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/build.yml

@@ -1,51 +0,0 @@
-name: Build Krkn
-on:
-  pull_request:
-
-jobs:
-  build:
-    runs-on: ubuntu-latest
-    steps:
-      - name: Check out code
-        uses: actions/checkout@v3
-      - name: Create multi-node KinD cluster
-        uses: redhat-chaos/actions/kind@main
-      - name: Install Python
-        uses: actions/setup-python@v4
-        with:
-          python-version: '3.9'
-          architecture: 'x64'
-      - name: Install environment
-        run: |
-          sudo apt-get install build-essential python3-dev
-          pip install --upgrade pip
-          pip install -r requirements.txt
-      - name: Run unit tests
-        run: python -m coverage run -a -m unittest discover -s tests -v
-      - name: Run CI
-        run: |
-          ./CI/run.sh
-          cat ./CI/results.markdown >> $GITHUB_STEP_SUMMARY
-          echo >> $GITHUB_STEP_SUMMARY
-      - name: Upload CI logs
-        uses: actions/upload-artifact@v3
-        with:
-          name: ci-logs
-          path: CI/out
-          if-no-files-found: error
-      - name: Collect coverage report
-        run: |
-          python -m coverage html
-      - name: Publish coverage report to job summary
-        run: |
-          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
-        with:
-          name: coverage
-          path: htmlcov
-          if-no-files-found: error
-      - name: Check CI results
-        run: grep Fail CI/results.markdown && false || true
-      

.github/workflows/docker-image.yml

@@ -1,8 +1,7 @@
 name: Docker Image CI
 on:
   push:
-    branches:
-      - main
+    tags: ['v[0-9].[0-9]+.[0-9]+']
   pull_request:
 
 jobs:
@@ -12,19 +11,45 @@ jobs:
     - name: Check out code
       uses: actions/checkout@v3
     - name: Build the Docker images
-      run: docker build --no-cache -t quay.io/redhat-chaos/krkn containers/
+      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/}
+        docker tag quay.io/krkn-chaos/krkn quay.io/redhat-chaos/krkn:${GITHUB_REF#refs/tags/}
+
+    - 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: github.ref == 'refs/heads/main' && github.event_name == 'push'
+      if: startsWith(github.ref, 'refs/tags')
+      run: docker login quay.io -u ${QUAY_USER} -p ${QUAY_TOKEN}
+      env:
+        QUAY_USER: ${{ secrets.QUAY_USERNAME }}
+        QUAY_TOKEN: ${{ secrets.QUAY_PASSWORD }}
+    - name: Push the KrknChaos Docker images
+      if: startsWith(github.ref, 'refs/tags')
+      run: |
+        docker push quay.io/krkn-chaos/krkn
+        docker push quay.io/krkn-chaos/krkn:${GITHUB_REF#refs/tags/}
+    - name: Login in to redhat-chaos quay
+      if: startsWith(github.ref, 'refs/tags/v')
       run: docker login quay.io -u ${QUAY_USER} -p ${QUAY_TOKEN}
       env:
         QUAY_USER: ${{ secrets.QUAY_USER_1 }}
         QUAY_TOKEN: ${{ secrets.QUAY_TOKEN_1 }}
-    - name: Push the Docker images
-      if: github.ref == 'refs/heads/main' && github.event_name == 'push'
-      run: docker push quay.io/redhat-chaos/krkn
+    - name: Push the RedHat Chaos Docker images
+      if: startsWith(github.ref, 'refs/tags')
+      run: | 
+        docker push quay.io/redhat-chaos/krkn
+        docker push quay.io/redhat-chaos/krkn:${GITHUB_REF#refs/tags/}
     - name: Rebuild krkn-hub
-      if: github.ref == 'refs/heads/main' && github.event_name == 'push'
+      if: startsWith(github.ref, 'refs/tags')
       uses: redhat-chaos/actions/krkn-hub@main
       with:
-        QUAY_USER: ${{ secrets.QUAY_USER_1 }}
-        QUAY_TOKEN: ${{ secrets.QUAY_TOKEN_1 }}
+        QUAY_USER: ${{ secrets.QUAY_USERNAME }}
+        QUAY_TOKEN: ${{ secrets.QUAY_PASSWORD }}
+        AUTOPUSH: ${{ secrets.AUTOPUSH }}

.github/workflows/functional_tests.yaml

@@ -1,129 +0,0 @@
-on: issue_comment
-
-jobs:
-  check_user:
-    # This job only runs for pull request comments
-    name: Check User Authorization
-    env:
-      USERS: ${{vars.USERS}}
-    if: contains(github.event.comment.body, '/funtest') && contains(github.event.comment.html_url, '/pull/')
-    runs-on: ubuntu-latest
-    steps:
-      - name: Check User
-        run: |
-          for name in `echo $USERS`
-          do 
-            name="${name//$'\r'/}"
-            name="${name//$'\n'/}"
-            if [ $name == "${{github.event.sender.login}}" ]
-            then
-              echo "user ${{github.event.sender.login}} authorized, action started..."
-              exit 0
-            fi
-          done
-          echo "user ${{github.event.sender.login}} is not allowed to run functional tests Action"
-          exit 1
-  pr_commented:
-    # This job only runs for pull request comments containing /functional
-    name: Functional Tests
-    if: contains(github.event.comment.body, '/funtest') && contains(github.event.comment.html_url, '/pull/')
-    runs-on: ubuntu-latest
-    needs:
-      - check_user
-    steps:
-      - name: Check out Kraken
-        uses: actions/checkout@v3
-      - name: Checkout Pull Request
-        run: gh pr checkout ${{ github.event.issue.number }}
-        env:
-          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
-      - name: Install OC CLI
-        uses: redhat-actions/oc-installer@v1
-        with:
-          oc_version: latest
-      - name: Install python 3.9
-        uses: actions/setup-python@v4
-        with:
-          python-version: '3.9'
-      - name: Setup kraken dependencies
-        run:  pip install -r requirements.txt
-      - name: Create Workdir & export the path
-        run: |
-         mkdir workdir
-         echo "WORKDIR_PATH=`pwd`/workdir" >> $GITHUB_ENV
-      - name: Generate run id
-        run: |
-          echo "RUN_ID=`date +%s`" > $GITHUB_ENV
-          echo "Run Id: ${RUN_ID}"
-      - name: Write Pull Secret
-        env:
-          PULLSECRET_BASE64: ${{ secrets.PS_64 }}
-        run: |
-          echo "$PULLSECRET_BASE64" | base64 --decode > pullsecret.txt
-      - name: Write Boot Private Key
-        env:
-          BOOT_KEY: ${{ secrets.CRC_KEY_FILE }}
-        run: |
-          echo -n "$BOOT_KEY" > key.txt
-      - name: Teardown CRC (Post Action)
-        uses: webiny/action-post-run@3.0.0
-        id: post-run-command
-        with:
-          run: podman run --rm -v "${{ github.workspace }}:/workspace:z" -e AWS_ACCESS_KEY_ID="${{ secrets.AWS_ACCESS_KEY_ID }}" -e AWS_SECRET_ACCESS_KEY="${{ secrets.AWS_SECRET_ACCESS_KEY }}" -e AWS_DEFAULT_REGION=us-west-2 quay.io/crcont/crc-cloud:v0.0.2 destroy --project-name "chaos-funtest-${{ env.RUN_ID }}" --backed-url "s3://krkn-crc-state/${{ env.RUN_ID }}" --provider "aws"
-      - name: Create cluster
-        run: |
-          podman run  --name crc-cloud-create --rm \
-          -v ${PWD}:/workspace:z \
-          -e AWS_ACCESS_KEY_ID="${{ secrets.AWS_ACCESS_KEY_ID }}" \
-          -e AWS_SECRET_ACCESS_KEY="${{ secrets.AWS_SECRET_ACCESS_KEY }}" \
-          -e AWS_DEFAULT_REGION="us-west-2" \
-          quay.io/crcont/crc-cloud:v0.0.2 \
-          create aws \
-          --project-name "chaos-funtest-${RUN_ID}" \
-          --backed-url "s3://krkn-crc-state/${RUN_ID}" \
-          --output "/workspace" \
-          --aws-ami-id "ami-00f5eaf98cf42ef9f" \
-          --pullsecret-filepath /workspace/pullsecret.txt \
-          --key-filepath /workspace/key.txt
-
-      - name: Setup kubeconfig
-        continue-on-error: true
-        run: |
-          ssh  -o StrictHostKeyChecking=no -i id_rsa core@$(cat host) "cat /opt/kubeconfig" > kubeconfig
-          sed -i "s/https:\/\/api.crc.testing:6443/https:\/\/`cat host`.nip.io:6443/g" kubeconfig
-          echo "KUBECONFIG=${PWD}/kubeconfig" > $GITHUB_ENV
-
-      - name: Example deployment, GitHub Action env init
-        env:
-          NAMESPACE: test-namespace
-          DEPLOYMENT_NAME: test-nginx
-        run: ./CI/CRC/init_github_action.sh
-      - name: Setup test suite
-        run: |
-          yq -i '.kraken.port="8081"' CI/config/common_test_config.yaml
-          yq -i '.kraken.signal_address="0.0.0.0"' CI/config/common_test_config.yaml
-          yq -i '.kraken.kubeconfig_path="'${KUBECONFIG}'"' CI/config/common_test_config.yaml
-          echo "test_app_outages_gh" > ./CI/tests/my_tests
-          echo "test_container"      >> ./CI/tests/my_tests
-          echo "test_namespace"      >> ./CI/tests/my_tests
-          echo "test_net_chaos"      >> ./CI/tests/my_tests
-          echo "test_time"           >> ./CI/tests/my_tests
-
-      - name: Print affected config files
-        run: |
-          echo -e "## CI/config/common_test_config.yaml\n\n"
-          cat CI/config/common_test_config.yaml
-
-      - name: Running test suite
-        run: |
-          ./CI/run.sh
-      - name: Print test output
-        run:  cat CI/out/*
-      - name: Create coverage report
-        run: |
-          echo "# Test results" > $GITHUB_STEP_SUMMARY
-          cat CI/results.markdown >> $GITHUB_STEP_SUMMARY
-          echo "# Test coverage" >> $GITHUB_STEP_SUMMARY
-          python -m coverage report --format=markdown >> $GITHUB_STEP_SUMMARY
-
-

