NGINX Canary Deployments

This guide shows you how to use the NGINX ingress controller and Flagger to automate canary deployments and A/B testing.

Flagger NGINX Ingress Controller

Prerequisites

Flagger requires a Kubernetes cluster v1.11 or newer and NGINX ingress 0.24 or newer.

Install NGINX with Helm v3:

kubectl create ns ingress-nginx
helm upgrade -i nginx-ingress stable/nginx-ingress \
--namespace ingress-nginx \
--set controller.stats.enabled=true \
--set controller.metrics.enabled=true \
--set controller.podAnnotations."prometheus\.io/scrape"=true \
--set controller.podAnnotations."prometheus\.io/port"=10254

Install Flagger and the Prometheus add-on in the same namespace as NGINX:

helm repo add flagger https://flagger.app

helm upgrade -i flagger flagger/flagger \
--namespace ingress-nginx \
--set prometheus.install=true \
--set meshProvider=nginx

Optionally you can enable Slack notifications:

helm upgrade -i flagger flagger/flagger \
--reuse-values \
--namespace ingress-nginx \
--set slack.url=https://hooks.slack.com/services/YOUR/SLACK/WEBHOOK \
--set slack.channel=general \
--set slack.user=flagger

Bootstrap

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 github.com/weaveworks/flagger//kustomize/podinfo

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: extensions/v1beta1
kind: Ingress
metadata:
  name: podinfo
  namespace: test
  labels:
    app: podinfo
  annotations:
    kubernetes.io/ingress.class: "nginx"
spec:
  rules:
    - host: app.example.com
      http:
        paths:
          - backend:
              serviceName: podinfo
              servicePort: 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/v1beta1
kind: Canary
metadata:
  name: podinfo
  namespace: test
spec:
  provider: nginx
  # deployment reference
  targetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: podinfo
  # ingress reference
  ingressRef:
    apiVersion: extensions/v1beta1
    kind: Ingress
    name: podinfo
  # HPA reference (optional)
  autoscalerRef:
    apiVersion: autoscaling/v2beta1
    kind: HorizontalPodAutoscaler
    name: podinfo
  # the maximum time in seconds for the canary deployment
  # to make progress before it is rollback (default 600s)
  progressDeadlineSeconds: 60
  service:
    # ClusterIP port number
    port: 80
    # container port number or name
    targetPort: 9898
  analysis:
    # schedule interval (default 60s)
    interval: 10s
    # max number of failed metric checks before rollback
    threshold: 10
    # max traffic percentage routed to canary
    # percentage (0-100)
    maxWeight: 50
    # canary increment step
    # percentage (0-100)
    stepWeight: 5
    # NGINX Prometheus checks
    metrics:
    - name: request-success-rate
      # minimum req success rate (non 5xx responses)
      # percentage (0-100)
      thresholdRange:
        min: 99
      interval: 1m
    # testing (optional)
    webhooks:
      - name: acceptance-test
        type: pre-rollout
        url: http://flagger-loadtester.test/
        timeout: 30s
        metadata:
          type: bash
          cmd: "curl -sd 'test' http://podinfo-canary/token | grep token"
      - name: load-test
        url: http://flagger-loadtester.test/
        timeout: 5s
        metadata:
          cmd: "hey -z 1m -q 10 -c 2 http://app.example.com/"

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:

# applied 
deployment.apps/podinfo
horizontalpodautoscaler.autoscaling/podinfo
ingresses.extensions/podinfo
canary.flagger.app/podinfo

# generated 
deployment.apps/podinfo-primary
horizontalpodautoscaler.autoscaling/podinfo-primary
service/podinfo
service/podinfo-canary
service/podinfo-primary
ingresses.extensions/podinfo-canary

Automated canary promotion

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.

