SMI Istio Canary Deployments

This guide shows you how to use the SMI Istio adapter and Flagger to automate canary deployments.

Prerequisites

  • Kubernetes > 1.13

  • Istio > 1.0

Install Istio SMI adapter

Install the SMI adapter:

kubectl apply -f https://raw.githubusercontent.com/deislabs/smi-adapter-istio/master/deploy/crds/crds.yaml
kubectl apply -f https://raw.githubusercontent.com/deislabs/smi-adapter-istio/master/deploy/operator-and-rbac.yaml

Create a generic Istio gateway to expose services outside the mesh on HTTP:

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:
- "*"

Save the above resource as public-gateway.yaml and then apply it:

kubectl apply -f ./public-gateway.yaml

Find the Gateway load balancer IP and add a DNS record for it:

kubectl -n istio-system get svc/istio-ingressgateway -ojson | jq -r .status.loadBalancer.ingress[0].ip

Install Flagger and Grafana

Add Flagger Helm repository:

helm repo add flagger https://flagger.app

Deploy Flagger in the istio-system namespace:

helm upgrade -i flagger flagger/flagger \
--namespace=istio-system \
--set meshProvider=smi:istio

Flagger comes with a Grafana dashboard made for monitoring the canary deployments.

Deploy Grafana in the istio-system namespace:

helm upgrade -i flagger-grafana flagger/grafana \
--namespace=istio-system \
--set url=http://prometheus.istio-system:9090

You can access Grafana using port forwarding:

kubectl -n istio-system port-forward svc/flagger-grafana 3000:80

Workloads bootstrap

Create a test namespace with Istio sidecar injection enabled:

Create a test namespace and enable Linkerd proxy injection:

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

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:

kubectl apply -k github.com/weaveworks/flagger//kustomize/tester

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

apiVersion: flagger.app/v1alpha3
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/v2beta1
kind: HorizontalPodAutoscaler
name: podinfo
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: 10s
# max number of failed metric checks before rollback
threshold: 5
# max traffic percentage routed to canary
# percentage (0-100)
maxWeight: 50
# canary increment step
# percentage (0-100)
stepWeight: 10
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 http://podinfo.test:9898/"

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
canary.flagger.app/podinfo
# generated
deployment.apps/podinfo-primary
horizontalpodautoscaler.autoscaling/podinfo-primary
service/podinfo
service/podinfo-canary
service/podinfo-primary
trafficsplits.split.smi-spec.io/podinfo

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.

Flagger Canary Stages

Trigger a canary deployment by updating the container image:

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

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

kubectl -n istio-system logs deployment/flagger -f | jq .msg
New revision detected podinfo.test
Scaling up podinfo.test
Waiting for podinfo.test rollout to finish: 0 of 1 updated replicas are available
Advance podinfo.test canary weight 5
Advance podinfo.test canary weight 10
Advance podinfo.test canary weight 15
Advance podinfo.test canary weight 20
Advance podinfo.test canary weight 25
Advance podinfo.test canary weight 30
Advance podinfo.test canary weight 35
Advance podinfo.test canary weight 40
Advance podinfo.test canary weight 45
Advance podinfo.test canary weight 50
Copying podinfo.test template spec to podinfo-primary.test
Waiting for podinfo-primary.test rollout to finish: 1 of 2 updated replicas are available
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.

During the analysis the canary’s progress can be monitored with Grafana. The Istio dashboard URL is http://localhost:3000/d/flagger-istio/istio-canary?refresh=10s&orgId=1&var-namespace=test&var-primary=podinfo-primary&var-canary=podinfo

You can monitor all canaries with:

watch kubectl get canaries --all-namespaces
NAMESPACE NAME STATUS WEIGHT LASTTRANSITIONTIME
test podinfo Progressing 15 2019-05-16T14:05:07Z
prod frontend Succeeded 0 2019-05-15T16:15:07Z
prod backend Failed 0 2019-05-14T17:05:07Z

Automated rollback

During the canary analysis you can generate HTTP 500 errors and high latency to test if Flagger pauses the rollout.

Create a tester pod and exec into it:

kubectl -n test run tester \
--image=quay.io/stefanprodan/podinfo:3.1.2 \
-- ./podinfo --port=9898
kubectl -n test exec -it tester-xx-xx sh

Generate HTTP 500 errors:

watch curl http://podinfo-canary:9898/status/500

Generate latency:

watch curl http://podinfo-canary:9898/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:
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