service = krkn_lib.replace_service_selector(selectors, service_name, service_namespace)
-            if original_service is None:
-                logging.error(f"failed to restore original service: {service_name}, namespace: {service_namespace} with selectors: {selectors}")
-                fail(scenario_telemetry, scenario_telemetries)
-                failed_post_scenarios.append(scenario)
-                break
-            logging.info("selectors successfully restored")
-            logging.info("undeploying service-hijacking resources...")
-            krkn_lib.undeploy_service_hijacking(webservice)
-
-            logging.info("End of scenario. Waiting for the specified duration: %s" % (wait_duration))
-            time.sleep(wait_duration)
-            
-            scenario_telemetry.exit_status = 0
-            scenario_telemetry.end_timestamp = time.time()
-            scenario_telemetries.append(scenario_telemetry)
-            logging.info("success")
-        except Exception as e:
-            logging.error(f"scenario {scenario} failed with exception: {e}")
-            fail(scenario_telemetry, scenario_telemetries)
-            failed_post_scenarios.append(scenario)
-
-    return failed_post_scenarios, scenario_telemetries
-
-
-def fail(scenario_telemetry: ScenarioTelemetry,  scenario_telemetries: list[ScenarioTelemetry]):
-    scenario_telemetry.exit_status = 1
-    scenario_telemetry.end_timestamp = time.time()
-    scenario_telemetries.append(scenario_telemetry)
-

kraken/shut_down/common_shut_down_func.py

@@ -1,191 +0,0 @@
-#!/usr/bin/env python
-import yaml
-import logging
-import time
-from multiprocessing.pool import ThreadPool
-from ..cerberus import setup as cerberus
-from ..post_actions import actions as post_actions
-from ..node_actions.aws_node_scenarios import AWS
-from ..node_actions.openstack_node_scenarios import OPENSTACKCLOUD
-from ..node_actions.az_node_scenarios import Azure
-from ..node_actions.gcp_node_scenarios import GCP
-from krkn_lib.k8s import KrknKubernetes
-from krkn_lib.telemetry.k8s import KrknTelemetryKubernetes
-from krkn_lib.models.telemetry import ScenarioTelemetry
-from krkn_lib.utils.functions import log_exception
-
-def multiprocess_nodes(cloud_object_function, nodes, processes=0):
-    try:
-        # pool object with number of element
-
-        if processes == 0: 
-            pool = ThreadPool(processes=len(nodes))
-        else: 
-            pool = ThreadPool(processes=processes)
-        logging.info("nodes type " + str(type(nodes[0])))
-        if type(nodes[0]) is tuple:
-            node_id = []
-            node_info = []
-            for node in nodes:
-                node_id.append(node[0])
-                node_info.append(node[1])
-            logging.info("node id " + str(node_id))
-            logging.info("node info" + str(node_info))
-            pool.starmap(cloud_object_function, zip(node_info, node_id))
-
-        else:
-            logging.info("pool type" + str(type(nodes)))
-            pool.map(cloud_object_function, nodes)
-        pool.close()
-    except Exception as e:
-        logging.info("Error on pool multiprocessing: " + str(e))
-
-
-# Inject the cluster shut down scenario
-# krkn_lib
-def cluster_shut_down(shut_down_config, kubecli: KrknKubernetes):
-    runs = shut_down_config["runs"]
-    shut_down_duration = shut_down_config["shut_down_duration"]
-    cloud_type = shut_down_config["cloud_type"]
-    timeout = shut_down_config["timeout"]
-    processes = 0
-    if cloud_type.lower() == "aws":
-        cloud_object = AWS()
-    elif cloud_type.lower() == "gcp":
-        cloud_object = GCP()
-        processes = 1
-    elif cloud_type.lower() == "openstack":
-        cloud_object = OPENSTACKCLOUD()
-    elif cloud_type.lower() in ["azure", "az"]:
-        cloud_object = Azure()
-    else:
-        logging.error(
-            "Cloud type %s is not currently supported for cluster shut down" %
-            cloud_type
-        )
-        # removed_exit
-        # sys.exit(1)
-        raise RuntimeError()
-
-    nodes = kubecli.list_nodes()
-    node_id = []
-    for node in nodes:
-        instance_id = cloud_object.get_instance_id(node)
-        node_id.append(instance_id)
-    logging.info("node id list " + str(node_id))
-    for _ in range(runs):
-        logging.info("Starting cluster_shut_down scenario injection")
