Migrate in-cluster to managed, on a new cluster

This tutorial shows you how to migrate an application from a Google Kubernetes Engine (GKE) cluster using in-cluster Cloud Service Mesh to a new cluster using managed Cloud Service Mesh — Google's fully managed, Istio-compliant service mesh.

In this tutorial, you:

1. Create a new Google Kubernetes Engine cluster, and install in-cluster Cloud Service Mesh and the Cloud Service Mesh ingress gateway on the cluster. This cluster will act as your existing cluster that you want to migrate away from.
2. Deploy the Online Boutique sample application onto the cluster with in-cluster Cloud Service Mesh.
3. Create another Google Kubernetes Engine cluster, in the same Google Cloud project.
4. Provision managed Cloud Service Mesh on the second cluster and deploy the Cloud Service Mesh ingress gateway.
5. Deploy Online Boutique onto the cluster with managed Cloud Service Mesh to replicate the deployment from the cluster with in-cluster Cloud Service Mesh.
6. Shift 50% of user traffic from the cluster with in-cluster Cloud Service Mesh to the cluster with managed Cloud Service Mesh, by using Istio's traffic splitting capabilities on the cluster with in-cluster Cloud Service Mesh.
7. Complete the migration from in-cluster Cloud Service Mesh to managed Cloud Service Mesh by pointing the domain name system (DNS) entry of the cluster with in-cluster Cloud Service Mesh to the cluster with managed Cloud Service Mesh.

Canary deployment

"Canary deployment" is a technique used in software development to test a new version of some software before releasing that new version to all users. It involves incrementally increasing the percentage of traffic sent to the new version. In this tutorial, you will set up a new cluster with managed Cloud Service Mesh and incrementally shift user traffic to it. You will start by directing 0% of user traffic to the new cluster, then 50%, and, finally, 100%. In production, you should use smaller and more increments. If at any point you notice that the new cluster is incapable of handling a percentage of traffic, you can rollback by reducing the percentage to 0%.

Canary control plane versus canary cluster

There are two commonly used strategies for migrations from in-cluster Cloud Service Mesh to managed Cloud Service Mesh:

• Canary control plane migration: In this strategy, you provision managed Cloud Service Mesh on the same cluster in which in-cluster Cloud Service Mesh is installed.
• Canary cluster migration: In this strategy, you create a new cluster and then provision managed Cloud Service Mesh on it.

In this tutorial, you will walk through the canary cluster migration strategy.

Costs

This tutorial uses the following billable components of Google Cloud:

• Google Kubernetes Engine
• Cloud Service Mesh

When you finish this tutorial, you can avoid ongoing costs by deleting the resources you created. For more information, see Clean up.

Before you begin

1. Sign in to your Google Cloud account. If you're new to Google Cloud, create an account to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.

2. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

   Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

   Go to project selector

3. Make sure that billing is enabled for your Google Cloud project.

4. Enable the required APIs.

   Enable the APIs

5. In the Google Cloud console, on the project selector page, select or create a Google Cloud project.

   Note: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.

   Go to project selector

6. Make sure that billing is enabled for your Google Cloud project.

7. Enable the required APIs.

   Enable the APIs

Launch Cloud Shell

In this tutorial you will use Cloud Shell, which is a shell environment hosted on Google Cloud that lets you manage your Google Cloud resources.

Cloud Shell comes preinstalled with the Google Cloud CLI, kubectl, and istioctl command-line tools. The gcloud CLI provides the primary CLI for Google Cloud.

Open a Cloud Shell session from the upper-right corner of this page, click and then click Acknowledge. A Cloud Shell session opens inside a frame lower on the page. Complete the following commands in that Cloud Shell session.

Download sample code

Clone the git repositories containing the Kubernetes and Istio resources you will use:

  git clone https://github.com/GoogleCloudPlatform/anthos-service-mesh-samples.git
  git clone https://github.com/GoogleCloudPlatform/microservices-demo.git

Set up the cluster with in-cluster Cloud Service Mesh

Create the cluster and install in-cluster Cloud Service Mesh

In the section, you create your cluster that uses in-cluster Cloud Service Mesh. In practice, this would be the cluster(s) that you are already using.

