mirror of https://github.com/fluxcd/flagger.git
380 lines
10 KiB
Markdown
380 lines
10 KiB
Markdown
# Skipper Canary Deployments
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This guide shows you how to use the [Skipper ingress controller](https://opensource.zalando.com/skipper/kubernetes/ingress-controller/) and Flagger to automate canary deployments.
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## Prerequisites
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Flagger requires a Kubernetes cluster **v1.19** or newer and Skipper ingress **v0.13** or newer.
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Install Skipper ingress-controller using [upstream definition](https://opensource.zalando.com/skipper/kubernetes/ingress-controller/#install-skipper-as-ingress-controller).
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Certain arguments are relevant:
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```yaml
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- -enable-connection-metrics
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- -histogram-metric-buckets=.01,1,10,100
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- -kubernetes
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- -kubernetes-in-cluster
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- -kubernetes-path-mode=path-prefix
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- -metrics-exp-decay-sample
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- -metrics-flavour=prometheus
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- -route-backend-metrics
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- -route-backend-error-counters
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- -route-response-metrics
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- -serve-host-metrics
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- -serve-route-metrics
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- -whitelisted-healthcheck-cidr=0.0.0.0/0 # permit Kind source health checks
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```
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Install Flagger using kustomize:
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```bash
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kustomize build https://github.com/fluxcd/flagger/kustomize/kubernetes | kubectl apply -f -
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```
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## Bootstrap
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Flagger takes a Kubernetes deployment and optionally a horizontal pod autoscaler (HPA),
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then creates a series of objects (Kubernetes deployments, ClusterIP services and canary ingress).
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These objects expose the application outside the cluster and drive the canary analysis and promotion.
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Create a test namespace:
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```bash
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kubectl create ns test
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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 https://github.com/fluxcd/flagger//kustomize/podinfo?ref=main
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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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helm upgrade -i flagger-loadtester flagger/loadtester \
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--namespace=test
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```
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Create an ingress definition \(replace `app.example.com` with your own domain\):
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```yaml
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apiVersion: networking.k8s.io/v1
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kind: Ingress
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metadata:
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name: podinfo
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namespace: test
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labels:
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app: podinfo
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annotations:
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kubernetes.io/ingress.class: "skipper"
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spec:
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rules:
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- host: "app.example.com"
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http:
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paths:
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- pathType: Prefix
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path: "/"
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backend:
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service:
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name: podinfo
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port:
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number: 80
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```
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Save the above resource as podinfo-ingress.yaml and then apply it:
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```bash
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kubectl apply -f ./podinfo-ingress.yaml
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```
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Create a canary custom resource (replace `app.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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provider: skipper
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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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# ingress reference
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ingressRef:
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apiVersion: networking.k8s.io/v1
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kind: Ingress
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name: podinfo
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# HPA reference (optional)
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autoscalerRef:
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apiVersion: autoscaling/v2
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kind: HorizontalPodAutoscaler
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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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service:
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# ClusterIP port number
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port: 80
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# container port number or name
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targetPort: 9898
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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: 10
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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: 5
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# Skipper Prometheus checks
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metrics:
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- name: request-success-rate
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interval: 1m
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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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- name: request-duration
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interval: 1m
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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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webhooks:
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- name: gate
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type: confirm-rollout
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url: http://flagger-loadtester.test/gate/approve
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- name: acceptance-test
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type: pre-rollout
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url: http://flagger-loadtester.test/
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timeout: 10s
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metadata:
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type: bash
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cmd: "curl -sd 'test' http://podinfo-canary/token | grep token"
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- name: load-test
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type: rollout
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url: http://flagger-loadtester.test/
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timeout: 5s
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metadata:
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type: cmd
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cmd: "hey -z 10m -q 10 -c 2 -host app.example.com http://skipper-ingress.kube-system"
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logCmdOutput: "true"
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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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ingress.networking.k8s.io/podinfo-ingress
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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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ingress.networking.k8s.io/podinfo-canary
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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
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key performance indicators like HTTP requests success rate, requests average duration and pod health.