-        stopping_nodes = set(node_id)
-        multiprocess_nodes(cloud_object.stop_instances, node_id, processes)
-        stopped_nodes = stopping_nodes.copy()
-        while len(stopping_nodes) > 0:
-            for node in stopping_nodes:
-                if type(node) is tuple:
-                    node_status = cloud_object.wait_until_stopped(
-                        node[1],
-                        node[0],
-                        timeout
-                    )
-                else:
-                    node_status = cloud_object.wait_until_stopped(
-                        node,
-                        timeout
-                    )
-
-                # Only want to remove node from stopping list
-                # when fully stopped/no error
-                if node_status:
-                    stopped_nodes.remove(node)
-
-            stopping_nodes = stopped_nodes.copy()
-
-        logging.info(
-            "Shutting down the cluster for the specified duration: %s" %
-            (shut_down_duration)
-        )
-        time.sleep(shut_down_duration)
-        logging.info("Restarting the nodes")
-        restarted_nodes = set(node_id)
-        multiprocess_nodes(cloud_object.start_instances, node_id, processes)
-        logging.info("Wait for each node to be running again")
-        not_running_nodes = restarted_nodes.copy()
-        while len(not_running_nodes) > 0:
-            for node in not_running_nodes:
-                if type(node) is tuple:
-                    node_status = cloud_object.wait_until_running(
-                        node[1],
-                        node[0],
-                        timeout
-                    )
-                else:
-                    node_status = cloud_object.wait_until_running(
-                        node,
-                        timeout
-                    )
-                if node_status:
-                    restarted_nodes.remove(node)
-            not_running_nodes = restarted_nodes.copy()
-        logging.info(
-            "Waiting for 150s to allow cluster component initialization"
-        )
-        time.sleep(150)
-
-        logging.info("Successfully injected cluster_shut_down scenario!")
-
-# krkn_lib
-
-def run(scenarios_list, config, wait_duration, kubecli: KrknKubernetes, telemetry: KrknTelemetryKubernetes) -> (list[str], list[ScenarioTelemetry]):
-    failed_post_scenarios = []
-    failed_scenarios = []
-    scenario_telemetries: list[ScenarioTelemetry] = []
-
-    for shut_down_config in scenarios_list:
-        config_path = shut_down_config
-        pre_action_output = ""
-        if isinstance(shut_down_config, list) :
-            if len(shut_down_config) == 0:
-                raise Exception("bad config file format for shutdown scenario")
-
-            config_path = shut_down_config[0]
-            if len(shut_down_config) > 1:
-                pre_action_output = post_actions.run("", shut_down_config[1])
-
-        scenario_telemetry = ScenarioTelemetry()
-        scenario_telemetry.scenario = config_path
-        scenario_telemetry.start_timestamp = time.time()
-        telemetry.set_parameters_base64(scenario_telemetry, config_path)
-
-        with open(config_path, "r") as f:
-            shut_down_config_yaml = yaml.full_load(f)
-            shut_down_config_scenario = \
-                shut_down_config_yaml["cluster_shut_down_scenario"]
-            start_time = int(time.time())
-            try:
-                cluster_shut_down(shut_down_config_scenario, kubecli)
-                logging.info(
-                    "Waiting for the specified duration: %s" % (wait_duration)
-                )
-                time.sleep(wait_duration)
-                failed_post_scenarios = post_actions.check_recovery(
-                    "", shut_down_config, failed_post_scenarios, pre_action_output
-                )
-                end_time = int(time.time())
-                cerberus.publish_kraken_status(
-                    config,
-                    failed_post_scenarios,
-                    start_time,
-                    end_time
-                )
-
-            except (RuntimeError, Exception):
-                log_exception(config_path)
-                failed_scenarios.append(config_path)
-                scenario_telemetry.exit_status = 1
-            else:
-                scenario_telemetry.exit_status = 0
-
