BookInfo Example

This example demonstrates how an application like Istio BookInfo can be deployed using Skyshift This test uses two k8s clusters:

• Cluster1 : A Product-Page microservice (application frontend) and details microservice run on the first cluster, which is used as frontend.
• Cluster2 : A Reviews-V2 (display rating with black stars) and Rating microservices run on the second cluster, used as backend.

1. Start Skyshift using the commands listed in README.md.

2. Add the first cluster to Skyshift

   Optionally, Create and configure KIND cluster

   kind create cluster --name=cluster1
   

   Next, enable MetalLB to provision loadbalancer for creating service with external IP, since this will be a frontend cluster

   kubectl apply -f https://raw.githubusercontent.com/metallb/metallb/v0.13.10/config/manifests/metallb-native.yaml
   

   Check the status of the MetalLB pods using the following command, and wait until they are in running state

   kubectl get pods -n metallb-system
   

   Once the pods are in running state, apply the following configuration.

   sleep 5
   kubectl apply -f - <<EOF
   apiVersion: metallb.io/v1beta1
   kind: IPAddressPool
   metadata:
       name: kind-pool
       namespace: metallb-system
   spec:
       addresses:
           - 172.18.255.1-172.18.255.250  # Choose an IP range that doesn't conflict with your local network
   ---
   apiVersion: metallb.io/v1beta1
   kind: L2Advertisement
   metadata:
       name: kind-advertisement
       namespace: metallb-system
   EOF
   

   Finally, add this cluster to Skyshift with label as frontend.

   skyctl create cluster --manager k8 kind-cluster1 --labels type frontend
   

3. Now, add the second cluster to Skyshift with label as backend Optionally, Create KIND cluster

   kind create cluster --name=cluster2
   

   skyctl create cluster --manager k8 kind-cluster2 --labels type backend
   

4. Submit the jobs productpage and details microservice to Skyshift

   export SKYSHIFT=<Path to cloned Skyshift directory>
   

   skyctl apply -f $SKYSHIFT/examples/bookinfo-demo/productpage.yaml
   

   skyctl apply -f $SKYSHIFT/examples/bookinfo-demo/details.yaml
   

   Verify if the jobs are in running state and scheduled in kind-cluster1

   $ skyctl get jobs
   ⠙ Fetching jobs
   NAME         CLUSTER        REPLICAS    RESOURCES          NAMESPACE    STATUS    AGE
   details-v1   kind-cluster1  1/1         cpus: 7.0          default      RUNNING   12s
                                           memory: 128.00 MB
   productpage  kind-cluster1  1/1         cpus: 7.0          default      RUNNING   18s
                                           memory: 128.00 MB
   ✔ Fetching jobs completed successfully.
   

5. Create a service for the jobs

   skyctl apply -f $SKYSHIFT/examples/bookinfo-demo/productpage_service.yaml 
   
   

   skyctl apply -f $SKYSHIFT/examples/bookinfo-demo/details_service.yaml 
   

6. Deploy reviews and ratings microservice in cluster2

   skyctl apply -f $SKYSHIFT/examples/bookinfo-demo/ratings.yaml
   

   skyctl apply -f $SKYSHIFT/examples/bookinfo-demo/reviews.yaml
   

   Ideally, now the jobs must be running in the clusters similar to below output, productpage, and details-v1 are scheduled in kind-cluster1, while ratings-v1, and reviews-v2 are scheduled in kind-cluster2

       $ skyctl get jobs
       ⠙ Fetching jobs
       NAME         CLUSTER        REPLICAS    RESOURCES          NAMESPACE    STATUS    AGE
       details-v1   kind-cluster1  1/1         cpus: 7.0          default      RUNNING   14m
                                               memory: 128.00 MB
       productpage  kind-cluster1  1/1         cpus: 7.0          default      RUNNING   15m
                                               memory: 128.00 MB
       ratings-v1   kind-cluster2  1/1         cpus: 7.0          default      RUNNING   47s
                                               memory: 128.00 MB
       reviews-v2   kind-cluster2  1/1         cpus: 7.0          default      RUNNING   15s
                                               memory: 128.00 MB
       ✔ Fetching jobs completed successfully.
   

7. Create a link between the two clusters

   skyctl create link -s kind-cluster1 -t kind-cluster2 clink
   

8. Now, we create reviews service in cluster1, so that it is accessible to productpage.

   skyctl apply -f $SKYSHIFT/examples/bookinfo-demo/ratings_service.yaml
   

   skyctl apply -f $SKYSHIFT/examples/bookinfo-demo/reviews_service.yaml
   

   At this point it uses clusterlink to import the reviews service from cluster2

9. Now, we can try to access the productpage frontend application using

   export FRONTEND_IP=`kubectl get svc productpage --context kind-cluster1 -o jsonpath='{.status.loadBalancer.ingress[0].ip}'`
   

   open http://$FRONTEND_IP/productpage in browser, and you should be able to view the rating/reviews of the book as shown below.

10) Finally, Cleanup

```
./cleanup.sh
```