1. Replace PROJECT_ID with your project ID and create a new cluster:

   gcloud container clusters create cluster-with-in-cluster-asm \
     --project=PROJECT_ID \
     --zone=us-central1-a \
     --machine-type=e2-standard-4 --num-nodes=2 \
     --workload-pool=PROJECT_ID.svc.id.goog
   

   Note: This operation can take a few minutes to complete.

2. Rename the cluster context so that the cluster is easier to work with:

   kubectl config rename-context \
     gke_PROJECT_ID_us-central1-a_cluster-with-in-cluster-asm \
     cluster-with-in-cluster-asm
   

3. Check that the cluster context has been renamed:

   kubectl config get-contexts --output="name"
   

4. Download the version that installs Cloud Service Mesh 1.18.7 to the current working directory:

   curl https://storage.googleapis.com/csm-artifacts/asm/asmcli_1.18 > asmcli
   

   You will be asked to type "y" and then press Enter.

   The output is similar to:

   % Total    % Received % Xferd  Average Speed   Time    Time     Time  Current
                                 Dload  Upload   Total   Spent    Left  Speed
   100  167k  100  167k    0     0   701k      0 --:--:-- --:--:-- --:--:--  701k
   

5. Make the asmcli script executable:

   chmod +x asmcli
   

6. Install in-cluster Cloud Service Mesh using asmcli:

   ./asmcli install \
     --project_id PROJECT_ID \
     --cluster_name cluster-with-in-cluster-asm \
     --cluster_location us-central1-a \
     --output_dir . \
     --enable_all \
     --ca mesh_ca
   

   It can take several minutes for the asmcli tool to finish. The tool outputs informational messages so you can follow its progress.

   Upon success, the output is similar to:

   ...
   asmcli: Successfully installed ASM.
   

Deploy Cloud Service Mesh's ingress gateway

1. You will deploy the Cloud Service Mesh's ingress gateway into a separate namespace called asm-ingress. Create the namespace:

   kubectl \
     --context cluster-with-in-cluster-asm \
     create namespace asm-ingress
   

2. Use the istio.io/rev=asm-1187-26 label to add the asm-ingress namespace to the service mesh and enable automatic sidecar proxy injection.

   kubectl \
     --context cluster-with-in-cluster-asm \
     label --overwrite namespace asm-ingress istio.io/rev=asm-1187-26
   

   The output is similar to:

   namespace/asm-ingress labeled
   

   Note: You may need to modify the istio.io/rev=asm-1187-26 label to match your in-cluster Cloud Service Mesh version. You can see the version suffixed in the name of your istiod-asm-* Service by running kubectl get service --context=cluster-with-in-cluster-asm --namespace=istio-system

3. Deploy the Cloud Service Mesh ingress gateway:

   kubectl \
     --context cluster-with-in-cluster-asm \
     --namespace=asm-ingress \
     apply -f anthos-service-mesh-samples/docs/shared/asm-ingress-gateway/asm-gateway-deployment-svc.yaml
   kubectl \
     --context cluster-with-in-cluster-asm \
     --namespace=asm-ingress \
     apply -f anthos-service-mesh-samples/docs/shared/asm-ingress-gateway/gateway.yaml
   

   The output is similar to:

   serviceaccount/asm-ingressgateway created
   service/asm-ingressgateway created
   deployment.apps/asm-ingressgateway created
   gateway.networking.istio.io/asm-ingressgateway created
   

   Note: You can browse the resources in the official Cloud Service Mesh samples GitHub repository.