-            scenario_telemetry.end_timestamp = time.time()
-            scenario_telemetries.append(scenario_telemetry)
-
-    return failed_scenarios, scenario_telemetries
-

kraken/syn_flood/__init__.py

@@ -1 +0,0 @@
-from .syn_flood import *

kraken/syn_flood/syn_flood.py

@@ -1,132 +0,0 @@
-import logging
-import os.path
-import time
-from typing import List
-
-import krkn_lib.utils
-import yaml
-from krkn_lib.k8s import KrknKubernetes
-from krkn_lib.models.telemetry import ScenarioTelemetry
-from krkn_lib.telemetry.k8s import KrknTelemetryKubernetes
-
-
-def run(scenarios_list: list[str], krkn_kubernetes: KrknKubernetes, telemetry: KrknTelemetryKubernetes) -> (list[str], list[ScenarioTelemetry]):
-    scenario_telemetries: list[ScenarioTelemetry] = []
-    failed_post_scenarios = []
-    for scenario in scenarios_list:
-        scenario_telemetry = ScenarioTelemetry()
-        scenario_telemetry.scenario = scenario
-        scenario_telemetry.start_timestamp = time.time()
-        telemetry.set_parameters_base64(scenario_telemetry, scenario)
-
-        try:
-            pod_names = []
-            config = parse_config(scenario)
-            if config["target-service-label"]:
-                target_services = krkn_kubernetes.select_service_by_label(config["namespace"], config["target-service-label"])
-            else:
-                target_services = [config["target-service"]]
-
-            for target in target_services:
-                if not krkn_kubernetes.service_exists(target, config["namespace"]):
-                    raise Exception(f"{target} service not found")
-                for i in range(config["number-of-pods"]):
-                    pod_name = "syn-flood-" + krkn_lib.utils.get_random_string(10)
-                    krkn_kubernetes.deploy_syn_flood(pod_name,
-                                                     config["namespace"],
-                                                     config["image"],
-                                                     target,
-                                                     config["target-port"],
-                                                     config["packet-size"],
-                                                     config["window-size"],
-                                                     config["duration"],
-                                                     config["attacker-nodes"]
-                                                     )
-                    pod_names.append(pod_name)
-
-            logging.info("waiting all the attackers to finish:")
-            did_finish = False
-            finished_pods = []
-            while not did_finish:
-                for pod_name in pod_names:
-                    if not krkn_kubernetes.is_pod_running(pod_name, config["namespace"]):
-                        finished_pods.append(pod_name)
-                    if set(pod_names) == set(finished_pods):
-                        did_finish = True
-                time.sleep(1)
-
-        except Exception as e:
-            logging.error(f"Failed to run syn flood scenario {scenario}: {e}")
-            failed_post_scenarios.append(scenario)
-            scenario_telemetry.exit_status = 1
-        else:
-            scenario_telemetry.exit_status = 0
-        scenario_telemetry.end_timestamp = time.time()
-        scenario_telemetries.append(scenario_telemetry)
-    return failed_post_scenarios, scenario_telemetries
-
-def parse_config(scenario_file: str) -> dict[str,any]:
-    if not os.path.exists(scenario_file):
-        raise Exception(f"failed to load scenario file {scenario_file}")
-
-    try:
-        with open(scenario_file) as stream:
-            config = yaml.safe_load(stream)
-    except Exception:
-        raise Exception(f"{scenario_file} is not a valid yaml file")
-
-    missing = []
-    if not check_key_value(config ,"packet-size"):
-        missing.append("packet-size")
-    if not check_key_value(config,"window-size"):
-        missing.append("window-size")
-    if not check_key_value(config, "duration"):
-        missing.append("duration")
-    if not check_key_value(config, "namespace"):
-        missing.append("namespace")
-    if not check_key_value(config, "number-of-pods"):
-        missing.append("number-of-pods")
-    if not check_key_value(config, "target-port"):
-        missing.append("target-port")
-    if not check_key_value(config, "image"):