.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

@@ -0,0 +1,201 @@
+name: Functional & Unit Tests
+on:
+  pull_request:
+  push:
+    branches:
+      - main
+jobs:
+  tests:
+    # Common steps
+    name: Functional & Unit Tests
+    runs-on: ubuntu-latest
+    steps:
+      - name: Check out code
+        uses: actions/checkout@v3
+      - name: Create multi-node KinD cluster
+        uses: redhat-chaos/actions/kind@main
+      - name: Install Helm & add repos
+        run: |
+          curl https://raw.githubusercontent.com/helm/helm/main/scripts/get-helm-3 | bash
+          helm repo add prometheus-community https://prometheus-community.github.io/helm-charts
+          helm repo add stable https://charts.helm.sh/stable
+          helm repo update
+      - name: Deploy prometheus & Port Forwarding
+        run: |
+          kubectl create namespace prometheus-k8s
+          helm install \
+          --wait --timeout 360s \
+          kind-prometheus \
+          prometheus-community/kube-prometheus-stack \
+          --namespace prometheus-k8s \
+          --set prometheus.service.nodePort=30000 \
+          --set prometheus.service.type=NodePort \
+          --set grafana.service.nodePort=31000 \
+          --set grafana.service.type=NodePort \
+          --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.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 }'`
+          kubectl -n prometheus-k8s port-forward $POD_NAME 9090:9090 &
+          sleep 5
+      - name: Install Python
+        uses: actions/setup-python@v4
+        with:
+          python-version: '3.9'
+          architecture: 'x64'
+      - name: Install environment
+        run: |
+          sudo apt-get install build-essential python3-dev
+          pip install --upgrade pip
+          pip install -r requirements.txt
+
+      - name: Deploy test workloads
+        run: |
+          kubectl apply -f CI/templates/outage_pod.yaml
+          kubectl wait --for=condition=ready pod -l scenario=outage --timeout=300s
+          kubectl apply -f CI/templates/container_scenario_pod.yaml
+          kubectl wait --for=condition=ready pod -l scenario=container --timeout=300s
+          kubectl create namespace namespace-scenario
+          kubectl apply -f CI/templates/time_pod.yaml
+          kubectl wait --for=condition=ready pod -l scenario=time-skew --timeout=300s
+          kubectl apply -f CI/templates/service_hijacking.yaml
+          kubectl wait --for=condition=ready pod -l "app.kubernetes.io/name=proxy" --timeout=300s
+      - name: Get Kind nodes
+        run: |
+          kubectl get nodes --show-labels=true
+      # Pull request only steps
+      - name: Run unit tests
+        if: github.event_name == 'pull_request'
+        run: python -m coverage run -a -m unittest discover -s tests -v
+
+      - name: Setup Pull Request Functional Tests
+        if: |
+          github.event_name == 'pull_request'
+        run: |
+            yq -i '.kraken.port="8081"' CI/config/common_test_config.yaml
+            yq -i '.kraken.signal_address="0.0.0.0"' CI/config/common_test_config.yaml
+            yq -i '.kraken.performance_monitoring="localhost:9090"' CI/config/common_test_config.yaml
+            echo "test_service_hijacking" > ./CI/tests/functional_tests
+            echo "test_app_outages" >> ./CI/tests/functional_tests
+            echo "test_container"      >> ./CI/tests/functional_tests
+            echo "test_namespace"      >> ./CI/tests/functional_tests
+            echo "test_net_chaos"      >> ./CI/tests/functional_tests
+            echo "test_time"           >> ./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
+      # for the badge
+      - name: Configure AWS Credentials
+        if: github.ref == 'refs/heads/main' && github.event_name == 'push'
+        uses: aws-actions/configure-aws-credentials@v4
+        with:
+          aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
+          aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
+          aws-region : ${{ secrets.AWS_REGION }}
+      - name: Setup Post Merge Request Functional Tests
+        if: github.ref == 'refs/heads/main' && github.event_name == 'push'
+        run: |
+          yq -i '.kraken.port="8081"' CI/config/common_test_config.yaml
+          yq -i '.kraken.signal_address="0.0.0.0"' CI/config/common_test_config.yaml
+          yq -i '.kraken.performance_monitoring="localhost:9090"' CI/config/common_test_config.yaml
+          yq -i '.telemetry.username="${{secrets.TELEMETRY_USERNAME}}"' CI/config/common_test_config.yaml
+          yq -i '.telemetry.password="${{secrets.TELEMETRY_PASSWORD}}"' CI/config/common_test_config.yaml
+          echo "test_telemetry" > ./CI/tests/functional_tests
+          echo "test_service_hijacking" >> ./CI/tests/functional_tests
+          echo "test_app_outages" >> ./CI/tests/functional_tests
+          echo "test_container"      >> ./CI/tests/functional_tests
+          echo "test_namespace"      >> ./CI/tests/functional_tests
+          echo "test_net_chaos"      >> ./CI/tests/functional_tests
+          echo "test_time"           >> ./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
+        env:
+          AWS_BUCKET: ${{ secrets.AWS_BUCKET }}
+        run: |
+          ./CI/run.sh
+          cat ./CI/results.markdown >> $GITHUB_STEP_SUMMARY
+          echo >> $GITHUB_STEP_SUMMARY
+      - name: Upload CI logs
+        uses: actions/upload-artifact@v4
+        with:
+          name: ci-logs
+          path: CI/out
+          if-no-files-found: error
+      - name: Collect coverage report
+        run: |
+          python -m coverage html
+          python -m coverage json
+      - name: Publish coverage report to job summary
+        run: |
+          pip install html2text
+          html2text --ignore-images --ignore-links -b 0 htmlcov/index.html >> $GITHUB_STEP_SUMMARY
+      - name: Upload coverage data
+        uses: actions/upload-artifact@v4
+        with:
+          name: coverage
+          path: htmlcov
+          if-no-files-found: error
+      - name: Upload json coverage
+        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"
+
+  badge:
+    permissions:
+      contents: write
+    name: Generate Coverage Badge
+    runs-on: ubuntu-latest
+    needs:
+      - tests
+    if: github.ref == 'refs/heads/main' && github.event_name == 'push'
+    steps:
+        - name: Check out doc repo
+          uses: actions/checkout@master
+          with:
+            repository: krkn-chaos/krkn-lib-docs
+            path: krkn-lib-docs
+            ssh-key: ${{ secrets.KRKN_LIB_DOCS_PRIV_KEY }}
+        - name: Download json coverage
+          uses: actions/download-artifact@v4
+          with:
+            name: coverage.json
+        - name: Set up Python
+          uses: actions/setup-python@v4
+          with:
+            python-version: 3.9
+        - name: Copy badge on GitHub Page Repo
+          env:
+            COLOR: yellow
+          run: |
+            # generate coverage badge on previously calculated total coverage
+            # and copy in the docs page
+            export TOTAL=$(python -c "import json;print(json.load(open('coverage.json'))['totals']['percent_covered_display'])")
+            [[ $TOTAL > 40 ]] && COLOR=green
+            echo "TOTAL: $TOTAL"
+            echo "COLOR: $COLOR"
+            curl "https://img.shields.io/badge/coverage-$TOTAL%25-$COLOR" > ./krkn-lib-docs/coverage_badge_krkn.svg
+        - name: Push updated Coverage Badge
+          run: |
+            cd krkn-lib-docs
+            git add .
+            git config user.name "krkn-chaos"
+            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
+      
+      

.gitignore

@@ -16,6 +16,7 @@ __pycache__/*
 *.out
 kube-burner*
 kube_burner*
+recommender_*.json
 
 # Project files
 .ropeproject
@@ -61,7 +62,7 @@ inspect.local.*
 !CI/config/common_test_config.yaml
 CI/out/*
 CI/ci_results
-CI/scenarios/*node.yaml
+CI/legacy/*node.yaml
 CI/results.markdown
 
 #env

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/CRC/deployment.yaml

@@ -1,44 +0,0 @@
-apiVersion: v1
-kind: Namespace
-metadata:
-  name: $NAMESPACE
-
----
-
-apiVersion: v1
-kind: Service
-metadata:
-  name: $DEPLOYMENT_NAME-service
-  namespace: $NAMESPACE
-spec:
-  selector:
-    app: $DEPLOYMENT_NAME
-  ports:
-    - name: http
-      port: 80
-      targetPort: 8080
-  type: ClusterIP
-
---- 
-
-apiVersion: apps/v1
-kind: Deployment
-metadata:
-  namespace: $NAMESPACE
-  name: $DEPLOYMENT_NAME-deployment
-spec:
-  replicas: 3
-  selector:
-    matchLabels:
-      app: $DEPLOYMENT_NAME
-  template:
-    metadata:
-      labels:
-        app: $DEPLOYMENT_NAME
-    spec:
-      containers:
-        - name: $DEPLOYMENT_NAME
-          image: nginxinc/nginx-unprivileged:stable-alpine
-          ports:
-            - name: http
-              containerPort: 8080

CI/CRC/init_github_action.sh

@@ -1,58 +0,0 @@
-#!/bin/bash
-SCRIPT_PATH=./CI/CRC
-DEPLOYMENT_PATH=$SCRIPT_PATH/deployment.yaml
-
-[[ ! -f $DEPLOYMENT_PATH ]] && echo "[ERROR] please run $0 from GitHub action root directory" && exit 1
-[[ -z $DEPLOYMENT_NAME ]] && echo "[ERROR] please set \$DEPLOYMENT_NAME environment variable" && exit 1
-[[ -z $NAMESPACE ]] && echo "[ERROR] please set \$NAMESPACE environment variable" && exit 1
-
-
-OPENSSL=`which openssl 2>/dev/null`
-[[ $? != 0 ]] && echo "[ERROR]: openssl missing, please install it and try again" && exit 1
-OC=`which oc 2>/dev/null`
-[[ $? != 0 ]] && echo "[ERROR]: oc missing, please install it and try again" && exit 1
-SED=`which sed 2>/dev/null`
-[[ $? != 0 ]] && echo "[ERROR]: sed missing, please install it and try again" && exit 1
-JQ=`which jq 2>/dev/null`
-[[ $? != 0 ]] && echo "[ERROR]: jq missing, please install it and try again" && exit 1
-ENVSUBST=`which envsubst 2>/dev/null`
-[[ $? != 0 ]] && echo "[ERROR]: envsubst missing, please install it and try again" && exit 1
-
-
-API_PORT="6443"
-API_ADDRESS="https://api.`cat host`.nip.io:${API_PORT}"
-FQN=$DEPLOYMENT_NAME.apps.$API_ADDRESS
-
-
-echo "[INF] deploying example deployment: $DEPLOYMENT_NAME in namespace: $NAMESPACE"
-$ENVSUBST < $DEPLOYMENT_PATH | $OC apply -f - > /dev/null 2>&1
-
-echo "[INF] creating SSL self-signed certificates for route https://$FQN"
-$OPENSSL genrsa -out servercakey.pem > /dev/null 2>&1
-$OPENSSL req -new -x509 -key servercakey.pem -out serverca.crt -subj "/CN=$FQN/O=Red Hat Inc./C=US" > /dev/null 2>&1
-$OPENSSL genrsa -out server.key > /dev/null 2>&1
-$OPENSSL req -new -key server.key -out server_reqout.txt -subj "/CN=$FQN/O=Red Hat Inc./C=US" > /dev/null 2>&1
-$OPENSSL x509 -req -in server_reqout.txt -days 3650 -sha256 -CAcreateserial -CA serverca.crt -CAkey servercakey.pem -out server.crt > /dev/null 2>&1
-echo "[INF] creating deployment: $DEPLOYMENT_NAME public route: https://$FQN"
-$OC create route --namespace $NAMESPACE  edge --service=$DEPLOYMENT_NAME-service --cert=server.crt --key=server.key --ca-cert=serverca.crt --hostname="$FQN" > /dev/null 2>&1
-
-
-echo "[INF] setting github action environment variables"
-
-NODE_NAME="`$OC get nodes  -o json | $JQ -r '.items[0].metadata.name'`"
-COVERAGE_FILE="`pwd`/coverage.md"
-echo "DEPLOYMENT_NAME=$DEPLOYMENT_NAME" >> $GITHUB_ENV
-echo "DEPLOYMENT_FQN=$FQN" >> $GITHUB_ENV
-echo "API_ADDRESS=$API_ADDRESS" >> $GITHUB_ENV
-echo "API_PORT=$API_PORT" >> $GITHUB_ENV
-echo "NODE_NAME=$NODE_NAME" >> $GITHUB_ENV
-echo "NAMESPACE=$NAMESPACE" >> $GITHUB_ENV
-echo "COVERAGE_FILE=$COVERAGE_FILE" >> $GITHUB_ENV
-
-echo "[INF] deployment fully qualified name will be available in \${{ env.DEPLOYMENT_NAME }} with value $DEPLOYMENT_NAME"
-echo "[INF] deployment name will be available in \${{ env.DEPLOYMENT_FQN }} with value $FQN"
-echo "[INF] OCP API address will be available in \${{ env.API_ADDRESS }} with value $API_ADDRESS"
-echo "[INF] OCP API port will be available in \${{ env.API_PORT }} with value $API_PORT"
-echo "[INF] OCP node name will be available in \${{ env.NODE_NAME }} with value $NODE_NAME"
-echo "[INF] coverage file will ve available in \${{ env.COVERAGE_FILE }} with value $COVERAGE_FILE"
-

