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296 lines
8.5 KiB
Markdown
296 lines
8.5 KiB
Markdown
# SMI Istio Canary Deployments
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This guide shows you how to use the SMI Istio adapter and Flagger to automate canary deployments.
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## Prerequisites
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* Kubernetes > 1.13
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* Istio > 1.0
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## Install Istio SMI adapter
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Install the SMI adapter:
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```bash
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kubectl apply -f https://raw.githubusercontent.com/deislabs/smi-adapter-istio/master/deploy/crds/crds.yaml
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kubectl apply -f https://raw.githubusercontent.com/deislabs/smi-adapter-istio/master/deploy/operator-and-rbac.yaml
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```
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Create a generic Istio gateway to expose services outside the mesh on HTTP:
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```yaml
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apiVersion: networking.istio.io/v1alpha3
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kind: Gateway
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metadata:
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name: public-gateway
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namespace: istio-system
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spec:
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selector:
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istio: ingressgateway
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servers:
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- port:
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number: 80
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name: http
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protocol: HTTP
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hosts:
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- "*"
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```
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Save the above resource as public-gateway.yaml and then apply it:
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```bash
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kubectl apply -f ./public-gateway.yaml
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```
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Find the Gateway load balancer IP and add a DNS record for it:
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```bash
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kubectl -n istio-system get svc/istio-ingressgateway -ojson | jq -r .status.loadBalancer.ingress[0].ip
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```
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## Install Flagger and Grafana
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Add Flagger Helm repository:
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```bash
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helm repo add flagger https://flagger.app
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```
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Deploy Flagger in the _**istio-system**_ namespace:
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```bash
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helm upgrade -i flagger flagger/flagger \
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--namespace=istio-system \
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--set meshProvider=smi:istio
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```
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Flagger comes with a Grafana dashboard made for monitoring the canary deployments.
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Deploy Grafana in the _**istio-system**_ namespace:
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```bash
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helm upgrade -i flagger-grafana flagger/grafana \
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--namespace=istio-system \
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--set url=http://prometheus.istio-system:9090
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```
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You can access Grafana using port forwarding:
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```bash
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kubectl -n istio-system port-forward svc/flagger-grafana 3000:80
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```
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## Workloads bootstrap
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Create a test namespace with Istio sidecar injection enabled:
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Create a test namespace and enable Linkerd proxy injection:
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```bash
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kubectl create ns test
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kubectl label namespace test istio-injection=enabled
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```
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Create a deployment and a horizontal pod autoscaler:
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```bash
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kubectl apply -k github.com/weaveworks/flagger//kustomize/podinfo
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```
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Deploy the load testing service to generate traffic during the canary analysis:
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```bash
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kubectl apply -k github.com/weaveworks/flagger//kustomize/tester
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```
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Create a canary custom resource \(replace example.com with your own domain\):
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```yaml
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apiVersion: flagger.app/v1beta1
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kind: Canary
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metadata:
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name: podinfo
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namespace: test
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spec:
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# deployment reference
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targetRef:
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apiVersion: apps/v1
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kind: Deployment
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name: podinfo
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# the maximum time in seconds for the canary deployment
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# to make progress before it is rollback (default 600s)
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progressDeadlineSeconds: 60
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# HPA reference (optional)
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autoscalerRef:
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apiVersion: autoscaling/v2beta1
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kind: HorizontalPodAutoscaler
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name: podinfo
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service:
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# container port
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port: 9898
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# Istio gateways (optional)
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gateways:
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- public-gateway.istio-system.svc.cluster.local
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# Istio virtual service host names (optional)
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hosts:
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- app.example.com
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analysis:
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# schedule interval (default 60s)
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interval: 10s
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# max number of failed metric checks before rollback
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threshold: 5
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# max traffic percentage routed to canary
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# percentage (0-100)
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maxWeight: 50
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# canary increment step
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# percentage (0-100)
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stepWeight: 10
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metrics:
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- name: request-success-rate
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# minimum req success rate (non 5xx responses)
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# percentage (0-100)
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thresholdRange:
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min: 99
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interval: 1m
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- name: request-duration
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# maximum req duration P99
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# milliseconds
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thresholdRange:
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max: 500
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interval: 30s
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# generate traffic during analysis
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webhooks:
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- name: load-test
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url: http://flagger-loadtester.test/
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timeout: 5s
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metadata:
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cmd: "hey -z 1m -q 10 -c 2 http://podinfo.test:9898/"
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```
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Save the above resource as podinfo-canary.yaml and then apply it:
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```bash
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kubectl apply -f ./podinfo-canary.yaml
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```
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After a couple of seconds Flagger will create the canary objects:
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```bash
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# applied
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deployment.apps/podinfo
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horizontalpodautoscaler.autoscaling/podinfo
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canary.flagger.app/podinfo
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# generated
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deployment.apps/podinfo-primary
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horizontalpodautoscaler.autoscaling/podinfo-primary
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service/podinfo
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service/podinfo-canary
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service/podinfo-primary
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trafficsplits.split.smi-spec.io/podinfo
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```
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## Automated canary promotion
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Flagger implements a control loop that gradually shifts traffic to the canary while measuring key performance indicators like HTTP requests success rate, requests average duration and pod health. Based on analysis of the KPIs a canary is promoted or aborted, and the analysis result is published to Slack.