-        missing.append("image")
-    if "target-service" not in config.keys():
-        missing.append("target-service")
-    if "target-service-label" not in config.keys():
-        missing.append("target-service-label")
-
-
-
-
-    if len(missing) > 0:
-        raise Exception(f"{(',').join(missing)} parameter(s) are missing")
-
-    if not config["target-service"] and not config["target-service-label"]:
-        raise Exception("you have either to set a target service or a label")
-    if config["target-service"] and config["target-service-label"]:
-        raise Exception("you cannot select both target-service and target-service-label")
-
-    if 'attacker-nodes' and not is_node_affinity_correct(config['attacker-nodes']):
-        raise Exception("attacker-nodes format is not correct")
-    return config
-
-def check_key_value(dictionary, key):
-    if key in dictionary:
-        value = dictionary[key]
-        if value is not None and value != '':
-            return True
-    return False
-
-def is_node_affinity_correct(obj) -> bool:
-    if not isinstance(obj, dict):
-        return False
-    for key in obj.keys():
-        if not isinstance(key, str):
-            return False
-        if not isinstance(obj[key], list):
-            return False
-    return True
-
-
-
-

kraken/time_actions/common_time_functions.py

@@ -1,388 +0,0 @@
-import datetime
-import time
-import logging
-import re
-
-import yaml
-import random
-
-from krkn_lib import utils
-from kubernetes.client import ApiException
-
-from ..cerberus import setup as cerberus
-from krkn_lib.k8s import KrknKubernetes
-from krkn_lib.telemetry.k8s import KrknTelemetryKubernetes
-from krkn_lib.models.telemetry import ScenarioTelemetry
-from krkn_lib.utils.functions import get_yaml_item_value, log_exception, get_random_string
-
-
-# krkn_lib
-def pod_exec(pod_name, command, namespace, container_name, kubecli:KrknKubernetes):
-    for i in range(5):
-        response = kubecli.exec_cmd_in_pod(
-            command,
-            pod_name,
-            namespace,
-            container_name
-        )
-        if not response:
-            time.sleep(2)
-            continue
-        elif (
-            "unauthorized" in response.lower() or
-            "authorization" in response.lower()
-        ):
-            time.sleep(2)
-            continue
-        else:
-            break
-    return response
-
-
-# krkn_lib
-def get_container_name(pod_name, namespace, kubecli:KrknKubernetes, container_name=""):
-
-    container_names = kubecli.get_containers_in_pod(pod_name, namespace)
-    if container_name != "":
-        if container_name in container_names:
-            return container_name
-        else:
-            logging.error(
-                "Container name %s not an existing container in pod %s" % (
-                    container_name,
-                    pod_name
-                )
-            )
-    else:
-        container_name = container_names[
-            # random module here is not used for security/cryptographic
-            # purposes
-            random.randint(0, len(container_names) - 1)  # nosec
-        ]
-        return container_name
-
-
-
-def skew_node(node_name: str, action: str, kubecli: KrknKubernetes):
-    pod_namespace = "default"
-    status_pod_name = f"time-skew-pod-{get_random_string(5)}"
-    skew_pod_name = f"time-skew-pod-{get_random_string(5)}"
-    ntp_enabled = True
-    logging.info(f'Creating pod to skew {"time" if action == "skew_time" else "date"} on node {node_name}')
-    status_command = ["timedatectl"]
-    param = "2001-01-01"
-    skew_command = ["timedatectl", "set-time"]
-    if action == "skew_time":
-        skew_command.append("01:01:01")
-    else:
-        skew_command.append("2001-01-01")
-
-    try:
-        status_response = kubecli.exec_command_on_node(node_name, status_command, status_pod_name, pod_namespace)
-        if "Network time on: no" in status_response:
-            ntp_enabled = False
-
-            logging.warning(f'ntp unactive on node {node_name} skewing {"time" if action == "skew_time" else "date"} to {param}')
-            pod_exec(skew_pod_name, skew_command, pod_namespace, None, kubecli)
-        else:
-            logging.info(f'ntp active in cluster node, {"time" if action == "skew_time" else "date"} skewing will have no effect, skipping')