CI/README.md

@@ -1,7 +1,7 @@
 ## CI Tests
 
 ### First steps
-Edit [my_tests](tests/my_tests) with tests you want to run
+Edit [functional_tests](tests/functional_tests) with tests you want to run
 
 ### How to run
 ```./CI/run.sh```
@@ -11,7 +11,7 @@ This will run kraken using python, make sure python3 is set up and configured pr
 
 ### Adding a test case
 
-1. Add in simple scenario yaml file to execute under [../CI/scenarios/](scenarios)
+1. Add in simple scenario yaml file to execute under [../CI/scenarios/](legacy)
 
 2. Copy [test_application_outages.sh](tests/test_app_outages.sh) for example on how to get started
 
@@ -27,7 +27,7 @@ This will run kraken using python, make sure python3 is set up and configured pr
 
     e. 15: Make sure name of config in line 14 matches what you pass on this line
 
-4. Add test name to [my_tests](../CI/tests/my_tests) file
+4. Add test name to [functional_tests](../CI/tests/functional_tests) file
 
     a. This will be the name of the file without ".sh"
 

CI/config/common_test_config.yaml

@@ -1,5 +1,5 @@
 kraken:
-    distribution: openshift                                # Distribution can be kubernetes or openshift.
+    distribution: kubernetes                                # Distribution can be kubernetes or openshift.
     kubeconfig_path: ~/.kube/config                        # Path to kubeconfig.
     exit_on_failure: False                                 # Exit when a post action scenario fails.
     litmus_version: v1.13.6                                # Litmus version to install.
@@ -29,9 +29,12 @@ tunings:
     daemon_mode: False                                     # Iterations are set to infinity which means that the kraken will cause chaos forever.
 telemetry:
     enabled: False                                           # enable/disables the telemetry collection feature
-    api_url: https://ulnmf9xv7j.execute-api.us-west-2.amazonaws.com/production #telemetry service endpoint
-    username: username                                      # telemetry service username
-    password: password                                      # telemetry service password
+    api_url: https://yvnn4rfoi7.execute-api.us-west-2.amazonaws.com/test #telemetry service endpoint
+    username: $TELEMETRY_USERNAME                                      # telemetry service username
+    password: $TELEMETRY_PASSWORD                                      # telemetry service password
+    prometheus_namespace: 'prometheus-k8s'                                # prometheus namespace
+    prometheus_pod_name: 'prometheus-kind-prometheus-kube-prome-prometheus-0'                                 # prometheus pod_name
+    prometheus_container_name: 'prometheus'
     prometheus_backup: True                                 # enables/disables prometheus data collection
     full_prometheus_backup: False                           # if is set to False only the /prometheus/wal folder will be downloaded.
     backup_threads: 5                                       # number of telemetry download/upload threads
@@ -39,3 +42,31 @@ telemetry:
     max_retries: 0                                          # maximum number of upload retries (if 0 will retry forever)
     run_tag: ''                                             # if set, this will be appended to the run folder in the bucket (useful to group the runs)
     archive_size: 10000                                     # the size of the prometheus data archive size in KB. The lower the size of archive is
+    logs_backup: True
+    logs_filter_patterns:
+        - "(\\w{3}\\s\\d{1,2}\\s\\d{2}:\\d{2}:\\d{2}\\.\\d+).+"         # Sep 9 11:20:36.123425532
+        - "kinit (\\d+/\\d+/\\d+\\s\\d{2}:\\d{2}:\\d{2})\\s+"          # kinit 2023/09/15 11:20:36 log
+        - "(\\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
+    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/run.sh

@@ -1,15 +1,14 @@
 #!/bin/bash
-set -x
 MAX_RETRIES=60
 
-OC=`which oc 2>/dev/null`
-[[ $? != 0 ]] && echo "[ERROR]: oc missing, please install it and try again" && exit 1
+KUBECTL=`which kubectl 2>/dev/null`
+[[ $? != 0 ]] && echo "[ERROR]: kubectl missing, please install it and try again" && exit 1
 
 wait_cluster_become_ready() {
   COUNT=1
-  until `$OC get namespace > /dev/null 2>&1`
+  until `$KUBECTL get namespace > /dev/null 2>&1`
   do
-    echo "[INF] waiting OpenShift to become ready, after $COUNT check"
+    echo "[INF] waiting Kubernetes to become ready, after $COUNT check"
     sleep 3
     [[ $COUNT == $MAX_RETRIES ]] && echo "[ERR] max retries exceeded, failing" && exit 1
     ((COUNT++))
@@ -18,9 +17,9 @@ wait_cluster_become_ready() {
 
 
 
-ci_tests_loc="CI/tests/my_tests"
+ci_tests_loc="CI/tests/functional_tests"
 
-echo "running test suit consisting of ${ci_tests}"
+echo -e "********* Running Functional Tests Suite *********\n\n"
 
 rm -rf CI/out
 
@@ -37,9 +36,32 @@ echo 'Test                   | Result | Duration' >> $results
 echo '-----------------------|--------|---------' >> $results
 
 # Run each test
-for test_name in `cat CI/tests/my_tests`
+failed_tests=()
+for test_name in `cat CI/tests/functional_tests`
 do
-  wait_cluster_become_ready
-  ./CI/run_test.sh $test_name $results
+  #wait_cluster_become_ready
+  return_value=`./CI/run_test.sh $test_name $results`
+  if [[ $return_value == 1 ]]
+  then
+    echo "Failed"
+    failed_tests+=("$test_name")
+  fi
   wait_cluster_become_ready
 done
+
+
+if (( ${#failed_tests[@]}>0 ))
+then
+  echo -e "\n\n======================================================================"
+  echo -e "\n     FUNCTIONAL TESTS FAILED  ${failed_tests[*]} ABORTING"
+  echo -e "\n======================================================================\n\n"
+
+  for test in "${failed_tests[@]}"
+  do
+    echo -e "\n********** $test KRKN RUN OUTPUT **********\n"
+    cat "CI/out/$test.out"
+    echo -e "\n********************************************\n\n\n\n"
+  done
+
+  exit 1
+fi

CI/run_test.sh

@@ -1,5 +1,4 @@
 #!/bin/bash
-set -x
 readonly SECONDS_PER_HOUR=3600
 readonly SECONDS_PER_MINUTE=60
 function get_time_format() {
@@ -14,9 +13,7 @@ ci_test=`echo $1`
 
 results_file=$2
 
-echo -e "\n======================================================================"
-echo -e "     CI test for ${ci_test}                    "
-echo -e "======================================================================\n"
+echo -e "test: ${ci_test}" >&2
 
 ci_results="CI/out/$ci_test.out"
 # Test ci
@@ -28,13 +25,16 @@ then
   # if the test passes update the results and complete
   duration=$SECONDS
   duration=$(get_time_format $duration)
-  echo "$ci_test: Successful"
+  echo -e  "> $ci_test: Successful\n" >&2
   echo "$ci_test | Pass | $duration" >> $results_file
   count=$retries
+  # return value for run.sh
+  echo 0
 else
   duration=$SECONDS
   duration=$(get_time_format $duration)
-  echo "$ci_test: Failed"
+  echo -e "> $ci_test: Failed\n" >&2
   echo "$ci_test | Fail | $duration" >> $results_file
-  echo "Logs for "$ci_test
+  # return value for run.sh
+  echo 1
 fi

CI/scenarios/app_outage.yaml

@@ -1,5 +0,0 @@
-application_outage:                                  # Scenario to create an outage of an application by blocking traffic
-  duration: 10                                      # Duration in seconds after which the routes will be accessible
-  namespace: openshift-monitoring            # Namespace to target - all application routes will go inaccessible if pod selector is empty
-  pod_selector: {}                            # Pods to target
-  block: [Ingress, Egress]                           # It can be Ingress or Egress or Ingress, Egress

CI/scenarios/container_scenario.yml

@@ -1,8 +0,0 @@
-scenarios:
-- name: "kill machine config container"
-  namespace: "openshift-machine-config-operator"
-  label_selector: "k8s-app=machine-config-server"
-  container_name: "hello-openshift"
-  action: "kill 1"
-  count: 1
-  retry_wait: 60

CI/scenarios/network_chaos.yaml

@@ -1,6 +0,0 @@
-network_chaos:                   # Scenario to create an outage by simulating random variations in the network.
-  duration: 10                   # seconds
-  instance_count: 1
-  execution: serial
-  egress:
-    bandwidth: 100mbit

CI/scenarios/network_diagnostics_namespace.yaml

@@ -1,7 +0,0 @@
-scenarios:
-  - action: delete
-    namespace: "^$openshift-network-diagnostics$"
-    label_selector:
-    runs: 1
-    sleep: 15
-    wait_time: 30

CI/scenarios/time_scenarios.yml

@@ -1,5 +0,0 @@
-time_scenarios:
-- action: skew_time
-  object_type: pod
-  label_selector: k8s-app=etcd
-  container_name: ""

CI/templates/container_scenario_pod.yaml

@@ -0,0 +1,16 @@
+apiVersion: v1
+kind: Pod
+metadata:
+  name: container
+  labels:
+    scenario: container
+spec:
+  hostNetwork: true
+  containers:
+  - name: fedtools
+    image: docker.io/fedora/tools
+    command:
+    - /bin/sh
+    - -c
+    - |
+      sleep infinity

CI/templates/outage_pod.yaml

@@ -0,0 +1,16 @@
+apiVersion: v1
+kind: Pod
+metadata:
+  name: outage
+  labels:
+    scenario: outage
+spec:
+  hostNetwork: true
+  containers:
+  - name: fedtools
+    image: docker.io/fedora/tools
+    command:
+    - /bin/sh
+    - -c
+    - |
+      sleep infinity

CI/templates/service_hijacking.yaml

@@ -0,0 +1,29 @@
+apiVersion: v1
+kind: Pod
+metadata:
+  name: nginx
+  labels:
+    app.kubernetes.io/name: proxy
+spec:
+  containers:
+  - name: nginx
+    image: nginx:stable
+    ports:
+      - containerPort: 80
+        name: http-web-svc
+
+---
+apiVersion: v1
+kind: Service
+metadata:
+  name: nginx-service
+spec:
+  selector:
+    app.kubernetes.io/name: proxy
+  type: NodePort
+  ports:
+  - name: name-of-service-port
+    protocol: TCP
+    port: 80
+    targetPort: http-web-svc
+    nodePort: 30036

CI/templates/time_pod.yaml

@@ -0,0 +1,16 @@
+apiVersion: v1
+kind: Pod
+metadata:
+  name: time-skew
+  labels:
+    scenario: time-skew
+spec:
+  hostNetwork: true
+  containers:
+  - name: fedtools
+    image: docker.io/fedora/tools
+    command:
+    - /bin/sh
+    - -c
+    - |
+      sleep infinity

CI/tests/common.sh

@@ -1,18 +1,26 @@
 ERRORED=false
 
 function finish {
-    if [ $? -eq 1 ] && [ $ERRORED != "true" ]
+    if [ $? != 0 ] && [ $ERRORED != "true" ]
     then
         error
     fi
 }
 
 function error {
-    echo "Error caught."
-    ERRORED=true
+    exit_code=$?
+    if [ $exit_code == 1 ]
+    then
+      echo "Error caught."
+      ERRORED=true
+    elif [ $exit_code == 2 ]
+    then
+      echo "Run with exit code 2 detected, it is expected, wrapping the exit code with 0 to avoid pipeline failure"
+      exit 0
+    fi
 }
 
 function get_node {
-  worker_node=$(oc get nodes --no-headers | grep worker | head -n 1)
+  worker_node=$(kubectl get nodes --no-headers | grep worker | head -n 1)
   export WORKER_NODE=$worker_node
 }

CI/tests/functional_tests

@@ -0,0 +1 @@
+

CI/tests/my_tests

@@ -1 +0,0 @@
-test_net_chaos

CI/tests/test_app_outages.sh

@@ -7,9 +7,11 @@ trap finish EXIT
 
 
 function functional_test_app_outage {
-
-  export scenario_type="application_outages"
-  export scenario_file="CI/scenarios/app_outage.yaml"
+  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_scenarios"
+  export scenario_file="scenarios/openshift/app_outage.yaml"
   export post_config=""
   envsubst < CI/config/common_test_config.yaml > CI/config/app_outage.yaml
   python3 -m coverage run -a run_kraken.py -c CI/config/app_outage.yaml

CI/tests/test_app_outages_gh.sh

@@ -1,21 +0,0 @@
-set -xeEo pipefail
-
-source CI/tests/common.sh
-
-trap error ERR
-trap finish EXIT
-
-
-function functional_test_app_outage {
-  [ -z $DEPLOYMENT_NAME ] && echo "[ERR] DEPLOYMENT_NAME variable not set, failing." && exit 1
-  yq -i '.application_outage.pod_selector={"app":"'$DEPLOYMENT_NAME'"}' CI/scenarios/app_outage.yaml
-  yq -i '.application_outage.namespace="'$NAMESPACE'"' CI/scenarios/app_outage.yaml
-  export scenario_type="application_outages"
-  export scenario_file="CI/scenarios/app_outage.yaml"
-  export post_config=""