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Trigger a canary deployment by updating the container image:
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```bash
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kubectl -n test set image deployment/podinfo \
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podinfod=quay.io/stefanprodan/podinfo:3.1.1
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```
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Flagger detects that the deployment revision changed and starts a new rollout:
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```text
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kubectl -n istio-system logs deployment/flagger -f | jq .msg
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New revision detected podinfo.test
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Scaling up podinfo.test
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Waiting for podinfo.test rollout to finish: 0 of 1 updated replicas are available
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Advance podinfo.test canary weight 5
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Advance podinfo.test canary weight 10
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Advance podinfo.test canary weight 15
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Advance podinfo.test canary weight 20
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Advance podinfo.test canary weight 25
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Advance podinfo.test canary weight 30
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Advance podinfo.test canary weight 35
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Advance podinfo.test canary weight 40
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Advance podinfo.test canary weight 45
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Advance podinfo.test canary weight 50
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Copying podinfo.test template spec to podinfo-primary.test
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Waiting for podinfo-primary.test rollout to finish: 1 of 2 updated replicas are available
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Promotion completed! Scaling down podinfo.test
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```
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**Note** that if you apply new changes to the deployment during the canary analysis, Flagger will restart the analysis.
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During the analysis the canary’s progress can be monitored with Grafana. The Istio dashboard URL is [http://localhost:3000/d/flagger-istio/istio-canary?refresh=10s&orgId=1&var-namespace=test&var-primary=podinfo-primary&var-canary=podinfo](http://localhost:3000/d/flagger-istio/istio-canary?refresh=10s&orgId=1&var-namespace=test&var-primary=podinfo-primary&var-canary=podinfo)
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You can monitor all canaries with:
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```bash
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watch kubectl get canaries --all-namespaces
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NAMESPACE NAME STATUS WEIGHT LASTTRANSITIONTIME
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test podinfo Progressing 15 2019-05-16T14:05:07Z
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prod frontend Succeeded 0 2019-05-15T16:15:07Z
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prod backend Failed 0 2019-05-14T17:05:07Z
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```
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## Automated rollback
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During the canary analysis you can generate HTTP 500 errors and high latency to test if Flagger pauses the rollout.
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Create a tester pod and exec into it:
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```bash
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kubectl -n test run tester \
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--image=quay.io/stefanprodan/podinfo:3.1.2 \
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-- ./podinfo --port=9898
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kubectl -n test exec -it tester-xx-xx sh
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```
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Generate HTTP 500 errors:
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```bash
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watch curl http://podinfo-canary:9898/status/500
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```
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Generate latency:
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```bash
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watch curl http://podinfo-canary:9898/delay/1
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```
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When the number of failed checks reaches the canary analysis threshold, the traffic is routed back to the primary, the canary is scaled to zero and the rollout is marked as failed.
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```text
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kubectl -n test describe canary/podinfo
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Status:
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Canary Weight: 0
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Failed Checks: 10
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Phase: Failed
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Events:
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Type Reason Age From Message
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---- ------ ---- ---- -------
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Normal Synced 3m flagger Starting canary deployment for podinfo.test
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Normal Synced 3m flagger Advance podinfo.test canary weight 5
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Normal Synced 3m flagger Advance podinfo.test canary weight 10
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Normal Synced 3m flagger Advance podinfo.test canary weight 15
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Normal Synced 3m flagger Halt podinfo.test advancement success rate 69.17% < 99%
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Normal Synced 2m flagger Halt podinfo.test advancement success rate 61.39% < 99%
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Normal Synced 2m flagger Halt podinfo.test advancement success rate 55.06% < 99%
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Normal Synced 2m flagger Halt podinfo.test advancement success rate 47.00% < 99%
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Normal Synced 2m flagger (combined from similar events): Halt podinfo.test advancement success rate 38.08% < 99%
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Warning Synced 1m flagger Rolling back podinfo.test failed checks threshold reached 10
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Warning Synced 1m flagger Canary failed! Scaling down podinfo.test
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```
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