This guide shows you how to use the Skipper ingress controller and Flagger to automate canary deployments.
Flagger requires a Kubernetes cluster v1.16 or newer and Skipper ingress 0.11.40 or newer.
Install Skipper ingress-controller using upstream definition.
Certain arguments are relevant:
- -enable-connection-metrics- -histogram-metric-buckets=.01,1,10,100- -kubernetes- -kubernetes-in-cluster- -kubernetes-path-mode=path-prefix- -metrics-exp-decay-sample- -metrics-flavour=prometheus- -route-backend-metrics- -route-backend-error-counters- -route-response-metrics- -serve-host-metrics- -serve-route-metrics- -whitelisted-healthcheck-cidr=0.0.0.0/0 # permit Kind source health checks
Install Flagger using kustomize:
kustomize build https://github.com/fluxcd/flagger/kustomize/kubernetes | kubectl apply -f -
Flagger takes a Kubernetes deployment and optionally a horizontal pod autoscaler (HPA), then creates a series of objects (Kubernetes deployments, ClusterIP services and canary ingress). These objects expose the application outside the cluster and drive the canary analysis and promotion.
Create a test namespace:
kubectl create ns test
Create a deployment and a horizontal pod autoscaler:
kubectl apply -k https://github.com/fluxcd/flagger//kustomize/podinfo?ref=main
Deploy the load testing service to generate traffic during the canary analysis:
helm upgrade -i flagger-loadtester flagger/loadtester \--namespace=test
Create an ingress definition (replace app.example.com
with your own domain):
apiVersion: networking.k8s.io/v1beta1kind: Ingressmetadata:name: podinfonamespace: testlabels:app: podinfoannotations:kubernetes.io/ingress.class: "skipper"spec:rules:- host: app.example.comhttp:paths:- backend:serviceName: podinfoservicePort: 80
Save the above resource as podinfo-ingress.yaml and then apply it:
kubectl apply -f ./podinfo-ingress.yaml
Create a canary custom resource (replace app.example.com
with your own domain):
apiVersion: flagger.app/v1beta1kind: Canarymetadata:name: podinfonamespace: testspec:provider: skipper# deployment referencetargetRef:apiVersion: apps/v1kind: Deploymentname: podinfo# ingress referenceingressRef:apiVersion: networking.k8s.io/v1beta1kind: Ingressname: podinfo# HPA reference (optional)autoscalerRef:apiVersion: autoscaling/v2beta2kind: HorizontalPodAutoscalername: podinfo# the maximum time in seconds for the canary deployment# to make progress before it is rollback (default 600s)progressDeadlineSeconds: 60service:# ClusterIP port numberport: 80# container port number or nametargetPort: 9898analysis:# schedule interval (default 60s)interval: 10s# max number of failed metric checks before rollbackthreshold: 10# max traffic percentage routed to canary# percentage (0-100)maxWeight: 50# canary increment step# percentage (0-100)stepWeight: 5# Skipper Prometheus checksmetrics:- name: request-success-rateinterval: 1m# minimum req success rate (non 5xx responses)# percentage (0-100)thresholdRange:min: 99- name: request-durationinterval: 1m# maximum req duration P99# millisecondsthresholdRange:max: 500webhooks:- name: gatetype: confirm-rollouturl: http://flagger-loadtester.test/gate/approve- name: acceptance-testtype: pre-rollouturl: http://flagger-loadtester.test/timeout: 10smetadata:type: bashcmd: "curl -sd 'test' http://podinfo-canary/token | grep token"- name: load-testtype: rollouturl: http://flagger-loadtester.test/timeout: 5smetadata:type: cmdcmd: "hey -z 10m -q 10 -c 2 -host app.example.com http://skipper-ingress.kube-system"logCmdOutput: "true"
Save the above resource as podinfo-canary.yaml and then apply it:
kubectl apply -f ./podinfo-canary.yaml
After a couple of seconds Flagger will create the canary objects:
# applieddeployment.apps/podinfohorizontalpodautoscaler.autoscaling/podinfoingress.networking.k8s.io/podinfo-ingresscanary.flagger.app/podinfo​# generateddeployment.apps/podinfo-primaryhorizontalpodautoscaler.autoscaling/podinfo-primaryservice/podinfoservice/podinfo-canaryservice/podinfo-primaryingress.networking.k8s.io/podinfo-canary
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 or MS Teams.