-  envsubst < CI/config/common_test_config.yaml > CI/config/app_outage.yaml
-  python3 -m coverage run -a run_kraken.py -c CI/config/app_outage.yaml
-  echo "App outage scenario test: Success"
-}
-
-functional_test_app_outage

CI/tests/test_container.sh

@@ -8,9 +8,11 @@ trap finish EXIT
 pod_file="CI/scenarios/hello_pod.yaml"
 
 function functional_test_container_crash {
-
+  yq -i '.scenarios[0].namespace="default"' scenarios/openshift/container_etcd.yml
+  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="- CI/scenarios/container_scenario.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

@@ -6,13 +6,14 @@ trap error ERR
 trap finish EXIT
 
 function funtional_test_namespace_deletion {
-  export scenario_type="namespace_scenarios"
-  export scenario_file="-  CI/scenarios/network_diagnostics_namespace.yaml"
+  export scenario_type="service_disruption_scenarios"
+  export scenario_file="scenarios/openshift/ingress_namespace.yaml"
   export post_config=""
-  yq '.scenarios.[0].namespace="^openshift-network-diagnostics$"' -i CI/scenarios/network_diagnostics_namespace.yaml
+  yq '.scenarios[0].namespace="^namespace-scenario$"' -i scenarios/openshift/ingress_namespace.yaml
+  yq '.scenarios[0].wait_time=30' -i scenarios/openshift/ingress_namespace.yaml
+  yq '.scenarios[0].action="delete"' -i scenarios/openshift/ingress_namespace.yaml
   envsubst < CI/config/common_test_config.yaml > CI/config/namespace_config.yaml
   python3 -m coverage run -a run_kraken.py -c CI/config/namespace_config.yaml
-  echo $?
   echo "Namespace scenario test: Success"
 }
 

CI/tests/test_net_chaos.sh

@@ -7,9 +7,16 @@ trap finish EXIT
 
 
 function functional_test_network_chaos {
+  yq -i '.network_chaos.duration=10' scenarios/openshift/network_chaos.yaml
+  yq -i '.network_chaos.node_name="kind-worker2"' scenarios/openshift/network_chaos.yaml
+  yq -i '.network_chaos.egress.bandwidth="100mbit"' scenarios/openshift/network_chaos.yaml
+  yq -i 'del(.network_chaos.interfaces)' scenarios/openshift/network_chaos.yaml
+  yq -i 'del(.network_chaos.label_selector)' scenarios/openshift/network_chaos.yaml
+  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_file="CI/scenarios/network_chaos.yaml"
+  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
   python3 -m coverage run -a run_kraken.py -c CI/config/network_chaos.yaml

CI/tests/test_service_hijacking.sh

@@ -0,0 +1,114 @@
+set -xeEo pipefail
+
+source CI/tests/common.sh
+
+trap error ERR
+trap finish EXIT
+# port mapping has been configured in kind-config.yml
+SERVICE_URL=http://localhost:8888
+PAYLOAD_GET_1="{ \
+  \"status\":\"internal server error\" \
+}"
+STATUS_CODE_GET_1=500
+
+PAYLOAD_PATCH_1="resource patched"
+STATUS_CODE_PATCH_1=201
+
+PAYLOAD_POST_1="{ \
+  \"status\": \"unauthorized\" \
+}"
+STATUS_CODE_POST_1=401
+
+PAYLOAD_GET_2="{ \
+  \"status\":\"resource created\" \
+}"
+STATUS_CODE_GET_2=201
+
+PAYLOAD_PATCH_2="bad request"
+STATUS_CODE_PATCH_2=400
+
+PAYLOAD_POST_2="not found"
+STATUS_CODE_POST_2=404
+
+JSON_MIME="application/json"
+TEXT_MIME="text/plain; charset=utf-8"
+
+function functional_test_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
+  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`"
+  OUT_CONTENT=`curl -X GET -s -o /dev/null -I -w "%{content_type}" $SERVICE_URL/list/index.php`
+  OUT_STATUS_CODE=`curl -X GET -s -o /dev/null -I -w "%{http_code}" $SERVICE_URL/list/index.php`
+  [ "${PAYLOAD_GET_1//[$'\t\r\n ']}" == "${OUT_GET//[$'\t\r\n ']}" ] && echo "Step 1 GET Payload OK" || (echo "Payload did not match. Test failed." && exit 1)
+  [ "$OUT_STATUS_CODE" == "$STATUS_CODE_GET_1" ] && echo "Step 1 GET Status Code OK" || (echo " Step 1 GET status code did not match. Test failed." && exit 1)
+  [ "$OUT_CONTENT" == "$JSON_MIME" ] && echo "Step 1 GET MIME OK" || (echo " Step 1 GET MIME did not match. Test failed." && exit 1)
+
+  #Checking Step 1 POST on /list/index.php
+  OUT_POST="`curl -s -X POST $SERVICE_URL/list/index.php`"
+  OUT_STATUS_CODE=`curl -X POST -s -o /dev/null -I -w "%{http_code}" $SERVICE_URL/list/index.php`
+  OUT_CONTENT=`curl -X POST -s -o /dev/null -I -w "%{content_type}" $SERVICE_URL/list/index.php`
+  [ "${PAYLOAD_POST_1//[$'\t\r\n ']}" == "${OUT_POST//[$'\t\r\n ']}" ] && echo "Step 1 POST Payload OK" || (echo "Payload did not match. Test failed." && exit 1)
+  [ "$OUT_STATUS_CODE" == "$STATUS_CODE_POST_1" ] && echo "Step 1 POST Status Code OK" || (echo "Step 1 POST status code did not match. Test failed." && exit 1)
+  [ "$OUT_CONTENT" == "$JSON_MIME" ] && echo "Step 1 POST MIME OK" || (echo " Step 1 POST MIME did not match. Test failed." && exit 1)
+
+  #Checking Step 1 PATCH on /patch
+  OUT_PATCH="`curl -s -X PATCH $SERVICE_URL/patch`"
+  OUT_STATUS_CODE=`curl -X PATCH -s -o /dev/null -I -w "%{http_code}" $SERVICE_URL/patch`
+  OUT_CONTENT=`curl -X PATCH -s -o /dev/null -I -w "%{content_type}" $SERVICE_URL/patch`
+  [ "${PAYLOAD_PATCH_1//[$'\t\r\n ']}" == "${OUT_PATCH//[$'\t\r\n ']}" ] && echo "Step 1 PATCH Payload OK" || (echo "Payload did not match. Test failed." && exit 1)
+  [ "$OUT_STATUS_CODE" == "$STATUS_CODE_PATCH_1" ] && echo "Step 1 PATCH Status Code OK" || (echo "Step 1 PATCH status code did not match. Test failed." && exit 1)
+  [ "$OUT_CONTENT" == "$TEXT_MIME" ] && echo "Step 1 PATCH MIME OK" || (echo " Step 1 PATCH MIME did not match. Test failed." && exit 1)
+  # wait for the next step
+  sleep 16
+
+  #Checking Step 2 GET on /list/index.php
+  OUT_GET="`curl -X GET -s $SERVICE_URL/list/index.php`"
+  OUT_CONTENT=`curl -X GET -s -o /dev/null -I -w "%{content_type}" $SERVICE_URL/list/index.php`
+  OUT_STATUS_CODE=`curl -X GET -s -o /dev/null -I -w "%{http_code}" $SERVICE_URL/list/index.php`
+  [ "${PAYLOAD_GET_2//[$'\t\r\n ']}" == "${OUT_GET//[$'\t\r\n ']}" ] && echo "Step 2 GET Payload OK" || (echo "Step 2 GET Payload did not match. Test failed." && exit 1)
+  [ "$OUT_STATUS_CODE" == "$STATUS_CODE_GET_2" ] && echo "Step 2 GET Status Code OK" || (echo "Step 2 GET status code did not match. Test failed." && exit 1)
+  [ "$OUT_CONTENT" == "$JSON_MIME" ] && echo "Step 2 GET MIME OK" || (echo " Step 2 GET MIME did not match. Test failed." && exit 1)
+
+  #Checking Step 2 POST on /list/index.php
+  OUT_POST="`curl -s -X POST $SERVICE_URL/list/index.php`"
+  OUT_CONTENT=`curl -X POST -s -o /dev/null -I -w "%{content_type}" $SERVICE_URL/list/index.php`
+  OUT_STATUS_CODE=`curl -X POST -s -o /dev/null -I -w "%{http_code}" $SERVICE_URL/list/index.php`
+  [ "${PAYLOAD_POST_2//[$'\t\r\n ']}" == "${OUT_POST//[$'\t\r\n ']}" ] && echo "Step 2 POST Payload OK" || (echo "Step 2 POST Payload did not match. Test failed." && exit 1)
+  [ "$OUT_STATUS_CODE" == "$STATUS_CODE_POST_2" ] && echo "Step 2 POST Status Code OK" || (echo "Step 2 POST status code did not match. Test failed." && exit 1)
+  [ "$OUT_CONTENT" == "$TEXT_MIME" ] && echo "Step 2 POST MIME OK" || (echo " Step 2 POST MIME did not match. Test failed." && exit 1)
+
+  #Checking Step 2 PATCH on /patch
+  OUT_PATCH="`curl -s -X PATCH $SERVICE_URL/patch`"
+  OUT_CONTENT=`curl -X PATCH -s -o /dev/null -I -w "%{content_type}" $SERVICE_URL/patch`
+  OUT_STATUS_CODE=`curl -X PATCH -s -o /dev/null -I -w "%{http_code}" $SERVICE_URL/patch`
+  [ "${PAYLOAD_PATCH_2//[$'\t\r\n ']}" == "${OUT_PATCH//[$'\t\r\n ']}" ] && echo "Step 2 PATCH Payload OK" || (echo "Step 2 PATCH Payload did not match. Test failed." && exit 1)
+  [ "$OUT_STATUS_CODE" == "$STATUS_CODE_PATCH_2" ] && echo "Step 2 PATCH Status Code OK" || (echo "Step 2 PATCH status code did not match. Test failed." && exit 1)
+  [ "$OUT_CONTENT" == "$TEXT_MIME" ] && echo "Step 2 PATCH MIME OK" || (echo " Step 2 PATCH MIME did not match. Test failed." && exit 1)
+  wait $PID
+
+  # now checking  if service has been restore correctly and nginx responds correctly
+  curl -s  $SERVICE_URL | grep nginx! && echo "BODY: Service restored!" || (echo "BODY: failed to restore service" && exit 1)
+  OUT_STATUS_CODE=`curl -X GET -s -o /dev/null -I -w "%{http_code}" $SERVICE_URL`
+  [ "$OUT_STATUS_CODE" == "200" ] && echo "STATUS_CODE: Service restored!" || (echo "STATUS_CODE: failed to restore service" && exit 1)
+
+  echo "Service Hijacking Chaos test: Success"
+}
+
+
+functional_test_service_hijacking

CI/tests/test_telemetry.sh

@@ -0,0 +1,38 @@
+set -xeEo pipefail
+
+source CI/tests/common.sh
+
+trap error ERR
+trap finish EXIT
+
+
+function functional_test_telemetry {
+  AWS_CLI=`which aws`
+  [ -z "$AWS_CLI" ]&& echo "AWS cli not found in path" && exit 1
+  [ -z "$AWS_BUCKET" ] && echo "AWS bucket not set in environment" && exit 1
+
+  export RUN_TAG="funtest-telemetry"
+  yq -i '.telemetry.enabled=True' CI/config/common_test_config.yaml
+  yq -i '.telemetry.full_prometheus_backup=True' CI/config/common_test_config.yaml
+  yq -i '.performance_monitoring.check_critical_alerts=True' CI/config/common_test_config.yaml
+  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="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 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 )
+  echo "all files uploaded!"
+  echo "Telemetry Collection: Success"
+}
+
+functional_test_telemetry

CI/tests/test_time.sh

@@ -7,8 +7,12 @@ trap finish EXIT
 
 
 function functional_test_time_scenario {
+  yq -i '.time_scenarios[0].label_selector="scenario=time-skew"' scenarios/openshift/time_scenarios_example.yml
+  yq -i '.time_scenarios[0].container_name=""' scenarios/openshift/time_scenarios_example.yml
+  yq -i '.time_scenarios[0].namespace="default"' scenarios/openshift/time_scenarios_example.yml
+  yq -i '.time_scenarios[1].label_selector="kubernetes.io/hostname=kind-worker2"' scenarios/openshift/time_scenarios_example.yml
   export scenario_type="time_scenarios"
-  export scenario_file="CI/scenarios/time_scenarios.yml"
+  export scenario_file="scenarios/openshift/time_scenarios_example.yml"
   export post_config=""
   envsubst < CI/config/common_test_config.yaml > CI/config/time_config.yaml
 

README.md

@@ -1,113 +1,25 @@
-# KrknChaos aka Kraken
-[![Docker Repository on Quay](https://quay.io/repository/redhat-chaos/krkn/status "Docker Repository on Quay")](https://quay.io/repository/redhat-chaos/krkn?tab=tags&tag=latest)
-![Workflow-Status](https://github.com/redhat-chaos/krkn/actions/workflows/docker-image.yml/badge.svg)
+# Krkn aka Kraken
+![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)
 
-Chaos and resiliency testing tool for Kubernetes and OpenShift.
-Kraken injects deliberate failures into Kubernetes/OpenShift clusters to check if it is resilient to turbulent conditions.
+Chaos and resiliency testing tool for Kubernetes.
+Kraken injects deliberate failures into Kubernetes clusters to check if it is resilient to turbulent conditions.
 
 
 ### 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 OpenShift 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://redhat-chaos.github.io/krknChoas.
+<!-- ### 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 [Kraken-hub](https://github.com/redhat-chaos/krknChaos-hub). One use case is CI integration where you do not want to carry around different configuration files for the scenarios.
-
-### Setting up infrastructure dependencies
-Kraken indexes the metrics specified in the profile into Elasticsearch in addition to leveraging Cerberus for understanding the health of the Kubernetes/OpenShift cluster under test. More information on the features is documented below. The infrastructure pieces can be easily installed and uninstalled by running:
-
-```
-$ cd kraken
-$ podman-compose up or $ docker-compose up      # Spins up the containers specified in the docker-compose.yml file present in the run directory.
-$ podman-compose down or $ docker-compose down  # Delete the containers installed.
-```
-This will manage the Cerberus and Elasticsearch containers on the host on which you are running Kraken.
-
