Container Service for Kubernetes:Use ACK One Gitops and Argo Rollouts to perform canary releases

Modify the rollout.yaml file based on the following sample code, and save and submit the file:

apiVersion: argoproj.io/v1alpha1
kind: Rollout
metadata:
  name: rollouts-demo
spec:
  replicas: 4
  strategy:
    canary:            # You do not need to configure metric analysis. 
      canaryService: rollouts-demo-canary
      stableService: rollouts-demo-stable
      trafficRouting:
        nginx:
          stableIngress: rollouts-demo-stable
      steps:
        - setWeight: 20
        - pause: {}          # Pause the canary release. The canary release continues only if it is resumed or promoted. 
        - setWeight: 40
        - pause: {duration: 5m}
        - setWeight: 60
        - pause: {duration: 5m}
        - setWeight: 80
        - pause: {duration: 5m}
  revisionHistoryLimit: 2
  selector:
    matchLabels:
      app: rollouts-demo
  template:
    metadata:
      labels:
        app: rollouts-demo
    spec:
      containers:
      - name: rollouts-demo
        image: argoproj/rollouts-demo:yellow   # Modify the image tag. 
        ports:
        - name: http
          containerPort: 8080
          protocol: TCP
        resources:
          requests:
            memory: 32Mi
            cpu: 5m        

Run the following command to query the rollout status:

kubectl argo rollouts get rollout rollouts-demo --watch

Expected output:

No duration is specified for the first pause in the rollout.yaml file. Therefore, the canary release can continue only if it is resumed or promoted.

Resume the canary release.

1. Modify the rollout.yaml file based on the following sample code, and save and submit the file:

         steps:
           - setWeight: 20
           - pause: {duration: 10s}   # Specify the duration of the pause.

2. Run the following command to resume the canary release:

   kubectl argo rollouts get rollout rollouts-demo --watch

   Expected output:

After the canary release is complete, the results in the following figure are returned.

Modify the rollout.yaml file based on the following sample code, and save and submit the file:

  strategy:
    canary:
      analysis:        # Configure metric analysis. 
        templates:     # Configure the metric analysis template. 
        - templateName: success-rate
        startingStep: 2 #delay starting analysis run until setWeight: 40%
        args:
          - name: service-name
            value: rollouts-demo-stable
      canaryService: rollouts-demo-canary
      stableService: rollouts-demo-stable
      trafficRouting:
        nginx:
          stableIngress: rollouts-demo-stable
      steps:
        - setWeight: 20
        - pause: {duration: 5m}
        - setWeight: 40
        - pause: {duration: 5m}
        - setWeight: 60
        - pause: {duration: 5m}
        - setWeight: 80
        - pause: {duration: 5m}
  revisionHistoryLimit: 2
  selector:
    matchLabels:
      app: rollouts-demo
  template:
    metadata:
      labels:
        app: rollouts-demo
    spec:
      containers:
      - name: rollouts-demo
        image: argoproj/rollouts-demo:blue  # Specify a new image tag.         

Obtain the endpoint of Managed Service for Prometheus.

Managed Service for Prometheus is exposed through a Kubernetes Service address in the following format: {ServiceName}.{Namespace}.svc.{ClusterDomain}:{ServicePort}. In this example, the Service that exposes Managed Service for Prometheus is deployed in the arms-prom namespace. The name of the Service is arms-prom-server, the default ClusterDomain is cluster.local, and the Service port is 9090. Therefore, the endpoint of Managed Service for Prometheus is http://arms-prom-server.arms-prom.svc.cluster.local:9090.

Add configurations related to Managed Service for Prometheus metric collection to the analysis.yaml file.

Set the value of the address parameter to the endpoint of Managed Service for Prometheus that is obtained in the preceding step. In the following sample code, a condition is added to verify successful canary releases. If the ratio of successful canary requests reaches 95% within the metric collection cycle, the canary release is considered successful and automatically proceeds to the next phase. For more information about how to configure metrics, see Prometheus Metrics.

apiVersion: argoproj.io/v1alpha1
kind: AnalysisTemplate
metadata:
  name: success-rate
spec:
  args:
  - name: service-name
  metrics:
  - name: success-rate
    interval: 5m
    successCondition: result[0] >= 0.95   # Add a condition to verify successful canary releases. 
    failureLimit: 10
    provider:
      prometheus:   # Specify the endpoint of the metric collection Service. 
        address: http://arms-prom-server.arms-prom.svc.cluster.local:9090  # Specify the endpoint of Managed Service for Prometheus that is obtained in the preceding step. 
        query: |
          sum(
            irate(nginx_ingress_controller_requests{status=~"(1|2).*", canary!="" ,service="{{args.service-name}}"}[5m]))
            /
            sum(irate(nginx_ingress_controller_requests{canary!="",service="{{args.service-name}}"}[5m])
          )

Make sure that Managed Service for Prometheus can continuously collect metric data.

1. Run the following command to query the Ingress of the application:

   kubectl get ingress

   Expected output:

   NAME                                        CLASS   HOSTS                 ADDRESS         PORTS   AGE
   rollouts-demo-rollouts-demo-stable-canary   nginx   rollouts-demo.local   8.217.XX.XX   80      9h
   rollouts-demo-stable                        nginx   rollouts-demo.local   8.217.XX.XX   80      9h

2. Add the following configuration to the local Hosts file:

   8.217.XX.XX  rollouts-demo.local

3. Open another command prompt and run the following command to continuously send requests to the application:

    while true; do curl -s "http://rollouts-demo.local/" | grep -o "<title>.*</title>" ;sleep 200ms;done

Run the following command to query the rollout status:

kubectl argo rollouts get rollout rollouts-demo --watch

Expected output:

View the metrics collected by Managed Service for Prometheus.

1. Log on to the ACK console. In the left-side navigation pane, click Cluster.

2. On the Clusters page, find the cluster that you want to manage and click its name. In the left-side pane, choose Operations > Prometheus Monitoring.

3. On the Prometheus Monitoring page, click the Network Monitoring tab and then click the Ingresses tab.

   The following figure shows the metrics.

   

After the canary release is complete, the results in the following figure are returned.