Cloud Service Mesh by example: canary deployments

Deploy Online Boutique

1. Set the current context for kubectl to the cluster where you plan to deploy Online Boutique. The command depends on whether you provisioned Cloud Service Mesh on a GKE cluster or a Kubernetes cluster outside GKE:

   GKE on Google Cloud

   gcloud container clusters get-credentials CLUSTER_NAME  \
       --project=PROJECT_ID \
       --zone=CLUSTER_LOCATION 
   

   GKE outside Google Cloud

   kubectl config use-context CLUSTER_NAME 
   

2. Create the namespace for the sample application and the ingress gateway:

   kubectl create namespace onlineboutique
   

3. Label the onlineboutique namespace to automatically inject Envoy proxies. Follow the steps on how to enable automatic sidecar injection.

4. Deploy the sample app. For this tutorial, you deploy Online Boutique, a microservice demo app.

   kubectl apply \
   -n onlineboutique \
   -f https://raw.githubusercontent.com/GoogleCloudPlatform/anthos-service-mesh-samples/main/docs/shared/online-boutique/kubernetes-manifests.yaml
   

5. Add a label version=v1 to the productcatalog deployment by running the following command:

   kubectl patch deployments/productcatalogservice -p '{"spec":{"template":{"metadata":{"labels":{"version":"v1"}}}}}' \
   -n onlineboutique
   

   View the services that you deployed:

   kubectl get pods -n onlineboutique
   

   Expected output:

   NAME                                     READY   STATUS    RESTARTS   AGE
   adservice-85598d856b-m84m6               2/2     Running   0          2m7s
   cartservice-c77f6b866-m67vd              2/2     Running   0          2m8s
   checkoutservice-654c47f4b6-hqtqr         2/2     Running   0          2m10s
   currencyservice-59bc889674-jhk8z         2/2     Running   0          2m8s
   emailservice-5b9fff7cb8-8nqwz            2/2     Running   0          2m10s
   frontend-77b88cc7cb-mr4rp                2/2     Running   0          2m9s
   loadgenerator-6958f5bc8b-55q7w           2/2     Running   0          2m8s
   paymentservice-68dd9755bb-2jmb7          2/2     Running   0          2m9s
   productcatalogservice-84f95c95ff-c5kl6   2/2     Running   0          114s
   recommendationservice-64dc9dfbc8-xfs2t   2/2     Running   0          2m9s
   redis-cart-5b569cd47-cc2qd               2/2     Running   0          2m7s
   shippingservice-5488d5b6cb-lfhtt         2/2     Running   0          2m7s
   

   A 2/2 in the READY column indicates that a pod is up and running with an Envoy proxy successfully injected.

6. Deploy your VirtualService and DestinationRule for v1 of productcatalog:

    kubectl apply -f destination-vs-v1.yaml -n onlineboutique
   

   apiVersion: networking.istio.io/v1beta1
   kind: DestinationRule
   metadata:
     name: productcatalogservice
   spec:
     host: productcatalogservice
     subsets:
     - labels:
         version: v1
       name: v1
   ---
   apiVersion: networking.istio.io/v1beta1
   kind: VirtualService
   metadata:
     name: productcatalogservice
   spec:
     hosts:
     - productcatalogservice
     http:
     - route:
       - destination:
           host: productcatalogservice
           subset: v1

   Note that only v1 is present in the resources.

   View the Destination Rule created.

     kubectl get destinationrules -n onlineboutique
   

   Expected output:

     NAME                    HOST                    AGE
     productcatalogservice   productcatalogservice   2m
   

   View the VirtualService created.

     kubectl get virtualservices -n onlineboutique
   

   Expected outcome:

     NAME                    GATEWAYS   HOSTS                       AGE
     productcatalogservice              ["productcatalogservice"]   2m
   

7. Visit the application in your browser using the external IP address of your ingress gateway:

   kubectl get services -n GATEWAY_NAMESPACE
   

This next section tours the Cloud Service Mesh UI and show how you can view your metrics.

View your services in Google Cloud console

1. In Google Cloud console, go to the Google Kubernetes Engine (GKE) Enterprise edition Services page.

   Go to Google Kubernetes Engine (GKE) Enterprise edition Services

2. By default, you view your services in the List view.

   The Table Overview lets you observe all your services, as well as important metrics at a glance.

3. In the top right, click Topology. Here you can view your services and their interaction with each other.

   You can expand Services and view the Requests per second for each of your services by hovering over on them with your cursor.

4. Navigate back to the Table View.

5. In the Services Table, select productcatalogservice. This takes you to an overview of your service.

6. On the left side of the screen, click Traffic.

7. Ensure 100% of the incoming traffic to productcatalogservice goes to the workload service.

The next section goes through creating a v2 of the productcatalog service.