-    except ApiException:
-        pass
-    except Exception as e:
-        logging.error(f"failed to execute skew command in pod: {e}")
-    finally:
-        kubecli.delete_pod(status_pod_name, pod_namespace)
-        if not ntp_enabled :
-            kubecli.delete_pod(skew_pod_name, pod_namespace)
-
-
-
-# krkn_lib
-def skew_time(scenario, kubecli:KrknKubernetes):
-    if scenario["action"] not in ["skew_date","skew_time"]:
-        raise RuntimeError(f'{scenario["action"]} is not a valid time skew action')
-
-    if "node" in scenario["object_type"]:
-        node_names = []
-        if "object_name" in scenario.keys() and scenario["object_name"]:
-            node_names = scenario["object_name"]
-        elif (
-            "label_selector" in scenario.keys() and
-            scenario["label_selector"]
-        ):
-            node_names = kubecli.list_nodes(scenario["label_selector"])
-        for node in node_names:
-            skew_node(node, scenario["action"], kubecli)
-            logging.info("Reset date/time on node " + str(node))
-        return "node", node_names
-
-    elif "pod" in scenario["object_type"]:
-        skew_command = "date --date "
-        if scenario["action"] == "skew_date":
-            skewed_date = "00-01-01"
-            skew_command += skewed_date
-        elif scenario["action"] == "skew_time":
-            skewed_time = "01:01:01"
-            skew_command += skewed_time
-        container_name = get_yaml_item_value(scenario, "container_name", "")
-        pod_names = []
-        if "object_name" in scenario.keys() and scenario["object_name"]:
-            for name in scenario["object_name"]:
-                if "namespace" not in scenario.keys():
-                    logging.error("Need to set namespace when using pod name")
-                    # removed_exit
-                    # sys.exit(1)
-                    raise RuntimeError()
-                pod_names.append([name, scenario["namespace"]])
-        elif "namespace" in scenario.keys() and scenario["namespace"]:
-            if "label_selector" not in scenario.keys():
-                logging.info(
-                    "label_selector key not found, querying for all the pods "
-                    "in namespace: %s" % (scenario["namespace"])
-                )
-                pod_names = kubecli.list_pods(scenario["namespace"])
-            else:
-                logging.info(
-                    "Querying for the pods matching the %s label_selector "
-                    "in namespace %s"
-                    % (scenario["label_selector"], scenario["namespace"])
-                )
-                pod_names = kubecli.list_pods(
-                    scenario["namespace"],
-                    scenario["label_selector"]
-                )
-            counter = 0
-            for pod_name in pod_names:
-                pod_names[counter] = [pod_name, scenario["namespace"]]
-                counter += 1
-        elif (
-            "label_selector" in scenario.keys() and
-            scenario["label_selector"]
-        ):
-            pod_names = kubecli.get_all_pods(scenario["label_selector"])
-
-        if len(pod_names) == 0:
-            logging.info(
-                "Cannot find pods matching the namespace/label_selector, "
-                "please check"
-            )
-            # removed_exit
-            # sys.exit(1)
-            raise RuntimeError()
-        pod_counter = 0
-        for pod in pod_names:
-            if len(pod) > 1:
-                selected_container_name = get_container_name(
-                    pod[0],
-                    pod[1],
-                    kubecli,
-                    container_name,
-
-                )
-                pod_exec_response = pod_exec(
-                    pod[0],
-                    skew_command,
-                    pod[1],
-                    selected_container_name,
-                    kubecli,
-
-                )
-                if pod_exec_response is False:
-                    logging.error(
-                        "Couldn't reset time on container %s "
-                        "in pod %s in namespace %s"
-                        % (selected_container_name, pod[0], pod[1])
-                    )
-                    # removed_exit
-                    # sys.exit(1)
-                    raise RuntimeError()
-                pod_names[pod_counter].append(selected_container_name)