Flagger Canary Stages

Trigger a canary deployment by updating the container image:

kubectl -n test set image deployment/podinfo \
podinfod=stefanprodan/podinfo:3.1.1

Flagger detects that the deployment revision changed and starts a new rollout:

kubectl -n test describe canary/podinfo

Status:
  Canary Weight:         0
  Failed Checks:         0
  Phase:                 Succeeded
Events:
  Type     Reason  Age   From     Message
  ----     ------  ----  ----     -------
  Normal   Synced  3m    flagger  New revision detected podinfo.test
  Normal   Synced  3m    flagger  Scaling up podinfo.test
  Warning  Synced  3m    flagger  Waiting for podinfo.test rollout to finish: 0 of 1 updated replicas are available
  Normal   Synced  3m    flagger  Advance podinfo.test canary weight 5
  Normal   Synced  3m    flagger  Advance podinfo.test canary weight 10
  Normal   Synced  3m    flagger  Advance podinfo.test canary weight 15
  Normal   Synced  2m    flagger  Advance podinfo.test canary weight 20
  Normal   Synced  2m    flagger  Advance podinfo.test canary weight 25
  Normal   Synced  1m    flagger  Advance podinfo.test canary weight 30
  Normal   Synced  1m    flagger  Advance podinfo.test canary weight 35
  Normal   Synced  55s   flagger  Advance podinfo.test canary weight 40
  Normal   Synced  45s   flagger  Advance podinfo.test canary weight 45
  Normal   Synced  35s   flagger  Advance podinfo.test canary weight 50
  Normal   Synced  25s   flagger  Copying podinfo.test template spec to podinfo-primary.test
  Warning  Synced  15s   flagger  Waiting for podinfo-primary.test rollout to finish: 1 of 2 updated replicas are available
  Normal   Synced  5s    flagger  Promotion 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   LASTTRANSITIONTIME
test        podinfo   Progressing   15       2019-05-06T14:05:07Z
prod        frontend  Succeeded     0        2019-05-05T16:15:07Z
prod        backend   Failed        0        2019-05-04T17:05:07Z

Automated rollback

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:3.1.2

Generate HTTP 500 errors:

watch curl http://app.example.com/status/500

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 test describe canary/podinfo

Status:
  Canary Weight:         0
  Failed Checks:         10
  Phase:                 Failed
Events:
  Type     Reason  Age   From     Message
  ----     ------  ----  ----     -------
  Normal   Synced  3m    flagger  Starting canary deployment for podinfo.test
  Normal   Synced  3m    flagger  Advance podinfo.test canary weight 5
  Normal   Synced  3m    flagger  Advance podinfo.test canary weight 10
  Normal   Synced  3m    flagger  Advance podinfo.test canary weight 15
  Normal   Synced  3m    flagger  Halt podinfo.test advancement success rate 69.17% < 99%
  Normal   Synced  2m    flagger  Halt podinfo.test advancement success rate 61.39% < 99%
  Normal   Synced  2m    flagger  Halt podinfo.test advancement success rate 55.06% < 99%
  Normal   Synced  2m    flagger  Halt podinfo.test advancement success rate 47.00% < 99%
  Normal   Synced  2m    flagger  (combined from similar events): Halt podinfo.test advancement success rate 38.08% < 99%
  Warning  Synced  1m    flagger  Rolling back podinfo.test failed checks threshold reached 10
  Warning  Synced  1m    flagger  Canary failed! Scaling down podinfo.test

Custom metrics

The canary analysis can be extended with Prometheus queries.

The demo app is instrumented with Prometheus so you can create a custom check that will use the HTTP request duration histogram to validate the canary.

Create a metric template and apply it on the cluster:

apiVersion: flagger.app/v1beta1
kind: MetricTemplate
metadata:
  name: latency
  namespace: test
spec:
  provider:
    type: prometheus
    address: http://flagger-promethues.ingress-nginx:9090
  query: |
    histogram_quantile(0.99,
      sum(
        rate(
          http_request_duration_seconds_bucket{
            kubernetes_namespace="{{ namespace }}",
            kubernetes_pod_name=~"{{ target }}-[0-9a-zA-Z]+(-[0-9a-zA-Z]+)"
          }[1m]
        )
      ) by (le)
    )

Edit the canary analysis and add the latency check:

  analysis:
    metrics:
    - name: "latency"
      templateRef:
        name: latency
      thresholdRange:
        max: 0.5
      interval: 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:3.1.3