-**NOTE**: Make sure you have enough resources (memory and disk) on the machine on top of which the containers are running as Elasticsearch is resource intensive. Cerberus monitors the system components by default, the [config](config/cerberus.yaml) can be tweaked to add applications namespaces, routes and other components to monitor as well. The command will keep running until killed since detached mode is not supported as of now.
-
-
-### Config
-Instructions on how to setup the config and the options supported can be found at [Config](docs/config.md).
-
-
-### Kubernetes/OpenShift chaos scenarios supported
-
-Scenario type               | Kubernetes    | OpenShift          
---------------------------- | ------------- |--------------------|  
-[Pod Scenarios](docs/pod_scenarios.md) | :heavy_check_mark: | :heavy_check_mark: |
-[Pod Network Scenarios](docs/pod_network_scenarios.md) | :x: | :heavy_check_mark: |
-[Container Scenarios](docs/container_scenarios.md) | :heavy_check_mark: | :heavy_check_mark: |
-[Node Scenarios](docs/node_scenarios.md) | :heavy_check_mark: | :heavy_check_mark: |
-[Time Scenarios](docs/time_scenarios.md) | :x: | :heavy_check_mark: |
-[Hog Scenarios: CPU, Memory](docs/arcaflow_scenarios.md) | :heavy_check_mark: | :heavy_check_mark: |
-[Cluster Shut Down Scenarios](docs/cluster_shut_down_scenarios.md) | :heavy_check_mark: | :heavy_check_mark: |
-[Service Disruption Scenarios](docs/service_disruption_scenarios.md.md) | :heavy_check_mark: | :heavy_check_mark: |
-[Zone Outage Scenarios](docs/zone_outage.md) | :heavy_check_mark: | :heavy_check_mark: |
-[Application_outages](docs/application_outages.md) | :heavy_check_mark: | :heavy_check_mark: |
-[PVC scenario](docs/pvc_scenario.md) | :heavy_check_mark: | :heavy_check_mark: |
-[Network_Chaos](docs/network_chaos.md) | :heavy_check_mark: | :heavy_check_mark: |
-[ManagedCluster Scenarios](docs/managedcluster_scenarios.md) | :heavy_check_mark: | :question:         |
-
-
-### 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/OpenShift 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/openshift-scale/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/redhat-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).
-
-
-### Scraping and storing metrics long term
-Kraken supports capturing metrics for the duration of the scenarios defined in the config and indexes then into Elasticsearch to be able to store and evaluate the state of the runs long term. The indexed metrics can be visualized with the help of Grafana. It uses [Kube-burner](https://github.com/kube-burner/kube-burner) under the hood. The metrics to capture need to be defined in a metrics profile which Kraken consumes to query prometheus ( installed by default in OpenShift ) with the start and end timestamp of the run. Information on enabling and leveraging this feature can be found [here](docs/metrics.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.redhat.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
@@ -116,6 +28,8 @@ Kraken supports injecting faults into [Open Cluster Management (OCM)](https://op
 - Blog post emphasizing the importance of making Chaos part of Performance and Scale runs to mimic the production environments: https://www.openshift.com/blog/making-chaos-part-of-kubernetes/openshift-performance-and-scalability-tests
 - Blog post on findings from Chaos test runs: https://cloud.redhat.com/blog/openshift/kubernetes-chaos-stories
 - Discussion with CNCF TAG App Delivery on Krkn workflow, features and addition to CNCF sandbox: [Github](https://github.com/cncf/sandbox/issues/44), [Tracker](https://github.com/cncf/tag-app-delivery/issues/465), [recording](https://www.youtube.com/watch?v=nXQkBFK_MWc&t=722s)
+- 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
@@ -125,13 +39,11 @@ 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
-Key Members(slack_usernames/full name): paigerube14/Paige Rubendall, mffiedler/Mike Fiedler, ravielluri/Naga Ravi Chaitanya Elluri.
-* [**#krkn on Kubernetes Slack**](https://kubernetes.slack.com)
-* [**#forum-chaos on CoreOS Slack internal to Red Hat**](https://coreos.slack.com)
+Key Members(slack_usernames/full name): paigerube14/Paige Rubendall, mffiedler/Mike Fiedler, tsebasti/Tullio Sebastiani, yogi/Yogananth Subramanian, sahil/Sahil Shah, pradeep/Pradeep Surisetty and ravielluri/Naga Ravi Chaitanya Elluri.
+* [**#krkn on Kubernetes Slack**](https://kubernetes.slack.com/messages/C05SFMHRWK1)
+
+The Linux Foundation® (TLF) has registered trademarks and uses trademarks. For a list of TLF trademarks, see [Trademark Usage](https://www.linuxfoundation.org/legal/trademark-usage).

ROADMAP.md

@@ -2,14 +2,15 @@
 
 Following are a list of enhancements that we are planning to work on adding support in Krkn. Of course any help/contributions are greatly appreciated.
 
-- [ ] [Ability to run multiple chaos scenarios in parallel under load to mimic real world outages](https://github.com/redhat-chaos/krkn/issues/424)
-- [x] [Centralized storage for chaos experiments artifacts](https://github.com/redhat-chaos/krkn/issues/423)
-- [ ] [Support for causing DNS outages](https://github.com/redhat-chaos/krkn/issues/394)
-- [x] [Chaos recommender](https://github.com/redhat-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
-- [x] [Support for pod level network traffic shaping](https://github.com/redhat-chaos/krkn/issues/393)
-- [ ] [Ability to visualize the metrics that are being captured by Kraken and stored in Elasticsearch](https://github.com/redhat-chaos/krkn/issues/124)
-- [ ] Support for running all the scenarios of Kraken on Kubernetes distribution - see https://github.com/redhat-chaos/krkn/issues/185, https://github.com/redhat-chaos/krkn/issues/186
-- [ ] Continue to improve [Chaos Testing Guide](https://redhat-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/redhat-chaos/krkn/issues/495)
-- [ ] [OCP and Kubernetes functionalities segregation](https://github.com/redhat-chaos/krkn/issues/497)
+- [ ] [Ability to run multiple chaos scenarios in parallel under load to mimic real world outages](https://github.com/krkn-chaos/krkn/issues/424)
+- [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 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)
+- [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/alerts.yaml

@@ -8,7 +8,7 @@
   description: 10 minutes avg. 99th etcd fsync latency on {{$labels.pod}} higher than 1s. {{$value}}s
   severity: error
 
-- expr: avg_over_time(histogram_quantile(0.99, rate(etcd_disk_backend_commit_duration_seconds_bucket[2m]))[10m:]) > 0.007
+- expr: avg_over_time(histogram_quantile(0.99, rate(etcd_disk_backend_commit_duration_seconds_bucket[2m]))[10m:]) > 0.03
   description: 10 minutes avg. 99th etcd commit latency on {{$labels.pod}} higher than 30ms. {{$value}}s
   severity: warning
 
@@ -88,3 +88,42 @@
 - expr: ALERTS{severity="critical", alertstate="firing"} > 0
   description: Critical prometheus alert. {{$labels.alertname}}
   severity: warning
+
+# etcd CPU and usage increase
+- expr: sum(rate(container_cpu_usage_seconds_total{image!='', namespace='openshift-etcd', container='etcd'}[1m])) * 100 / sum(machine_cpu_cores)  > 5
+  description: Etcd CPU usage increased significantly by {{$value}}%
+  severity: critical
+
+# etcd memory usage increase
+- expr: sum(deriv(container_memory_usage_bytes{image!='', namespace='openshift-etcd', container='etcd'}[5m])) * 100 / sum(node_memory_MemTotal_bytes) > 5
+  description: Etcd memory usage increased significantly by {{$value}}%
+  severity: critical
+
+# Openshift API server CPU and memory usage increase
+- expr: sum(rate(container_cpu_usage_seconds_total{image!='', namespace='openshift-apiserver', container='openshift-apiserver'}[1m])) * 100 / sum(machine_cpu_cores) > 5
+  description: openshift apiserver cpu usage increased significantly by {{$value}}%
+  severity: critical
+
+- expr: (sum(deriv(container_memory_usage_bytes{namespace='openshift-apiserver', container='openshift-apiserver'}[5m]))) * 100 / sum(node_memory_MemTotal_bytes) > 5
+  description: openshift apiserver memory usage increased significantly by {{$value}}%
+  severity: critical
+
+# Openshift kube API server CPU and memory usage increase
+- expr: sum(rate(container_cpu_usage_seconds_total{image!='', namespace='openshift-kube-apiserver', container='kube-apiserver'}[1m])) * 100 / sum(machine_cpu_cores) > 5
+  description: openshift apiserver cpu usage increased significantly by {{$value}}%
+  severity: critical
+
+- expr: (sum(deriv(container_memory_usage_bytes{namespace='openshift-kube-apiserver', container='kube-apiserver'}[5m]))) * 100 / sum(node_memory_MemTotal_bytes) > 5
+  description: openshift apiserver memory usage increased significantly by {{$value}}%
+  severity: critical
+
+# Master node CPU usage increase
+- expr: (sum((sum(deriv(pod:container_cpu_usage:sum{container="",pod!=""}[5m])) BY (namespace, pod) * on(pod, namespace) group_left(node) (node_namespace_pod:kube_pod_info:)  )  *  on(node) group_left(role) (max by (node) (kube_node_role{role="master"})))) * 100 / sum(machine_cpu_cores) > 5
+  description: master nodes cpu usage increased significantly by {{$value}}%
+  severity: critical
+
+# Master nodes memory usage increase
+- expr: (sum((sum(deriv(container_memory_usage_bytes{container="",pod!=""}[5m])) BY (namespace, pod) * on(pod, namespace) group_left(node) (node_namespace_pod:kube_pod_info:)  )  *  on(node) group_left(role) (max by (node) (kube_node_role{role="master"})))) * 100 / sum(node_memory_MemTotal_bytes) > 5
+  description: master nodes memory usage increased significantly by {{$value}}%
+  severity: critical
+

config/alerts_openshift.yaml

@@ -99,3 +99,41 @@
 - expr: ALERTS{severity="critical", alertstate="firing"} > 0
   description: Critical prometheus alert. {{$labels.alertname}}
   severity: warning
+
+# etcd CPU and usage increase
+- expr: sum(rate(container_cpu_usage_seconds_total{image!='', namespace='openshift-etcd', container='etcd'}[1m])) * 100 / sum(machine_cpu_cores)  > 5
+  description: Etcd CPU usage increased significantly by {{$value}}%
+  severity: critical
+
+# etcd memory usage increase
+- expr: sum(deriv(container_memory_usage_bytes{image!='', namespace='openshift-etcd', container='etcd'}[5m])) * 100 / sum(node_memory_MemTotal_bytes) > 5
+  description: Etcd memory usage increased significantly by {{$value}}%
+  severity: critical
+
+# Openshift API server CPU and memory usage increase
+- expr: sum(rate(container_cpu_usage_seconds_total{image!='', namespace='openshift-apiserver', container='openshift-apiserver'}[1m])) * 100 / sum(machine_cpu_cores) > 5
+  description: openshift apiserver cpu usage increased significantly by {{$value}}%
+  severity: critical
+
+- expr: (sum(deriv(container_memory_usage_bytes{namespace='openshift-apiserver', container='openshift-apiserver'}[5m]))) * 100 / sum(node_memory_MemTotal_bytes) > 5
+  description: openshift apiserver memory usage increased significantly by {{$value}}%
+  severity: critical
+
+# Openshift kube API server CPU and memory usage increase
+- expr: sum(rate(container_cpu_usage_seconds_total{image!='', namespace='openshift-kube-apiserver', container='kube-apiserver'}[1m])) * 100 / sum(machine_cpu_cores) > 5
+  description: openshift apiserver cpu usage increased significantly by {{$value}}%
+  severity: critical
+
+- expr: (sum(deriv(container_memory_usage_bytes{namespace='openshift-kube-apiserver', container='kube-apiserver'}[5m]))) * 100 / sum(node_memory_MemTotal_bytes) > 5
+  description: openshift apiserver memory usage increased significantly by {{$value}}%
+  severity: critical
+
+# Master node CPU usage increase
+- expr: (sum((sum(deriv(pod:container_cpu_usage:sum{container="",pod!=""}[5m])) BY (namespace, pod) * on(pod, namespace) group_left(node) (node_namespace_pod:kube_pod_info:)  )  *  on(node) group_left(role) (max by (node) (kube_node_role{role="master"})))) * 100 / sum(machine_cpu_cores) > 5
+  description: master nodes cpu usage increased significantly by {{$value}}%
+  severity: critical
+
+# Master nodes memory usage increase