-            else:
-                selected_container_name = get_container_name(
-                    pod,
-                    scenario["namespace"],
-                    kubecli,
-                    container_name
-                )
-                pod_exec_response = pod_exec(
-                    pod,
-                    skew_command,
-                    scenario["namespace"],
-                    selected_container_name,
-                    kubecli
-                )
-                if pod_exec_response is False:
-                    logging.error(
-                        "Couldn't reset time on container "
-                        "%s in pod %s in namespace %s"
-                        % (
-                            selected_container_name,
-                            pod,
-                            scenario["namespace"]
-                        )
-                    )
-                    # removed_exit
-                    # sys.exit(1)
-                    raise RuntimeError()
-                pod_names[pod_counter].append(selected_container_name)
-            logging.info("Reset date/time on pod " + str(pod[0]))
-            pod_counter += 1
-        return "pod", pod_names
-
-
-# From kubectl/oc command get time output
-def parse_string_date(obj_datetime):
-    try:
-        logging.info("Obj_date time " + str(obj_datetime))
-        obj_datetime = re.sub(r"\s\s+", " ", obj_datetime).strip()
-        logging.info("Obj_date sub time " + str(obj_datetime))
-        date_line = re.match(
-            r"[\s\S\n]*\w{3} \w{3} \d{1,} \d{2}:\d{2}:\d{2} \w{3} \d{4}[\s\S\n]*",  # noqa
-            obj_datetime
-        )
-        if date_line is not None:
-            search_response = date_line.group().strip()
-            logging.info("Search response: " + str(search_response))
-            return search_response
-        else:
-            return ""
-    except Exception as e:
-        logging.info(
-            "Exception %s when trying to parse string to date" % str(e)
-        )
-        return ""
-
-
-# Get date and time from string returned from OC
-def string_to_date(obj_datetime):
-    obj_datetime = parse_string_date(obj_datetime)
-    try:
-        date_time_obj = datetime.datetime.strptime(
-            obj_datetime,
-            "%a %b %d %H:%M:%S %Z %Y"
-        )
-        return date_time_obj
-    except Exception:
-        logging.info("Couldn't parse string to datetime object")
-        return datetime.datetime(datetime.MINYEAR, 1, 1)
-
-
-# krkn_lib
-def check_date_time(object_type, names, kubecli:KrknKubernetes):
-    skew_command = "date"
-    not_reset = []
-    max_retries = 30
-    if object_type == "node":
-        for node_name in names:
-            first_date_time = datetime.datetime.utcnow()
-            check_pod_name = f"time-skew-pod-{get_random_string(5)}"
-            node_datetime_string = kubecli.exec_command_on_node(node_name, [skew_command], check_pod_name)
-            node_datetime = string_to_date(node_datetime_string)
-            counter = 0
-            while not (
-                first_date_time < node_datetime < datetime.datetime.utcnow()
-            ):
-                time.sleep(10)
-                logging.info(
-                    "Date/time on node %s still not reset, "
-                    "waiting 10 seconds and retrying" % node_name
-                )
-
-                node_datetime_string = kubecli.exec_cmd_in_pod([skew_command], check_pod_name, "default")
-                node_datetime = string_to_date(node_datetime_string)
-                counter += 1
-                if counter > max_retries:
-                    logging.error(
-                        "Date and time in node %s didn't reset properly" %
-                        node_name
-                    )
-                    not_reset.append(node_name)
-                    break
-            if counter < max_retries:
-                logging.info(
-                    "Date in node " + str(node_name) + " reset properly"
-                )
-            kubecli.delete_pod(check_pod_name)
-
-    elif object_type == "pod":
-        for pod_name in names:
-            first_date_time = datetime.datetime.utcnow()
-            counter = 0
-            pod_datetime_string = pod_exec(
-                pod_name[0],
-                skew_command,
-                pod_name[1],