Deploy Online Boutique

1. You will deploy Online Boutique into a separate namespace called onlineboutique. Create the namespace:

   kubectl \
     --context cluster-with-in-cluster-asm \
     create namespace onlineboutique
   

2. Use the istio.io/rev=asm-1187-26 label to add the onlineboutique namespace to the service mesh and enable automatic sidecar proxy injection.

   kubectl \
     --context cluster-with-in-cluster-asm \
     label --overwrite namespace onlineboutique istio.io/rev=asm-1187-26
   

   The output is similar to:

   namespace/onlineboutique labeled
   

3. Deploy Online Boutique's 12 services, including the load generator that imitates user traffic:

   kubectl \
     --context cluster-with-in-cluster-asm \
     --namespace=onlineboutique \
     apply -f anthos-service-mesh-samples/docs/shared/online-boutique/kubernetes-manifests.yaml
   kubectl \
     --context cluster-with-in-cluster-asm \
     --namespace=onlineboutique \
     apply -f anthos-service-mesh-samples/docs/shared/online-boutique/virtual-service.yaml
   

4. Get the external IP address of the Cloud Service Mesh ingress gateway:

   kubectl \
     --context cluster-with-in-cluster-asm \
     --namespace asm-ingress \
     get service --output jsonpath='{.items[0].status.loadBalancer.ingress[0].ip}'
   

5. Copy the external IP address of the ingress gateway, and access it through your web browser. You will see the Online Boutique sample app.

Set up the new cluster with managed Cloud Service Mesh

Create the cluster and provision managed Cloud Service Mesh

In this section, you create the cluster that you will migrate to. You will provision managed Cloud Service Mesh, and deploy Online Boutique in order to replicate the deployments from the cluster that uses in-cluster Cloud Service Mesh.

1. Create a new cluster:

   gcloud container clusters create cluster-with-csm \
     --project=PROJECT_ID --zone=us-central1-a \
     --machine-type=e2-standard-4 --num-nodes=2 \
     --workload-pool PROJECT_ID.svc.id.goog
   

   Note: This operation can take a few minutes to complete.

2. Rename the cluster context so that the cluster is easier to work with:

   kubectl config rename-context \
     gke_PROJECT_ID_us-central1-a_cluster-with-csm \
     cluster-with-csm
   

3. Check that the cluster context has been renamed:

   kubectl config get-contexts --output="name"
   

4. Enable Cloud Service Mesh on your project's fleet. A fleet is a logical grouping of Kubernetes clusters and other resources that can be managed together.

   gcloud container fleet mesh enable --project PROJECT_ID
   

   The output is similar to:

   Waiting for Feature Service Mesh to be created...done.
   

5. Register the cluster to the project's fleet:

   gcloud container fleet memberships register cluster-with-csm-membership \
     --gke-cluster=us-central1-a/cluster-with-csm \
     --enable-workload-identity \
     --project PROJECT_ID
   

   The output is similar to:

   Waiting for membership to be created...done.
   Finished registering to the Fleet.
   

6. Enable managed Cloud Service Mesh on the cluster:

   gcloud container fleet mesh update \
     --management automatic \
     --memberships cluster-with-csm-membership \
     --project PROJECT_ID
   

   The output is similar to:

   Waiting for Feature Service Mesh to be updated...done.
   

   Note: Managed Cloud Service Mesh takes cares of a lot of the manual maintenance associated with upgrading, scaling, and securing your service mesh. Learn more about about Managed Cloud Service Mesh.

7. Verify that managed Cloud Service Mesh has been provisioned for the cluster and is ready to be used:

   gcloud container fleet mesh describe --project PROJECT_ID
   

   It can take about 10 minutes for Cloud Service Mesh to provision and be ready to use on the cluster. If you see controlPlaneManagement.state: DISABLED or controlPlaneManagement.state: PROVISIONING, you will need to re-run the previous command every few minutes until you see controlPlaneManagement.state: ACTIVE.