Trigger a canary deployment by updating the container image:
kubectl -n test set image deployment/podinfo \podinfod=stefanprodan/podinfo:4.0.6
Flagger detects that the deployment revision changed and starts a new rollout:
kubectl -n test describe canary/podinfo​Status:Canary Weight: 0Failed Checks: 0Phase: SucceededEvents:New revision detected! Scaling up podinfo.testWaiting for podinfo.test rollout to finish: 0 of 1 updated replicas are availablePre-rollout check acceptance-test passedAdvance podinfo.test canary weight 5Advance podinfo.test canary weight 10Advance podinfo.test canary weight 15Advance podinfo.test canary weight 20Advance podinfo.test canary weight 25Advance podinfo.test canary weight 30Advance podinfo.test canary weight 35Advance podinfo.test canary weight 40Advance podinfo.test canary weight 45Advance podinfo.test canary weight 50Copying podinfo.test template spec to podinfo-primary.testWaiting for podinfo-primary.test rollout to finish: 1 of 2 updated replicas are availableRouting all traffic to primaryPromotion completed! Scaling down podinfo.test
Note that if you apply new changes to the deployment during the canary analysis, Flagger will restart the analysis.
You can monitor all canaries with:
watch kubectl get canaries --all-namespaces​NAMESPACE NAME STATUS WEIGHT LASTTRANSITIONTIMEtest podinfo-2 Progressing 30 2020-08-14T12:32:12Ztest podinfo Succeeded 0 2020-08-14T11:23:88Z
During the canary analysis you can generate HTTP 500 errors to test if Flagger pauses and rolls back the faulted version.
Trigger another canary deployment:
kubectl -n test set image deployment/podinfo \podinfod=stefanprodan/podinfo:4.0.6
Exec into the load tester pod with:
kubectl -n test exec -it deploy/flagger-loadtester bash
Generate HTTP 500 errors:
hey -z 1m -c 5 -q 5 http://app.example.com/status/500
Generate latency:
watch -n 1 curl http://app.example.com/delay/1
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.
kubectl -n flagger-system logs deploy/flagger -f | jq .msg​New revision detected! Scaling up podinfo.testCanary deployment podinfo.test not ready: waiting for rollout to finish: 0 of 1 updated replicas are availableStarting canary analysis for podinfo.testPre-rollout check acceptance-test passedAdvance podinfo.test canary weight 5Advance podinfo.test canary weight 10Advance podinfo.test canary weight 15Advance podinfo.test canary weight 20Halt podinfo.test advancement success rate 53.42% < 99%Halt podinfo.test advancement success rate 53.19% < 99%Halt podinfo.test advancement success rate 48.05% < 99%Rolling back podinfo.test failed checks threshold reached 3Canary failed! Scaling down podinfo.test
The canary analysis can be extended with Prometheus queries.
Create a metric template and apply it on the cluster:
apiVersion: flagger.app/v1beta1kind: MetricTemplatemetadata:name: latencynamespace: testspec:provider:type: prometheusaddress: http://flagger-prometheus.flagger-system:9090query: |histogram_quantile(0.99,sum(rate(skipper_serve_route_duration_seconds_bucket{route=~"{{ printf "kube(ew)?_%s__%s_canary__.*__%s_canary(_[0-9]+)?" namespace ingress service }}",le="+Inf"}[1m])) by (le))
Edit the canary analysis and add the latency check:
analysis:metrics:- name: "latency"templateRef:name: latencythresholdRange:max: 0.5interval: 1m
The threshold is set to 500ms so if the average request duration in the last minute goes over half a second then the analysis will fail and the canary will not be promoted.
Trigger a canary deployment by updating the container image:
kubectl -n test set image deployment/podinfo \podinfod=stefanprodan/podinfo:4.0.6
Generate high response latency:
watch curl http://app.example.com/delay/2
Watch Flagger logs:
kubectl -n flagger-system logs deployment/flagger -f | jq .msg​Starting canary deployment for podinfo.testAdvance podinfo.test canary weight 5Advance podinfo.test canary weight 10Advance podinfo.test canary weight 15Halt podinfo.test advancement latency 1.20 > 0.5Halt podinfo.test advancement latency 1.45 > 0.5Halt podinfo.test advancement latency 1.60 > 0.5Halt podinfo.test advancement latency 1.69 > 0.5Halt podinfo.test advancement latency 1.70 > 0.5Rolling back podinfo.test failed checks threshold reached 5Canary failed! Scaling down podinfo.test
If you have alerting configured, Flagger will send a notification with the reason why the canary failed.