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Based on analysis of the KPIs a canary is promoted or aborted, and the analysis result is published to Slack or MS Teams.
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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=stefanprodan/podinfo:4.0.6
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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 test describe canary/podinfo
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Status:
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Canary Weight: 0
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Failed Checks: 0
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Phase: Succeeded
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Events:
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New revision detected! 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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Pre-rollout check acceptance-test passed
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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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Routing all traffic to primary
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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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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-2 Progressing 30 2020-08-14T12:32:12Z
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test podinfo Succeeded 0 2020-08-14T11:23:88Z
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```
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## Automated rollback
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During the canary analysis you can generate HTTP 500 errors to test if Flagger pauses and rolls back the faulted version.
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Trigger another canary deployment:
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```bash
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kubectl -n test set image deployment/podinfo \
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podinfod=stefanprodan/podinfo:4.0.6
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```
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Exec into the load tester pod with:
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```bash
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kubectl -n test exec -it deploy/flagger-loadtester bash
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```
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Generate HTTP 500 errors:
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```bash
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hey -z 1m -c 5 -q 5 http://app.example.com/status/500
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```
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Generate latency:
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```bash
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watch -n 1 curl http://app.example.com/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,
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the canary is scaled to zero and the rollout is marked as failed.
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```text
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kubectl -n flagger-system logs deploy/flagger -f | jq .msg
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New revision detected! Scaling up podinfo.test
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Canary deployment podinfo.test not ready: waiting for rollout to finish: 0 of 1 updated replicas are available
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Starting canary analysis for podinfo.test
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Pre-rollout check acceptance-test passed
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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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Halt podinfo.test advancement success rate 53.42% < 99%
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Halt podinfo.test advancement success rate 53.19% < 99%
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Halt podinfo.test advancement success rate 48.05% < 99%
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Rolling back podinfo.test failed checks threshold reached 3
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Canary failed! Scaling down podinfo.test
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```
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## Custom metrics
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The canary analysis can be extended with Prometheus queries.
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Create a metric template and apply it on the cluster:
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```yaml
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apiVersion: flagger.app/v1beta1
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kind: MetricTemplate
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metadata:
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name: latency
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namespace: test
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spec:
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provider:
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type: prometheus
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address: http://flagger-prometheus.flagger-system:9090
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query: |
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histogram_quantile(0.99,
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sum(
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rate(
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skipper_serve_route_duration_seconds_bucket{
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route=~"{{ printf "kube(ew)?_%s__%s_canary__.*__%s_canary(_[0-9]+)?" namespace ingress service }}",
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le="+Inf"
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}[1m]
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)
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) by (le)
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)
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```
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Edit the canary analysis and add the latency check:
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```yaml
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analysis:
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metrics:
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- name: "latency"
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templateRef:
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name: latency
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thresholdRange:
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max: 0.5
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interval: 1m
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```
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The threshold is set to 500ms so if the average request duration in the last minute goes over half a second
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then the analysis will fail and the canary will not be promoted.
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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=stefanprodan/podinfo:4.0.6
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```
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Generate high response latency:
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```bash
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watch curl http://app.example.com/delay/2
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```
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Watch Flagger logs:
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```text
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kubectl -n flagger-system logs deployment/flagger -f | jq .msg
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Starting canary deployment for podinfo.test
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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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Halt podinfo.test advancement latency 1.20 > 0.5
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Halt podinfo.test advancement latency 1.45 > 0.5
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Halt podinfo.test advancement latency 1.60 > 0.5
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Halt podinfo.test advancement latency 1.69 > 0.5
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Halt podinfo.test advancement latency 1.70 > 0.5
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Rolling back podinfo.test failed checks threshold reached 5
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Canary failed! Scaling down podinfo.test
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```
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If you have alerting configured, Flagger will send a notification with the reason why the canary failed.
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