:Use canary releases to deploy an application across clusters

Procedure

1. Create a file named app-meta.yaml with the following content. The file defines the Kubernetes resources that are required to deploy an application.

   apiVersion: apps/v1
   kind: Deployment
   metadata:
     labels:
       app: demo
     name: demo
     namespace: demo
   spec:
     replicas: 1
     selector:
       matchLabels:
         app: demo
     template:
       metadata:
         labels:
           app: demo
       spec:
         containers:
         - image: registry.cn-hangzhou.aliyuncs.com/acs/rollouts-demo:red
           name: demo

2. Run the following command to deploy an application named demo on a master instance:

   kubectl apply -f app-meta.yaml

3. Create a file named policy-topology.yaml and copy the following content to the file: Specify the testing cluster cluster-test and the production cluster cluster-prod as the destination clusters.

   1. Run the following command to query the clusters associated with the Fleet instance. Confirm the destination clusters to which the application will be deployed.

      kubectl get managedclusters

      Expected output:

      NAME                     HUB ACCEPTED   MANAGED CLUSTER URLS   JOINED   AVAILABLE   AGE
      managedcluster-c5***z9   true                                  True     True        12d
      managedcluster-c1***e5   true                                  True     True        12d

   2. Select the destination clusters and replace <clusterid1> and <clusterid2> in the example with the IDs of the destination clusters.

   apiVersion: core.oam.dev/v1alpha1
   kind: Policy
   metadata:
     name: cluster-test
     namespace: demo
   type: topology
   properties:
     clusters: ["<clusterid1>"]
   ---
   apiVersion: core.oam.dev/v1alpha1
   kind: Policy
   metadata:
     name: cluster-prod
     namespace: demo
   type: topology
   properties:
     clusters: ["<clusterid2>"]

4. Run the following command to apply the configurations in the policy-topology.yaml file:

   kubectl apply -f policy-topology.yaml

5. Create a file named workflow.yaml and copy the following content to the file. The file defines a workflow.

   apiVersion: core.oam.dev/v1alpha1
   kind: Workflow
   metadata:
     name: deploy-demo
     namespace: demo
   steps:
     - type: deploy
       name: deploy-test
       properties:
         policies: ["cluster-test"]
     - type: deploy
       name: deploy-prod
       properties:
         auto: false
         policies: ["cluster-prod"]

   Note

   Add auto: false below deploy-prod in the workflow. After this setting is added, you need to manually confirm the deploy-pod step before the step can be performed.

6. Run the following command to deploy a multi-cluster application workflow on the Fleet instance:

   kubectl apply -f workflow.yaml

7. Create a file named app.yaml with the following content. The file defines the application.

   apiVersion: core.oam.dev/v1beta1
   kind: Application
   metadata:
     name: demo
     namespace: demo
     annotations:
       app.oam.dev/publishVersion: version1
   spec:
     components:
       - name: demo
         type: ref-objects
         properties:
           objects:
             - apiVersion: apps/v1
               kind: Deployment
               name: demo
     workflow:
       ref: deploy-demo

   Parameter	Description
   annotations: app.oam.dev/publishVersion	The version of the application. If an application or the Kubernetes resources that are used by an application are updated, you must change the value of this parameter to trigger the master instance to synchronize the updates to the clusters.
   components. type: ref-objects	The apiVersion, kind, and name parameters are used to reference Kubernetes resources in the same namespace. The master instance deploys these resources in the specified clusters. ACK One supports the following Kubernetes resources: Deployment/apps/v1, Secret/v1, ConfigMap/v1, and Ingress/networking.k8s.io/v1. If you require other resources, Submit a ticket to contact the ACK One team.
   workflow. ref	Specify the workflow that is used to deploy the application.

8. Run the following command to deploy the application demo on the master instance:

   kubectl apply -f app.yaml

9. Run the following command to query the deployment progress of the application.

   The output shows that the application named demo is in the workflowSuspending state.

   kubectl get app demo -n demo

   Expected output:

   NAME   COMPONENT   TYPE          PHASE                HEALTHY   STATUS   AGE
   demo   demo        ref-objects   workflowSuspending   true               38s

10. Run the following command to query the status of the Deployment in both clusters.

    Replace <clusterid1> and <clusterid2> with the IDs of the destination clusters. The output shows that the Deployment is deployed in the testing cluster but is not deployed in the production cluster.

    • Run the following command to query the status of the Deployment in the cluster cluster-test:

      kubectl amc get deployment demo -n demo -m <clusterid1>

      Expected output:

      Run on ManagedCluster <clusterid1>
      NAME   READY   UP-TO-DATE   AVAILABLE   AGE
      demo   1/1     1            1           2m

    • Run the following command to query the status of the Deployment in the cluster cluster-prod:

      kubectl amc get deployment demo -n demo -m <clusterid2>

      Expected output:

      Run on ManagedCluster <clusterid2>
      Error from server (NotFound): deployments.apps "demo" not found

11. Run the following command to deploy the Deployment in the production cluster:

    kubectl amc workflow resume demo -n demo

    Expected output:

    Successfully resume workflow: demo

12. Query the status of the Deployment in the production cluster.

    The output shows that the Deployment is deployed in the production cluster.

    kubectl amc get deployment demo -n demo -m <clusterid2>

    Expected output:

    Run on ManagedCluster <clusterid2>
    NAME   READY   UP-TO-DATE   AVAILABLE   AGE
    demo   1/1     1            1           8m