Generate high response latency:

watch curl http://app.exmaple.com/delay/2

Watch Flagger logs:

kubectl -n nginx-ingress logs deployment/flagger -f | jq .msg

Starting canary deployment for podinfo.test
Advance podinfo.test canary weight 5
Advance podinfo.test canary weight 10
Advance podinfo.test canary weight 15
Halt podinfo.test advancement latency 1.20 > 0.5
Halt podinfo.test advancement latency 1.45 > 0.5
Halt podinfo.test advancement latency 1.60 > 0.5
Halt podinfo.test advancement latency 1.69 > 0.5
Halt podinfo.test advancement latency 1.70 > 0.5
Rolling back podinfo.test failed checks threshold reached 5
Canary failed! Scaling down podinfo.test

If you have alerting configured, Flagger will send a notification with the reason why the canary failed.

A/B Testing

Besides weighted routing, Flagger can be configured to route traffic to the canary based on HTTP match conditions. In an A/B testing scenario, you'll be using HTTP headers or cookies to target a certain segment of your users. This is particularly useful for frontend applications that require session affinity.

Flagger A/B Testing Stages

Edit the canary analysis, remove the max/step weight and add the match conditions and iterations:

  analysis:
    interval: 1m
    threshold: 10
    iterations: 10
    match:
      # curl -H 'X-Canary: insider' http://app.example.com
      - headers:
          x-canary:
            exact: "insider"
      # curl -b 'canary=always' http://app.example.com
      - headers:
          cookie:
            exact: "canary"
    metrics:
    - name: request-success-rate
      thresholdRange:
        min: 99
      interval: 1m
    webhooks:
      - name: load-test
        url: http://flagger-loadtester.test/
        timeout: 5s
        metadata:
          cmd: "hey -z 1m -q 10 -c 2 -H 'Cookie: canary=always' http://app.example.com/"

The above configuration will run an analysis for ten minutes targeting users that have a canary cookie set to always or those that call the service using the X-Canary: insider header.

Trigger a canary deployment by updating the container image:

kubectl -n test set image deployment/podinfo \
podinfod=stefanprodan/podinfo:3.1.4

Flagger detects that the deployment revision changed and starts the A/B testing:

kubectl -n test describe canary/podinfo

Status:
  Failed Checks:         0
  Phase:                 Succeeded
Events:
  Type     Reason  Age   From     Message
  ----     ------  ----  ----     -------
  Normal   Synced  3m    flagger  New revision detected podinfo.test
  Normal   Synced  3m    flagger  Scaling up podinfo.test
  Warning  Synced  3m    flagger  Waiting for podinfo.test rollout to finish: 0 of 1 updated replicas are available
  Normal   Synced  3m    flagger  Advance podinfo.test canary iteration 1/10
  Normal   Synced  3m    flagger  Advance podinfo.test canary iteration 2/10
  Normal   Synced  3m    flagger  Advance podinfo.test canary iteration 3/10
  Normal   Synced  2m    flagger  Advance podinfo.test canary iteration 4/10
  Normal   Synced  2m    flagger  Advance podinfo.test canary iteration 5/10
  Normal   Synced  1m    flagger  Advance podinfo.test canary iteration 6/10
  Normal   Synced  1m    flagger  Advance podinfo.test canary iteration 7/10
  Normal   Synced  55s   flagger  Advance podinfo.test canary iteration 8/10
  Normal   Synced  45s   flagger  Advance podinfo.test canary iteration 9/10
  Normal   Synced  35s   flagger  Advance podinfo.test canary iteration 10/10
  Normal   Synced  25s   flagger  Copying podinfo.test template spec to podinfo-primary.test
  Warning  Synced  15s   flagger  Waiting for podinfo-primary.test rollout to finish: 1 of 2 updated replicas are available
  Normal   Synced  5s    flagger  Promotion completed! Scaling down podinfo.test

The above procedure can be extended with custom metrics checks, webhooks, manual promotion approval and Slack or MS Teams notifications.