Deploy v2 of a service

1. For this tutorial, productcatalogservice-v2 introduces a 3-second latency into requests with the EXTRA_LATENCY field. This simulates a regression in the new version of the service.

   apiVersion: apps/v1
   kind: Deployment
   metadata:
     name: productcatalogservice-v2
   spec:
     selector:
       matchLabels:
         app: productcatalogservice
     template:
       metadata:
         labels:
           app: productcatalogservice
           version: v2
       spec:
         containers:
         - env:
           - name: PORT
             value: '3550'
           - name: EXTRA_LATENCY
             value: 3s
           name: server
           image: gcr.io/google-samples/microservices-demo/productcatalogservice:v0.3.6
           livenessProbe:
             exec:
               command: ["/bin/grpc_health_probe", "-addr=:3550"]
           ports:
           - containerPort: 3550
           readinessProbe:
             exec:
               command: ["/bin/grpc_health_probe", "-addr=:3550"]
           resources:
             limits:
               cpu: 200m
               memory: 128Mi
             requests:
               cpu: 100m
               memory: 64Mi
         terminationGracePeriodSeconds: 5

   Apply this resource to the onlineboutique namespace.

   kubectl apply -f productcatalog-v2.yaml -n onlineboutique
   

2. Check on your application pods.

   kubectl get pods -n onlineboutique
   

   Expected output:

   NAME                                     READY   STATUS    RESTARTS   AGE
   adservice-85598d856b-8wqfd                  2/2     Running   0          25h
   cartservice-c77f6b866-7jwcr                 2/2     Running   0          25h
   checkoutservice-654c47f4b6-n8c6x            2/2     Running   0          25h
   currencyservice-59bc889674-l5xw2            2/2     Running   0          25h
   emailservice-5b9fff7cb8-jjr89               2/2     Running   0          25h
   frontend-77b88cc7cb-bwtk4                   2/2     Running   0          25h
   loadgenerator-6958f5bc8b-lqmnw              2/2     Running   0          25h
   paymentservice-68dd9755bb-dckrj             2/2     Running   0          25h
   productcatalogservice-84f95c95ff-ddhjv      2/2     Running   0          25h
   productcatalogservice-v2-6df4cf5475-9lwjb   2/2     Running   0          8s
   recommendationservice-64dc9dfbc8-7s7cx      2/2     Running   0          25h
   redis-cart-5b569cd47-vw7lw                  2/2     Running   0          25h
   shippingservice-5488d5b6cb-dj5gd            2/2     Running   0          25h
   

   Note that there are now two productcatalogservices listed.

3. Use DestinationRule to specify the subsets of a service. In this scenario, there is a subset for v1 and then a separate subset for v2 of productcatalogservice.

   apiVersion: networking.istio.io/v1beta1
   kind: DestinationRule
   metadata:
     name: productcatalogservice
   spec:
     host: productcatalogservice
     subsets:
     - labels:
         version: v1
       name: v1
     - labels:
         version: v2
       name: v2

   Note the labels field. The versions of productcatalogservice are distinguished after the traffic is routed by the VirtualService.

   Apply the DestinationRule:

   kubectl apply -f destination-v1-v2.yaml -n onlineboutique
   

Split traffic between v1 and v2

1. Use VirtualService to define a small percentage of the traffic to direct to v2 of the productcatalogservice.

   apiVersion: networking.istio.io/v1beta1
   kind: VirtualService
   metadata:
     name: productcatalogservice
   spec:
     hosts:
     - productcatalogservice
     http:
     - route:
       - destination:
           host: productcatalogservice
           subset: v1
         weight: 75
       - destination:
           host: productcatalogservice
           subset: v2
         weight: 25

   The subset field indicates the version, and the weight field indicates the percentage split of traffic. 75% of traffic goes to v1 of productcatalog, and 25% goes to v2.

   Apply the VirtualService:

   kubectl apply -f vs-split-traffic.yaml -n onlineboutique
   

If you visit the EXTERNAL_IP of the cluster's ingress, you should notice that periodically, the frontend is slower to load.

In the next section, explore the traffic split in Google Cloud console.

Observe the traffic split in Google Cloud console

1. Return to Google Cloud console and go to the GKE Enterprise Services page. Go to GKE Enterprise Services

2. In the top right, click Topology.

   Expand the productcatalogservice workload and note the productcatalogservice and productcatalogservice-v2 deployments.

3. Return to the Table View.

4. Click productcatalogservice in the Services Table.

5. Return to Traffic on the left navigation bar.

6. Note that the incoming traffic is split between v1 and v2 by the percentage specified in the VirtualService file, and that there are 2 workloads of the productcatalog service.

   On the right side of the page, you see Requests, Error Rate, and Latency Metrics. With Cloud Service Mesh, each service has these metrics outlined to provide you with observability metrics.

Roll out or roll back to a version

After observing the metrics during a canary deployment, you can complete the roll out the new service version, or roll back to the original service version by leveraging the VirtualService resource.

Roll out

After you are satisfied with the behavior of a v2 service, you can incrementally increase the percentage of traffic directed to the v2 service. Eventually, traffic can be 100% directed to the new service in the VirtualService resource you created above by removing the traffic split from that resource.

apiVersion: networking.istio.io/v1beta1
kind: VirtualService
metadata:
  name: productcatalogservice
spec:
  hosts:
  - productcatalogservice
  http:
  - route:
    - destination:
        host: productcatalogservice
        subset: v2

To direct all the traffic to v2 of productcatalogservice:

kubectl apply -f vs-v2.yaml -n onlineboutique

Roll back

If you need to roll back to the v1 service, apply the destination-vs-v1.yaml from earlier. This directs traffic only to v1 of productcatalogservice.

apiVersion: networking.istio.io/v1beta1
kind: VirtualService
metadata:
  name: productcatalogservice
spec:
  hosts:
  - productcatalogservice
  http:
  - route:
    - destination:
        host: productcatalogservice
        subset: v1

To direct all the traffic to v1 of productcatalogservice:

kubectl apply -f vs-v1.yaml -n onlineboutique