Istio A/B Testing

This guide shows you how to automate A/B testing with Istio and Flagger.

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.

Prerequisites

Flagger requires a Kubernetes cluster v1.16 or newer and Istio v1.0 or newer.

Install Istio with telemetry support and Prometheus:

istioctl manifest install --set profile=default

kubectl apply -f https://raw.githubusercontent.com/istio/istio/release-1.18/samples/addons/prometheus.yaml

Install Flagger in the istio-system namespace:

kubectl apply -k github.com/fluxcd/flagger//kustomize/istio

Create an ingress gateway to expose the demo app outside of the mesh:

apiVersion: networking.istio.io/v1alpha3
kind: Gateway
metadata:
  name: public-gateway
  namespace: istio-system
spec:
  selector:
    istio: ingressgateway
  servers:
    - port:
        number: 80
        name: http
        protocol: HTTP
      hosts:
        - "*"

Bootstrap

Create a test namespace with Istio sidecar injection enabled:

kubectl create ns test
kubectl label namespace test istio-injection=enabled

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:

kubectl apply -k https://github.com/fluxcd/flagger//kustomize/tester?ref=main

Create a canary custom resource (replace example.com with your own domain):

apiVersion: flagger.app/v1beta1
kind: Canary
metadata:
  name: podinfo
  namespace: test
spec:
  # deployment reference
  targetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: podinfo
  # the maximum time in seconds for the canary deployment
  # to make progress before it is rollback (default 600s)
  progressDeadlineSeconds: 60
  # HPA reference (optional)
  autoscalerRef:
    apiVersion: autoscaling/v2
    kind: HorizontalPodAutoscaler
    name: podinfo
  service:
    # container port
    port: 9898
    # Istio gateways (optional)
    gateways:
    - istio-system/public-gateway
    # Istio virtual service host names (optional)
    hosts:
    - app.example.com
    # Istio traffic policy (optional)
    trafficPolicy:
      tls:
        # use ISTIO_MUTUAL when mTLS is enabled
        mode: DISABLE
  analysis:
    # schedule interval (default 60s)
    interval: 1m
    # total number of iterations
    iterations: 10
    # max number of failed iterations before rollback
    threshold: 2
    # canary match condition
    match:
      - headers:
          user-agent:
            regex: ".*Firefox.*"
      - headers:
          cookie:
            regex: "^(.*?;)?(type=insider)(;.*)?$"
    metrics:
    - name: request-success-rate
      # minimum req success rate (non 5xx responses)
      # percentage (0-100)
      thresholdRange:
        min: 99
      interval: 1m
    - name: request-duration
      # maximum req duration P99
      # milliseconds
      thresholdRange:
        max: 500
      interval: 30s
    # generate traffic during analysis
    webhooks:
      - name: load-test
        url: http://flagger-loadtester.test/
        timeout: 15s
        metadata:
          cmd: "hey -z 1m -q 10 -c 2 -H 'Cookie: type=insider' http://podinfo.test:9898/"

Note that when using Istio 1.5 you have to replace the request-duration with a metric template.

The above configuration will run an analysis for ten minutes targeting Firefox users and those that have an insider cookie.

Save the above resource as podinfo-abtest.yaml and then apply it:

kubectl apply -f ./podinfo-abtest.yaml

After a couple of seconds Flagger will create the canary objects:

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

# generated 
deployment.apps/podinfo-primary
horizontalpodautoscaler.autoscaling/podinfo-primary
service/podinfo
service/podinfo-canary
service/podinfo-primary
destinationrule.networking.istio.io/podinfo-canary
destinationrule.networking.istio.io/podinfo-primary
virtualservice.networking.istio.io/podinfo

Automated canary promotion

Trigger a canary deployment by updating the container image:

kubectl -n test set image deployment/podinfo \
podinfod=ghcr.io/stefanprodan/podinfo:6.0.1

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

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

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   100      2019-03-16T14:05:07Z
prod        frontend  Succeeded     0        2019-03-15T16:15:07Z
prod        backend   Failed        0        2019-03-14T17:05:07Z

Automated rollback

During the canary analysis you can generate HTTP 500 errors and high latency to test Flagger's rollback.

Generate HTTP 500 errors:

watch curl -b 'type=insider' http://app.example.com/status/500

Generate latency:

watch curl -b 'type=insider' 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 test describe canary/podinfo

Status:
  Failed Checks:         2
  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 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  3m    flagger  Halt podinfo.test advancement success rate 69.17% < 99%
  Normal   Synced  2m    flagger  Halt podinfo.test advancement success rate 61.39% < 99%
  Warning  Synced  2m    flagger  Rolling back podinfo.test failed checks threshold reached 2
  Warning  Synced  1m    flagger  Canary failed! Scaling down podinfo.test

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

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