-                pod_name[2],
-                kubecli
-            )
-            pod_datetime = string_to_date(pod_datetime_string)
-            while not (
-                first_date_time < pod_datetime < datetime.datetime.utcnow()
-            ):
-                time.sleep(10)
-                logging.info(
-                    "Date/time on pod %s still not reset, "
-                    "waiting 10 seconds and retrying" % pod_name[0]
-                )
-                pod_datetime = pod_exec(
-                    pod_name[0],
-                    skew_command,
-                    pod_name[1],
-                    pod_name[2],
-                    kubecli
-                )
-                pod_datetime = string_to_date(pod_datetime)
-                counter += 1
-                if counter > max_retries:
-                    logging.error(
-                        "Date and time in pod %s didn't reset properly" %
-                        pod_name[0]
-                    )
-                    not_reset.append(pod_name[0])
-                    break
-            if counter < max_retries:
-                logging.info(
-                    "Date in pod " + str(pod_name[0]) + " reset properly"
-                )
-    return not_reset
-
-
-# krkn_lib
-def run(scenarios_list, config, wait_duration, kubecli:KrknKubernetes, telemetry: KrknTelemetryKubernetes) -> (list[str], list[ScenarioTelemetry]):
-    failed_scenarios = []
-    scenario_telemetries: list[ScenarioTelemetry] = []
-    for time_scenario_config in scenarios_list:
-        scenario_telemetry = ScenarioTelemetry()
-        scenario_telemetry.scenario = time_scenario_config
-        scenario_telemetry.start_timestamp = time.time()
-        telemetry.set_parameters_base64(scenario_telemetry, time_scenario_config)
-        try:
-            with open(time_scenario_config, "r") as f:
-                scenario_config = yaml.full_load(f)
-                for time_scenario in scenario_config["time_scenarios"]:
-                    start_time = int(time.time())
-                    object_type, object_names = skew_time(time_scenario, kubecli)
-                    not_reset = check_date_time(object_type, object_names, kubecli)
-                    if len(not_reset) > 0:
-                        logging.info("Object times were not reset")
-                    logging.info(
-                        "Waiting for the specified duration: %s" % (wait_duration)
-                    )
-                    time.sleep(wait_duration)
-                    end_time = int(time.time())
-                    cerberus.publish_kraken_status(
-                        config,
-                        not_reset,
-                        start_time,
-                        end_time
-                    )
-        except (RuntimeError, Exception):
-            scenario_telemetry.exit_status = 1
-            log_exception(time_scenario_config)
-            failed_scenarios.append(time_scenario_config)
-        else:
-            scenario_telemetry.exit_status = 0
-        scenario_telemetry.end_timestamp = time.time()
-        scenario_telemetries.append(scenario_telemetry)
-
-    return failed_scenarios, scenario_telemetries

kraken/zone_outage/actions.py

@@ -1,121 +0,0 @@
-import yaml
-import logging
-import time
-from ..node_actions.aws_node_scenarios import AWS
-from ..cerberus import setup as cerberus
-from krkn_lib.telemetry.k8s import KrknTelemetryKubernetes
-from krkn_lib.models.telemetry import ScenarioTelemetry
-from krkn_lib.utils.functions import log_exception
-
-def run(scenarios_list, config, wait_duration, telemetry: KrknTelemetryKubernetes) -> (list[str], list[ScenarioTelemetry]) :
-    """
-    filters the subnet of interest and applies the network acl
-    to create zone outage
-    """
-    failed_post_scenarios = ""
-    scenario_telemetries: list[ScenarioTelemetry] = []
-    failed_scenarios = []
-
-    for zone_outage_config in scenarios_list:
-        scenario_telemetry = ScenarioTelemetry()
-        scenario_telemetry.scenario = zone_outage_config
-        scenario_telemetry.start_timestamp = time.time()
-        telemetry.set_parameters_base64(scenario_telemetry, zone_outage_config)
-        try:
-            if len(zone_outage_config) > 1:
-                with open(zone_outage_config, "r") as f:
-                    zone_outage_config_yaml = yaml.full_load(f)
