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Add Gloo canary deployment docs and diagram
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stefanprodan
@@ -33,4 +33,4 @@ spec:
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timeout: 5s
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metadata:
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type: cmd
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cmd: "hey -z 1m -q 10 -c 2 http://gloo.exmaple.com/"
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cmd: "hey -z 1m -q 10 -c 2 http://gloo.example.com/"
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# NGNIX Ingress Controller Canary Deployments
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This guide shows you how to use the [Gloo](https://gloo.solo.io/) ingress controller and Flagger to automate canary deployments.
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### Prerequisites
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Flagger requires a Kubernetes cluster **v1.11** or newer and Gloo ingress **0.13.29** or newer.
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Install Gloo with Helm:
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```bash
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helm repo add gloo https://storage.googleapis.com/solo-public-helm
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helm upgrade -i gloo gloo/gloo \
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--namespace gloo-system
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```
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Install Flagger and the Prometheus add-on in the same namespace as Gloo:
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```bash
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helm repo add flagger https://flagger.app
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helm upgrade -i flagger flagger/flagger \
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--namespace gloo-system \
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--set prometheus.install=true \
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--set meshProvider=gloo
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```
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Optionally you can enable Slack notifications:
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```bash
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helm upgrade -i flagger flagger/flagger \
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--reuse-values \
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--namespace gloo-system \
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--set slack.url=https://hooks.slack.com/services/YOUR/SLACK/WEBHOOK \
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--set slack.channel=general \
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--set slack.user=flagger
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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 Gloo upstream groups).
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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 -f ${REPO}/artifacts/gloo/deployment.yaml
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kubectl apply -f ${REPO}/artifacts/gloo/hpa.yaml
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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 virtual service definition that references an upstream group that will be generated by Flagger
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(replace `app.example.com` with your own domain):
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```yaml
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apiVersion: gateway.solo.io/v1
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kind: VirtualService
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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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virtualHost:
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domains:
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- 'app.example.com'
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name: podinfo.test
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routes:
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- matcher:
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prefix: /
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routeAction:
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upstreamGroup:
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name: podinfo
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namespace: test
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```
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Save the above resource as podinfo-virtualservice.yaml and then apply it:
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```bash
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kubectl apply -f ./podinfo-virtualservice.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/v1alpha3
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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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# 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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# 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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# container port
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port: 9898
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canaryAnalysis:
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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: 5
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# Gloo Prometheus checks
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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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threshold: 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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threshold: 500
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interval: 30s
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# load testing (optional)
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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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type: cmd
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cmd: "hey -z 1m -q 10 -c 2 http://app.example.com/"
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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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virtualservices.gateway.solo.io/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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upstreamgroups.gloo.solo.io/podinfo
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```
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When the bootstrap finishes Flagger will set the canary status to initialized:
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```bash
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kubectl -n test get canary podinfo
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NAME STATUS WEIGHT LASTTRANSITIONTIME
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podinfo Initialized 0 2019-05-17T08:09:51Z
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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
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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.
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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:1.4.1
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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 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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Type Reason Age From Message
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---- ------ ---- ---- -------
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Normal Synced 3m flagger New revision detected podinfo.test
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Normal Synced 3m flagger Scaling up podinfo.test
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Warning Synced 3m flagger Waiting for podinfo.test rollout to finish: 0 of 1 updated replicas are available
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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 2m flagger Advance podinfo.test canary weight 20
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Normal Synced 2m flagger Advance podinfo.test canary weight 25
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Normal Synced 1m flagger Advance podinfo.test canary weight 30
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Normal Synced 1m flagger Advance podinfo.test canary weight 35
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Normal Synced 55s flagger Advance podinfo.test canary weight 40
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Normal Synced 45s flagger Advance podinfo.test canary weight 45
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Normal Synced 35s flagger Advance podinfo.test canary weight 50
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Normal Synced 25s flagger Copying podinfo.test template spec to podinfo-primary.test
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Warning Synced 15s flagger Waiting for podinfo-primary.test rollout to finish: 1 of 2 updated replicas are available
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Normal Synced 5s flagger 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 Progressing 15 2019-05-17T14:05:07Z
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prod frontend Succeeded 0 2019-05-17T16:15:07Z
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prod backend Failed 0 2019-05-17T17:05:07Z
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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 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=quay.io/stefanprodan/podinfo:1.4.2
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```
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Generate HTTP 500 errors:
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```bash
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watch curl http://app.example.com/status/500
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```
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Generate high 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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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 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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### Custom metrics
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The canary analysis can be extended with Prometheus queries.
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The demo app is instrumented with Prometheus so you can create a custom check that will use the HTTP request duration
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histogram to validate the canary.
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Edit the canary analysis and add the following metric:
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```yaml
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canaryAnalysis:
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metrics:
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- name: "404s percentage"
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threshold: 5
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query: |
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100 - sum(
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rate(
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http_request_duration_seconds_count{
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kubernetes_namespace="test",
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kubernetes_pod_name=~"podinfo-[0-9a-zA-Z]+(-[0-9a-zA-Z]+)"
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status!="404"
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}[1m]
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)
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)
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/
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sum(
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rate(
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http_request_duration_seconds_count{
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kubernetes_namespace="test",
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kubernetes_pod_name=~"podinfo-[0-9a-zA-Z]+(-[0-9a-zA-Z]+)"
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}[1m]
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)
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) * 100
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```
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The above configuration validates the canary by checking if the HTTP 404 req/sec percentage is below 5
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percent of the total traffic. If the 404s rate reaches the 5% threshold, then the canary fails.
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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:1.4.3
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```
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Generate 404s:
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```bash
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watch curl http://app.example.com/status/400
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```
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Watch Flagger logs:
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```
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kubectl -n gloo-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 404s percentage 6.20 > 5
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Halt podinfo.test advancement 404s percentage 6.45 > 5
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Halt podinfo.test advancement 404s percentage 7.60 > 5
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Halt podinfo.test advancement 404s percentage 8.69 > 5
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Halt podinfo.test advancement 404s percentage 9.70 > 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 Slack configured, Flagger will send a notification with the reason why the canary failed.
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