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.
Create a test namespace with Istio sidecar injection enabled:
export REPO=https://raw.githubusercontent.com/weaveworks/flagger/master
kubectl apply -f ${REPO}/artifacts/namespaces/test.yamlCreate a deployment and a horizontal pod autoscaler:
kubectl apply -f ${REPO}/artifacts/ab-testing/deployment.yaml
kubectl apply -f ${REPO}/artifacts/ab-testing/hpa.yamlDeploy the load testing service to generate traffic during the canary analysis:
kubectl -n test apply -f ${REPO}/artifacts/loadtester/deployment.yaml
kubectl -n test apply -f ${REPO}/artifacts/loadtester/service.yamlCreate a canary custom resource (replace example.com with your own domain):
apiVersion: flagger.app/v1alpha3
kind: Canary
metadata:
name: abtest
namespace: test
spec:
# deployment reference
targetRef:
apiVersion: apps/v1
kind: Deployment
name: abtest
# the maximum time in seconds for the canary deployment
# to make progress before it is rollback (default 600s)
progressDeadlineSeconds: 60
# HPA reference (optional)
autoscalerRef:
apiVersion: autoscaling/v2beta1
kind: HorizontalPodAutoscaler
name: abtest
service:
# container port
port: 9898
# Istio gateways (optional)
gateways:
- public-gateway.istio-system.svc.cluster.local
# Istio virtual service host names (optional)
hosts:
- app.example.com
canaryAnalysis:
# schedule interval (default 60s)
interval: 1m
# total number of iterations
iterations: 10
# max number of failed iterations before rollback
threshold: 2
# canary match condition
match:
- headers:
user-agent:
regex: "^(?!.*Chrome).*Safari.*"
- headers:
cookie:
regex: "^(.*?;)?(type=insider)(;.*)?$"
metrics:
- name: request-success-rate
# minimum req success rate (non 5xx responses)
# percentage (0-100)
threshold: 99
interval: 1m
- name: request-duration
# maximum req duration P99
# milliseconds
threshold: 500
interval: 30s
# generate traffic during analysis
webhooks:
- name: load-test
url: http://flagger-loadtester.test/
timeout: 5s
metadata:
cmd: "hey -z 1m -q 10 -c 2 -H 'Cookie: type=insider' http://podinfo.test:9898/"The above configuration will run an analysis for ten minutes targeting Safari 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.yamlAfter a couple of seconds Flagger will create the canary objects:
# applied
deployment.apps/abtest
horizontalpodautoscaler.autoscaling/abtest
canary.flagger.app/abtest
# generated
deployment.apps/abtest-primary
horizontalpodautoscaler.autoscaling/abtest-primary
service/abtest
service/abtest-canary
service/abtest-primary
virtualservice.networking.istio.io/abtestTrigger a canary deployment by updating the container image:
kubectl -n test set image deployment/abtest \
podinfod=quay.io/stefanprodan/podinfo:1.4.1Flagger detects that the deployment revision changed and starts a new rollout:
kubectl -n test describe canary/abtest
Status:
Failed Checks: 0
Phase: Succeeded
Events:
Type Reason Age From Message
---- ------ ---- ---- -------
Normal Synced 3m flagger New revision detected abtest.test
Normal Synced 3m flagger Scaling up abtest.test
Warning Synced 3m flagger Waiting for abtest.test rollout to finish: 0 of 1 updated replicas are available
Normal Synced 3m flagger Advance abtest.test canary iteration 1/10
Normal Synced 3m flagger Advance abtest.test canary iteration 2/10
Normal Synced 3m flagger Advance abtest.test canary iteration 3/10
Normal Synced 2m flagger Advance abtest.test canary iteration 4/10
Normal Synced 2m flagger Advance abtest.test canary iteration 5/10
Normal Synced 1m flagger Advance abtest.test canary iteration 6/10
Normal Synced 1m flagger Advance abtest.test canary iteration 7/10
Normal Synced 55s flagger Advance abtest.test canary iteration 8/10
Normal Synced 45s flagger Advance abtest.test canary iteration 9/10
Normal Synced 35s flagger Advance abtest.test canary iteration 10/10
Normal Synced 25s flagger Copying abtest.test template spec to abtest-primary.test
Warning Synced 15s flagger Waiting for abtest-primary.test rollout to finish: 1 of 2 updated replicas are available
Normal Synced 5s flagger Promotion completed! Scaling down abtest.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 abtest Progressing 100 2019-03-16T14:05:07Z
prod frontend Succeeded 0 2019-03-15T16:15:07Z
prod backend Failed 0 2019-03-14T17:05:07ZDuring 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/500Generate latency:
watch curl -b 'type=insider' http://app.example.com/delay/1When 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/abtest
Status:
Failed Checks: 2
Phase: Failed
Events:
Type Reason Age From Message
---- ------ ---- ---- -------
Normal Synced 3m flagger Starting canary deployment for abtest.test
Normal Synced 3m flagger Advance abtest.test canary iteration 1/10
Normal Synced 3m flagger Advance abtest.test canary iteration 2/10
Normal Synced 3m flagger Advance abtest.test canary iteration 3/10
Normal Synced 3m flagger Halt abtest.test advancement success rate 69.17% < 99%
Normal Synced 2m flagger Halt abtest.test advancement success rate 61.39% < 99%
Warning Synced 2m flagger Rolling back abtest.test failed checks threshold reached 2
Warning Synced 1m flagger Canary failed! Scaling down abtest.test