-                    scenario_config = zone_outage_config_yaml["zone_outage"]
-                    vpc_id = scenario_config["vpc_id"]
-                    subnet_ids = scenario_config["subnet_id"]
-                    duration = scenario_config["duration"]
-                    cloud_type = scenario_config["cloud_type"]
-                    ids = {}
-                    acl_ids_created = []
-
-                    if cloud_type.lower() == "aws":
-                        cloud_object = AWS()
-                    else:
-                        logging.error(
-                            "Cloud type %s is not currently supported for "
-                            "zone outage scenarios"
-                            % cloud_type
-                        )
-                        # removed_exit
-                        # sys.exit(1)
-                        raise RuntimeError()
-
-                    start_time = int(time.time())
-
-                    for subnet_id in subnet_ids:
-                        logging.info("Targeting subnet_id")
-                        network_association_ids = []
-                        associations, original_acl_id = \
-                            cloud_object.describe_network_acls(vpc_id, subnet_id)
-                        for entry in associations:
-                            if entry["SubnetId"] == subnet_id:
-                                network_association_ids.append(
-                                    entry["NetworkAclAssociationId"]
-                                )
-                        logging.info(
-                            "Network association ids associated with "
-                            "the subnet %s: %s"
-                            % (subnet_id, network_association_ids)
-                        )
-                        acl_id = cloud_object.create_default_network_acl(vpc_id)
-                        new_association_id = \
-                            cloud_object.replace_network_acl_association(
-                                network_association_ids[0], acl_id
-                            )
-
-                        # capture the orginal_acl_id, created_acl_id and
-                        # new association_id to use during the recovery
-                        ids[new_association_id] = original_acl_id
-                        acl_ids_created.append(acl_id)
-
-                    # wait for the specified duration
-                    logging.info(
-                        "Waiting for the specified duration "
-                        "in the config: %s" % (duration)
-                    )
-                    time.sleep(duration)
-
-                    # replace the applied acl with the previous acl in use
-                    for new_association_id, original_acl_id in ids.items():
-                        cloud_object.replace_network_acl_association(
-                            new_association_id,
-                            original_acl_id
-                        )
-                    logging.info(
-                        "Wating for 60 seconds to make sure "
-                        "the changes are in place"
-                    )
-                    time.sleep(60)
-
-                    # delete the network acl created for the run
-                    for acl_id in acl_ids_created:
-                        cloud_object.delete_network_acl(acl_id)
-
-                    logging.info(
-                        "End of scenario. "
-                        "Waiting for the specified duration: %s" % (wait_duration)
-                    )
-                    time.sleep(wait_duration)
-
-                    end_time = int(time.time())
-                    cerberus.publish_kraken_status(
-                        config,
-                        failed_post_scenarios,
-                        start_time,
-                        end_time
-                    )
-        except (RuntimeError, Exception):
-            scenario_telemetry.exit_status = 1
-            failed_scenarios.append(zone_outage_config)
-            log_exception(zone_outage_config)
-        else:
-            scenario_telemetry.exit_status = 0
-        scenario_telemetry.end_timestamp = time.time()
-        scenario_telemetries.append(scenario_telemetry)
-    return failed_scenarios, scenario_telemetries
-

krkn/cerberus/__init__.py

@@ -0,0 +1 @@
+from .setup import *