+- expr: (sum((sum(deriv(container_memory_usage_bytes{container="",pod!=""}[5m])) BY (namespace, pod) * on(pod, namespace) group_left(node) (node_namespace_pod:kube_pod_info:)  )  *  on(node) group_left(role) (max by (node) (kube_node_role{role="master"})))) * 100 / sum(node_memory_MemTotal_bytes) > 5
+  description: master nodes memory usage increased significantly by {{$value}}%
+  severity: critical

config/config.yaml

@@ -1,6 +1,5 @@
 kraken:
-    distribution: openshift                                # 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
@@ -8,40 +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_scenarios:
+              - scenarios/kube/service_hijacking.yaml
+        - 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
@@ -51,14 +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"
-    capture_metrics: False
-    metrics_profile_path: config/metrics-aggregated.yaml
-    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
@@ -67,14 +83,19 @@ telemetry:
     enabled: False                                           # enable/disables the telemetry collection feature
     api_url: https://ulnmf9xv7j.execute-api.us-west-2.amazonaws.com/production #telemetry service endpoint
     username: username                                      # telemetry service username
-    password: password                                      # telemetry service password
+    password: password                                    # telemetry service password
     prometheus_backup: True                                 # enables/disables prometheus data collection
+    prometheus_namespace: ""                                # namespace where prometheus is deployed (if distribution is kubernetes)
+    prometheus_container_name: ""                           # name of the prometheus container name (if distribution is kubernetes)
+    prometheus_pod_name: ""                                 # name of the prometheus pod (if distribution is kubernetes)
     full_prometheus_backup: False                           # if is set to False only the /prometheus/wal folder will be downloaded.
     backup_threads: 5                                       # number of telemetry download/upload threads
     archive_path: /tmp                                      # local path where the archive files will be temporarly stored
     max_retries: 0                                          # maximum number of upload retries (if 0 will retry forever)
     run_tag: ''                                             # if set, this will be appended to the run folder in the bucket (useful to group the runs)
-    archive_size: 500000                                     # the size of the prometheus data archive size in KB. The lower the size of archive is
+    archive_size: 500000
+    telemetry_group: ''                                     # if set will archive the telemetry in the S3 bucket on a folder named after the value, otherwise will use "default"
+    # the size of the prometheus data archive size in KB. The lower the size of archive is
                                                             # the higher the number of archive files will be produced and uploaded (and processed by backup_threads
                                                             # simultaneously).
                                                             # For unstable/slow connection is better to keep this value low
@@ -88,6 +109,10 @@ telemetry:
     oc_cli_path: /usr/bin/oc                                # optional, if not specified will be search in $PATH
     events_backup: True                                     # enables/disables cluster events collection
 
-
-
-
+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:
@@ -20,8 +20,6 @@ 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"
-    capture_metrics: False
-    metrics_profile_path: config/metrics-aggregated.yaml
     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

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
 
@@ -19,8 +19,6 @@ 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"
-    capture_metrics: False
-    metrics_profile_path: config/metrics-aggregated.yaml
     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

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
@@ -77,3 +76,8 @@ telemetry:
      - "kinit (\\d+/\\d+/\\d+\\s\\d{2}:\\d{2}:\\d{2})\\s+"          # kinit 2023/09/15 11:20:36 log
      - "(\\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
+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
+
+

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

config/recommender_config.yaml

@@ -1,5 +1,5 @@
 application: openshift-etcd
-namespace: openshift-etcd
+namespaces: openshift-etcd
 labels: app=openshift-etcd
 kubeconfig: ~/.kube/config.yaml
 prometheus_endpoint: <Prometheus_Endpoint>
@@ -7,6 +7,8 @@ auth_token: <Auth_Token>
 scrape_duration: 10m
 chaos_library: "kraken"
 log_level: INFO
+json_output_file: False
+json_output_folder_path:
 
 # for output purpose only do not change if not needed
 chaos_tests:
@@ -26,4 +28,8 @@ chaos_tests:
     - pod_network_chaos
   MEM:
     - node_memory_hog
-    - pvc_disk_fill
+    - pvc_disk_fill
+
+threshold: .7
+cpu_threshold: .5
+mem_threshold: .5

containers/Dockerfile

@@ -1,30 +0,0 @@
-# Dockerfile for kraken
-
-FROM mcr.microsoft.com/azure-cli:latest as azure-cli
-
-FROM registry.access.redhat.com/ubi8/ubi:latest
-
-LABEL org.opencontainers.image.authors="Red Hat OpenShift Chaos Engineering"
-
-ENV KUBECONFIG /root/.kube/config
-
-# Copy azure client binary from azure-cli image
-COPY --from=azure-cli /usr/local/bin/az /usr/bin/az
-
-# Install dependencies
-RUN yum install -y git python39 python3-pip jq gettext wget && \
-    python3.9 -m pip install -U pip && \
-    git clone https://github.com/redhat-chaos/krkn.git --branch v1.5.3 /root/kraken && \
-    mkdir -p /root/.kube && cd /root/kraken && \
-    pip3.9 install -r requirements.txt && \
-    pip3.9 install virtualenv && \
-    wget https://github.com/mikefarah/yq/releases/latest/download/yq_linux_amd64 -O /usr/bin/yq && chmod +x /usr/bin/yq
-
-# Get Kubernetes and OpenShift clients from stable releases
-WORKDIR /tmp
-RUN wget https://mirror.openshift.com/pub/openshift-v4/clients/ocp/stable/openshift-client-linux.tar.gz && tar -xvf openshift-client-linux.tar.gz && cp oc /usr/local/bin/oc && cp kubectl /usr/local/bin/kubectl
-
-WORKDIR /root/kraken
-
-ENTRYPOINT ["python3.9", "run_kraken.py"]
-CMD ["--config=config/config.yaml"]

containers/Dockerfile-ppc64le

@@ -1,29 +0,0 @@
-# Dockerfile for kraken
-
-FROM ppc64le/centos:8
-
-FROM mcr.microsoft.com/azure-cli:latest as azure-cli
-
-LABEL org.opencontainers.image.authors="Red Hat OpenShift Chaos Engineering"
-
-ENV KUBECONFIG /root/.kube/config
-
-# Copy azure client binary from azure-cli image
-COPY --from=azure-cli /usr/local/bin/az /usr/bin/az
-
-# Install dependencies
-RUN yum install -y git python39 python3-pip jq gettext wget && \
-    python3.9 -m pip install -U pip && \
-    git clone https://github.com/redhat-chaos/krkn.git --branch v1.5.3 /root/kraken && \
-    mkdir -p /root/.kube && cd /root/kraken && \
-    pip3.9 install -r requirements.txt && \
-    pip3.9 install virtualenv && \
-    wget https://github.com/mikefarah/yq/releases/latest/download/yq_linux_amd64 -O /usr/bin/yq && chmod +x /usr/bin/yq
-
-# Get Kubernetes and OpenShift clients from stable releases
-WORKDIR /tmp
-RUN wget https://mirror.openshift.com/pub/openshift-v4/clients/ocp/stable/openshift-client-linux.tar.gz && tar -xvf openshift-client-linux.tar.gz && cp oc /usr/local/bin/oc && cp kubectl /usr/local/bin/kubectl
-
-WORKDIR /root/kraken
-
-ENTRYPOINT python3.9 run_kraken.py --config=config/config.yaml

containers/Dockerfile.template

@@ -0,0 +1,62 @@
+# 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 1.23.1 &&\
+    go get github.com/moby/buildkit@v0.12.5 &&\
+    go get github.com/containerd/containerd@v1.7.11&&\
+    go get github.com/docker/docker@v25.0.6&&\
+    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
+
+FROM fedora:40
+ARG PR_NUMBER
+ARG TAG
+RUN groupadd -g 1001 krkn && useradd -m -u 1001 -g krkn krkn
+RUN dnf update -y
+
+ENV KUBECONFIG /home/krkn/.kube/config
+
+
+# This overwrites any existing configuration in /etc/yum.repos.d/kubernetes.repo
+RUN dnf update && dnf install -y --setopt=install_weak_deps=False \
+    git python39 jq yq gettext wget which &&\
+    dnf clean all
+
+# copy oc client binary from oc-build image
+COPY --from=oc-build /tmp/oc/oc /usr/bin/oc
+
+# krkn build
+RUN git clone https://github.com/krkn-chaos/krkn.git /home/krkn/kraken && \
+    mkdir -p /home/krkn/.kube
+
+WORKDIR /home/krkn/kraken
+
+# default behaviour will be to build main
+# if it is a PR trigger the PR itself will be checked out
+RUN if [ -n "$PR_NUMBER" ]; then git fetch origin pull/${PR_NUMBER}/head:pr-${PR_NUMBER} && git checkout pr-${PR_NUMBER};fi
+# if it is a TAG trigger checkout the tag
+RUN if [ -n "$TAG" ]; then git checkout "$TAG";fi
+
+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"]
+CMD ["--config=config/config.yaml"]

containers/README.md

@@ -6,41 +6,9 @@ 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
 
 Refer to [instructions](https://github.com/redhat-chaos/krkn/blob/main/containers/build_own_image-README.md) for information on how to run a custom containerized version of kraken using podman.
-
-
-### Kraken as a KubeApp ( Unsupported and not recommended )
-
-#### GENERAL NOTES:
-
-- It is not generally recommended to run Kraken internal to the cluster as the pod which is running Kraken might get disrupted, the suggested use case to run kraken from inside k8s/OpenShift is to target **another** cluster (eg. to bypass network restrictions or to leverage cluster's computational resources)
-
-- your kubeconfig might contain several cluster contexts and credentials so be sure, before creating the ConfigMap, to keep **only** the credentials related to the destination cluster. Please refer to the [Kubernetes documentation](https://kubernetes.io/docs/tasks/access-application-cluster/configure-access-multiple-clusters/) for more details
-- to add privileges to the service account you must be logged in the cluster with an highly privileged account (ideally kubeadmin)
-
-  
-
-To run containerized Kraken as a Kubernetes/OpenShift Deployment, follow these steps:
-
-1. Configure the [config.yaml](https://github.com/redhat-chaos/krkn/blob/main/config/config.yaml) file according to your requirements.
-
-**NOTE**: both the scenarios ConfigMaps are needed regardless you're running kraken in Kubernetes or OpenShift
-
-2. Create a namespace under which you want to run the kraken pod using `kubectl create ns <namespace>`.
-3. Switch to `<namespace>` namespace:
-- In Kubernetes, use `kubectl config set-context --current --namespace=<namespace>`
-- In OpenShift, use `oc project <namespace>`
-  
-4. Create a ConfigMap named kube-config using `kubectl create configmap kube-config --from-file=<path_to_kubeconfig>`  *(eg. ~/.kube/config)*
-5. Create a ConfigMap named kraken-config using `kubectl create configmap kraken-config --from-file=<path_to_kraken>/config`
-6. Create a ConfigMap named scenarios-config using `kubectl create configmap scenarios-config --from-file=<path_to_kraken>/scenarios`
-7. Create a ConfigMap named scenarios-openshift-config using `kubectl create configmap scenarios-openshift-config --from-file=<path_to_kraken>/scenarios/openshift`
-8. Create a ConfigMap named scenarios-kube-config using `kubectl create configmap scenarios-kube-config --from-file=<path_to_kraken>/scenarios/kube` 
-9. Create a service account to run the kraken pod `kubectl create serviceaccount useroot`.
-10.  In Openshift, add privileges to service account and execute `oc adm policy add-scc-to-user privileged -z useroot`.
-11.  Create a Job using `kubectl apply -f <path_to_kraken>/containers/kraken.yml` and monitor the status using `oc get jobs` and `oc get pods`.

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/kraken.yml

@@ -1,49 +0,0 @@
----
-apiVersion: batch/v1
-kind: Job
-metadata:
-  name: kraken
-spec:
-  parallelism: 1
-  completions: 1
-  template:
-    metadata:
-      labels:
-        tool: Kraken
-    spec:
-      serviceAccountName: useroot
-      containers:
-        - name: kraken
-          securityContext:
-            privileged: true
-          image: quay.io/redhat-chaos/krkn
-          command: ["/bin/sh", "-c"]
-          args: ["python3.9 run_kraken.py -c config/config.yaml"]
-          volumeMounts:
-            - mountPath: "/root/.kube"
-              name: config
-            - mountPath: "/root/kraken/config"
-              name: kraken-config
-            - mountPath: "/root/kraken/scenarios"
-              name: scenarios-config
-            - mountPath: "/root/kraken/scenarios/openshift"
-              name: scenarios-openshift-config
-            - mountPath: "/root/kraken/scenarios/kube"
-              name: scenarios-kube-config
-      restartPolicy: Never
-      volumes:
-        - name: config
-          configMap:
-            name: kube-config
-        - name: kraken-config
-          configMap:
-            name: kraken-config
-        - name: scenarios-config
-          configMap:
-            name: scenarios-config
-        - name: scenarios-openshift-config
-          configMap:
-            name: scenarios-openshift-config
-        - name: scenarios-kube-config
-          configMap:
-            name: scenarios-kube-config

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"
+  }
+]

docker-compose.yml

@@ -1,31 +0,0 @@
-version: "3"
-services:
-  elastic:
-    image: docker.elastic.co/elasticsearch/elasticsearch:7.13.2
-    deploy:
-      replicas: 1
-      restart_policy:
-        condition: on-failure
-    network_mode: host
-    environment:
-      discovery.type: single-node
-  kibana:
-    image: docker.elastic.co/kibana/kibana:7.13.2
-    deploy:
-      replicas: 1
-      restart_policy:
-        condition: on-failure
-    network_mode: host
-    environment:
-      ELASTICSEARCH_HOSTS: "http://0.0.0.0:9200"
-  cerberus:
-    image: quay.io/openshift-scale/cerberus:latest
-    privileged: true
-    deploy:
-      replicas: 1
-      restart_policy:
-        condition: on-failure
-    network_mode: host
-    volumes:
-       - ./config/cerberus.yaml:/root/cerberus/config/config.yaml:Z  # Modify the config in case of the need to monitor additional components
-       - ${HOME}/.kube/config:/root/.kube/config:Z

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

@@ -1,89 +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**: For Azure node killing scenarios, make sure [Azure CLI](https://docs.microsoft.com/en-us/cli/azure/install-azure-cli?view=azure-cli-latest) is installed.
-
-You will also 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. Login using ```az login```
-
-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/OpenShift 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/redhat-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/OpenShift 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/redhat-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/redhat-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

@@ -1,55 +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>
-- id: wait-for-pods
-  config:
-    namespace_pattern: ^<namespace>$
-    label_selector: <pod label>
-    count: <expected number of pods that match namespace and label>
-```
-
-#### 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

@@ -1,54 +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/redhat-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/redhat-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/redhat-chaos/krkn/releases).
-```
-$ git clone https://github.com/redhat-chaos/krkn.git --branch <release version>
-$ cd kraken
-```
-
-#### 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/redhat-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/redhat-chaos/krkn-hub#supported-chaos-scenarios) to get started.
-
-
-### Run Kraken as a Kubernetes deployment ( unsupported option - standalone or containerized deployers are recommended )
-Refer [Instructions](https://github.com/redhat-chaos/krkn/blob/main/containers/README.md) on how to deploy and run Kraken as a Kubernetes/OpenShift deployment.
-
-
-Refer to the [chaos-kraken chart manpage](https://artifacthub.io/packages/helm/startx/chaos-kraken)
-and especially the [kraken configuration values](https://artifacthub.io/packages/helm/startx/chaos-kraken#chaos-kraken-values-dictionary) 
-for details on how to configure this chart.

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/metrics.md

@@ -1,31 +0,0 @@
-## Scraping and storing metrics for the run
-
-There are cases where the state of the cluster and metrics on the cluster during the chaos test run need to be stored long term to review after the cluster is terminated, for example CI and automation test runs. To help with this, Kraken supports capturing metrics for the duration of the scenarios defined in the config.
-
-The metrics to capture need to be defined in a metrics profile which Kraken consumes to query prometheus with the start and end timestamp of the run. Each run has a unique identifier ( uuid ). The uuid is generated automatically if not set in the config. 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:
-    capture_metrics: True
-    metrics_profile_path: config/metrics-aggregated.yaml
-    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.
-```
-
-### Metrics profile
-A couple of [metric profiles](https://github.com/redhat-chaos/krkn/tree/main/config), [metrics.yaml](https://github.com/redhat-chaos/krkn/blob/main/config/metrics.yaml), and [metrics-aggregated.yaml](https://github.com/redhat-chaos/krkn/blob/main/config/metrics-aggregated.yaml) are shipped by default and can be tweaked to add more metrics to capture during the run. The following are the API server metrics for example:
-
-```
-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
-```
-

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

@@ -1,177 +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 only on AWS, Azure, OpenStack, BareMetal, GCP
-, VMware and Alibaba as of now.
-
-**NOTE**: Node scenarios are supported only when running the standalone version of Kraken until https://github.com/redhat-chaos/krkn/issues/106 gets fixed.
-
-
-#### AWS
-
-How to set up AWS cli to run node scenarios is defined [here](cloud_setup.md#aws).
-
-#### Baremetal
-**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
-How to set up GCP cli to run node scenarios is defined [here](cloud_setup.md#gcp).
-
-#### 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
-
-How to set up Azure cli to run node scenarios is defined [here](cloud_setup.md#azure).
-
-
-#### 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
-*
-
-
-#### IBMCloud and Vmware example 
-
-
-```
-- id: ibmcloud-node-stop
-  config:
-    name: "<node_name>"        
-    label_selector: "node-role.kubernetes.io/worker"    # When node_name is not specified, a node with matching label_selector is selected for node chaos scenario injection 
-    runs: 1                             # Number of times to inject each scenario under actions (will perform on same node each time)                                                           
-    instance_count: 1                   # Number of nodes to perform action/select that match the label selector                                             
-    timeout: 30                        # Duration to wait for completion of node scenario injection
-    skip_openshift_checks: False       # Set to True if you don't want to wait for the status of the nodes to change on OpenShift before passing the scenario 
-- id: ibmcloud-node-start
-  config:
-    name: "<node_name>" #Same name as before       
-    label_selector: "node-role.kubernetes.io/worker"    # When node_name is not specified, a node with matching label_selector is selected for node chaos scenario injection 
-    runs: 1                             # Number of times to inject each scenario under actions (will perform on same node each time)                                                           
-    instance_count: 1                   # Number of nodes to perform action/select that match the label selector                                             
-    timeout: 30                        # Duration to wait for completion of node scenario injection
-    skip_openshift_checks: False       # Set to True if you don't want to wait for the status of the nodes to change on OpenShift before passing the scenario 
-    ```
-
-
-
-#### 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.
-
-Node scenarios can be injected by placing the node scenarios config files under node_scenarios option in the kraken config. Refer to [node_scenarios_example](https://github.com/redhat-chaos/krkn/blob/main/scenarios/node_scenarios_example.yml) config file.
-
-
-```
-node_scenarios:
-  - actions:                                                        # Node chaos scenarios to be injected.
-    - node_stop_start_scenario
-    - stop_start_kubelet_scenario
-    - node_crash_scenario
-    node_name:                                                      # Node on which scenario has to be injected.
-    label_selector: node-role.kubernetes.io/worker                  # When node_name is not specified, a node 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.
-    runs: 1                                                         # Number of times to inject each scenario under actions (will perform on same node each time).
-    timeout: 120                                                    # Duration to wait for completion of node scenario injection.
-    cloud_type: aws                                                 # Cloud type on which Kubernetes/OpenShift runs.
-  - actions:
-    - node_reboot_scenario
-    node_name:
-    label_selector: node-role.kubernetes.io/infra
-    instance_count: 1
-    timeout: 120
-    cloud_type: azure
-  - actions:
-    - node_crash_scenario
-    node_name:
-    label_selector: node-role.kubernetes.io/infra
-    instance_count: 1
-    timeout: 120
-  - actions:
-    - stop_start_helper_node_scenario                               # Node chaos scenario for helper node.
-    instance_count: 1
-    timeout: 120
-    helper_node_ip:                                                 # ip address of the helper node.
-    service:                                                        # Check status of the services on the helper node.
-      - haproxy
-      - dhcpd
-      - named
-    ssh_private_key: /root/.ssh/id_rsa                              # ssh key to access the helper node.
-    cloud_type: openstack
-  - actions:
-    - node_stop_start_scenario
-    node_name:
-    label_selector: node-role.kubernetes.io/worker
-    instance_count: 1
-    timeout: 120
-    cloud_type: bm
-    bmc_user: defaultuser                                           # For baremetal (bm) cloud type. The default IPMI username. Optional if specified for all machines.
-    bmc_password: defaultpass                                       # For baremetal (bm) cloud type. The default IPMI password. Optional if specified for all machines.
-    bmc_info:                                                       # This section is here to specify baremetal per-machine info, so it is optional if there is no per-machine info.
-      node-1:                                                       # The node name for the baremetal machine
-        bmc_addr: mgmt-machine1.example.com                         # Optional. For baremetal nodes with the IPMI BMC address missing from 'oc get bmh'.
-      node-2:
-        bmc_addr: mgmt-machine2.example.com
-        bmc_user: user                                              # The baremetal IPMI user. Overrides the default IPMI user specified above. Optional if the default is set.
-        bmc_password: pass                                          # The baremetal IPMI password. Overrides the default IPMI user specified above. Optional if the default is set.
-```