   The output is similar to:

   createTime: '2022-07-06T01:05:39.110120474Z'
   membershipSpecs:
     projects/123456789123/locations/global/memberships/cluster-with-csm-membership:
       mesh:
         management: MANAGEMENT_AUTOMATIC
   membershipStates:
     projects/123456789123/locations/global/memberships/cluster-with-csm-membership:
       servicemesh:
         controlPlaneManagement:
           details:
           - code: REVISION_READY
             details: 'Ready: asm-managed'
           state: ACTIVE
         dataPlaneManagement:
           details:
           - code: OK
             details: Service is running.
           state: ACTIVE
       state:
         code: OK
         description: 'Revision(s) ready for use: asm-managed.'
         updateTime: '2022-07-06T01:19:24.243993678Z'
   name: projects/your-project-id/locations/global/features/servicemesh
   resourceState:
     state: ACTIVE
   spec: {}
   state:
     state: {}
   updateTime: '2022-07-06T01:19:27.475885687Z'
   

Deploy Cloud Service Mesh's ingress gateway

1. You will deploy the Cloud Service Mesh's ingress gateway into a separate namespace called asm-ingress. Create the namespace:

   kubectl \
     --context cluster-with-csm \
     create namespace asm-ingress
   

2. Use the istio.io/rev=asm-managed label to add the asm-ingress namespace to the service mesh and enable automatic sidecar proxy injection.

   kubectl \
     --context cluster-with-csm \
     label namespace asm-ingress 'istio.io/rev=asm-managed'
   

3. Deploy the Cloud Service Mesh ingress gateway:

   kubectl \
     --context cluster-with-csm \
     --namespace=asm-ingress \
     apply -f anthos-service-mesh-samples/docs/shared/asm-ingress-gateway/asm-gateway-deployment-svc.yaml
   kubectl \
     --context cluster-with-csm \
     --namespace=asm-ingress \
     apply -f anthos-service-mesh-samples/docs/shared/asm-ingress-gateway/gateway.yaml
   

   The output is similar to:

   namespace/asm-ingress configured
   serviceaccount/asm-ingressgateway configured
   service/asm-ingressgateway configured
   deployment.apps/asm-ingressgateway configured
   gateway.networking.istio.io/asm-ingressgateway configured
   

   Note: You can browse the resources in the official Cloud Service Mesh samples GitHub repository.

Deploy Online Boutique

1. You will deploy Online Boutique into a separate namespace called onlineboutique. Create the namespace:

   kubectl \
     --context cluster-with-csm \
     create namespace onlineboutique
   

2. Use the istio.io/rev=asm-managed label to add the onlineboutique namespace to the service mesh and enable automatic sidecar proxy injection.

   kubectl \
     --context cluster-with-csm \
     label namespace onlineboutique 'istio.io/rev=asm-managed'
   

3. Deploy Online Boutique's 12 services, including the load generator that imitates user traffic:

   kubectl \
     --context cluster-with-csm \
     --namespace=onlineboutique \
     apply -f anthos-service-mesh-samples/docs/shared/online-boutique/kubernetes-manifests.yaml
   kubectl \
     --context cluster-with-csm \
     --namespace=onlineboutique \
     apply -f anthos-service-mesh-samples/docs/shared/online-boutique/virtual-service.yaml
   

4. Get the external IP address of the Cloud Service Mesh ingress gateway:

   kubectl \
     --context cluster-with-csm \
     --namespace asm-ingress \
     get service --output jsonpath='{.items[0].status.loadBalancer.ingress[0].ip}'
   

5. Copy the external IP address of the asm-ingressgateway Service, and access it through your web browser. You will see the Online Boutique sample app. You will use the external IP address in the next section, so copy it into an environment variable:

   export INGRESS_IP_OF_CLUSTER_WITH_MANAGED_ASM=$( \
     kubectl \
       --context cluster-with-csm \
       --namespace asm-ingress \
       get service --output jsonpath='{.items[0].status.loadBalancer.ingress[0].ip}' \
     )
   

Test the cluster with Cloud Service Mesh using a canary deployment

In this section, you configure the cluster with in-cluster Cloud Service Mesh such that 50% of the user traffic to Online Boutique is shifted to the instance of Online Boutique on the cluster with managed Cloud Service Mesh. To achieve this, you deploy two Istio resources to the cluster with in-cluster Cloud Service Mesh:

• a ServiceEntry to tell in-cluster Cloud Service Mesh about the managed Cloud Service Mesh cluster's Online Boutique endpoint
• a VirtualService to tell the in-cluster Cloud Service Mesh ingress gateway to split the traffic 50-50.