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

@@ -1,40 +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
-- id: wait-for-pods
-  config:
-    namespace_pattern: ^kube-system$
-    label_selector: k8s-app=kube-scheduler
-    count: 3
-```
-
-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 '^.*$' and label_selector to "" to randomly select any namespace in your cluster.
-
-**label_selector:** Label on the namespace you want to delete. Set to "" if you are using the namespace variable.
-
-**delete_count:** Number of namespaces to kill in each run. Based on matching namespace and label specified, default is 1.
-
-**runs:** Number of runs/iterations to kill namespaces, default is 1.
-
-**sleep:** Number of seconds to wait between each iteration/count of killing namespaces. Defaults to 10 seconds if not set
-
-Refer to [namespace_scenarios_example](https://github.com/redhat-chaos/krkn/blob/main/scenarios/regex_namespace.yaml) config file.
-
-```
-scenarios:
-- namespace: "^.*$"
-  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/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/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/redhat-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.

kind-config.yml

@@ -2,6 +2,9 @@ kind: Cluster
 apiVersion: kind.x-k8s.io/v1alpha4
 nodes:
   - role: control-plane
+    extraPortMappings:
+      - containerPort: 30036
+        hostPort: 8888
   - role: control-plane
   - role: control-plane
   - role: worker

kraken/application_outage/actions.py

@@ -1,86 +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.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, 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.startTimeStamp = 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)
-                    # Write the rendered template to a file
-                    with open("kraken_network_policy.yaml", "w") as f:
-                        f.write(rendered_spec)
-                    # Block the traffic by creating network policy
-                    logging.info("Creating the network policy")
-                    runcommand.invoke(
-                        "kubectl create -f %s -n %s --validate=false" % ("kraken_network_policy.yaml", 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")
-                    runcommand.invoke("kubectl delete -f %s -n %s" % ("kraken_network_policy.yaml", 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.exitStatus = 1
-                failed_scenarios.append(app_outage_config)
-                log_exception(app_outage_config)
-            else:
-                scenario_telemetry.exitStatus = 0
-            scenario_telemetry.endTimeStamp = 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