Note: In production, this traffic split to the cluster with managed Cloud Service Mesh should be done in small increments — instead of an immediate 50% — and gradually be increased to 100%.

1. Set the IP address of the managed Cloud Service Mesh cluster's ingress gateway inside the ServiceEntry resource:

   sed -i "s/1.2.3.4/${INGRESS_IP_OF_CLUSTER_WITH_MANAGED_ASM}/" anthos-service-mesh-samples/docs/migrate-to-managed-asm/service-entry.yaml
   

2. Deploy the ServiceEntry to the cluster with in-cluster Cloud Service Mesh:

   kubectl \
     --context cluster-with-in-cluster-asm \
     --namespace onlineboutique \
     apply -f anthos-service-mesh-samples/docs/migrate-to-managed-asm/service-entry.yaml
   

3. Deploy the VirtualService to the cluster with in-cluster Cloud Service Mesh:

   kubectl \
     --context cluster-with-in-cluster-asm \
     --namespace onlineboutique \
     apply -f anthos-service-mesh-samples/docs/migrate-to-managed-asm/virtual-service-in-cluster-asm.yaml
   

4. Visit the IP address of the ingress gateway of the cluster with in-cluster Cloud Service Mesh, in your web browser:

   kubectl \
     --context cluster-with-in-cluster-asm \
     --namespace asm-ingress \
     get service
   

   Refresh the Online Boutique homepage multiple times, and check the footer of the page each time. Notice that 50% of the requests are handled by a Pod on the cluster with managed Cloud Service Mesh.

Migrate to the cluster with managed Cloud Service Mesh

This section assumes that you own a domain name and have access to its DNS (Domain Name Server) settings.

1. Add an A record to the DNS settings to point the domain name (such as example.com) to the IP address of the ingress gateway running on the cluster with in-cluster Cloud Service Mesh.

   Note: This operation can take a few minutes to complete.

2. Access Online Boutique by visiting the domain name in your web browser.

3. Minimize DNS record time to live (TTL) to ensure you can quickly revert the DNS entry if you need to rollback.

4. Set the A record of your domain name to the external IP address of the ingress gateway of the cluster with managed Cloud Service Mesh.

5. When the migration is successful, delete the cluster with in-cluster Cloud Service Mesh:

   gcloud container clusters delete cluster-with-in-cluster-asm \
     --zone=us-central1-a \
     --project=PROJECT_ID
   

Clean up

To avoid incurring charges to your Google Cloud account for the resources used in this tutorial, either delete the project that contains the resources, or keep the project and delete the individual resources.

Delete project

Caution: Deleting a project has the following effects:
• Everything in the project is deleted. If you used an existing project for the tasks in this document, when you delete it, you also delete any other work you've done in the project.
• Custom project IDs are lost. When you created this project, you might have created a custom project ID that you want to use in the future. To preserve the URLs that use the project ID, such as an appspot.com URL, delete selected resources inside the project instead of deleting the whole project.
1. In the Google Cloud console, go to the Manage resources page.

   Go to Manage resources

2. In the project list, select the project that you want to delete, and then click Delete.
3. In the dialog, type the project ID, and then click Shut down to delete the project.

Delete the resources

Delete the cluster with managed Cloud Service Mesh:

  gcloud container clusters delete cluster-with-managed-asm \
    --zone=us-central1-a \
    --project=PROJECT_ID

What's next

• Learn about Managed Cloud Service Mesh.
• Learn about Cloud Service Mesh security best practices.