This repository is a clone of Akka.NET shopping cart example, modifying it to use Akka.Hosting and Akka.Discovery.KubernetesApi and designed as a showcase of how Akka.NET cluster pods can be auto scaled.

• The sharding entity actor in this example has been modified to generate synthetic CPU load when it is initialized.
• The Kubernetes YAML configuration file was designed to auto scale the cluster from 3 replicas to a maximum of 10 replicas when the metric server detects a spike of average pod CPU consumption over 80% (800m)

1. Make sure that you have Docker Desktop installed on your computer
2. Make sure that Docker Desktop is running using WSL Linux containers
3. Make sure that Docker Desktop Kubernetes feature is enabled
4. In a Windows PowerShell terminal, navigate to the project directory and execute

   .\install-metrics.cmd

   You should see an output similar to this:

   PS C:\> .\install-metrics.cmd
   serviceaccount/metrics-server created
   clusterrole.rbac.authorization.k8s.io/system:aggregated-metrics-reader created
   clusterrole.rbac.authorization.k8s.io/system:metrics-server created
   rolebinding.rbac.authorization.k8s.io/metrics-server-auth-reader created
   clusterrolebinding.rbac.authorization.k8s.io/metrics-server:system:auth-delegator created
   clusterrolebinding.rbac.authorization.k8s.io/system:metrics-server created
   service/metrics-server created
   deployment.apps/metrics-server created
   apiservice.apiregistration.k8s.io/v1beta1.metrics.k8s.io created
   

5. Wait a minute or so for Kubernetes metrics-server to spin up.
6. Confirm that Kubernetes metrics-server is up by executing:

   kubectl top node

   If metrics-server has been installed successfully, you should see an output similar to this:

   PS C:\> kubectl top node
   NAME             CPU(cores)   CPU%   MEMORY(bytes)   MEMORY%
   docker-desktop   172m         2%     3041Mi          52%   
   

In a Windows PowerShell terminal, navigate to the project directory and execute

.\start-k8s.cmd

This will:

• Compile the project,
• Build the docker image
• Create an Akka.NET sharded cluster inside the shopping-cart namespace

Execute kubectl top pod -n shopping-cart a few times until you see that metrics-server has successfully collected metrics from the pods:

PS C:\> kubectl top pod -n shopping-cart
error: metrics not available yet
PS C:\> kubectl top pod -n shopping-cart
error: metrics not available yet
PS C:\> kubectl top pod -n shopping-cart
error: metrics not available yet
PS C:\> kubectl top pod -n shopping-cart
NAME         CPU(cores)   MEMORY(bytes)
backend-0    39m          69Mi
backend-1    58m          75Mi
frontend-0   90m          89Mi

1. The frontend-0 pod will spawn 30 actors inside the backend stateful set cluster, creating a CPU spike on all 3 backend pods.
2. Execute

   kubectl top pod -n shopping-cart

   and check that backend pod CPU metrics spikes to above 800m

   PS C:\> kubectl top pod -n shopping-cart
   NAME         CPU(cores)   MEMORY(bytes)
   backend-0    1001m        86Mi
   backend-1    975m         84Mi
   backend-2    962m         83Mi
   frontend-0   63m          99Mi   
   

3. The pod auto scaler will scale the backend cluster after a few seconds

   PS C:\> kubectl top pod -n shopping-cart
   NAME         CPU(cores)   MEMORY(bytes)
   backend-0    21m          86Mi
   backend-1    17m          87Mi
   backend-2    18m          86Mi
   backend-3    18m          87Mi
   backend-4    17m          83Mi
   backend-5    16m          88Mi
   backend-6    17m          82Mi
   backend-7    16m          91Mi
   frontend-0   35m          99Mi

4. Shut down the frontend-0 pod by scaling the frontend stateful set to 0. Execute:

   kubectl scale --replicas=0 statefulset/frontend -n shopping-cart

5. Confirm that the frontend-0 pod has been shut down by executing kubectl top pod -n shopping-cart

   PS C:\> kubectl top pod -n shopping-cart
   NAME        CPU(cores)   MEMORY(bytes)
   backend-0   21m          87Mi
   backend-1   21m          88Mi
   backend-2   17m          84Mi
   backend-3   20m          88Mi
   backend-4   20m          84Mi
   backend-5   26m          89Mi
   backend-6   19m          83Mi
   backend-7   17m          92Mi

   Note that frontend-0 pod is now missing from the list
6. Wait 5-10 minutes and check the cluster status again by executing kubectl top pod -n shopping-cart

   PS C:\> kubectl top pod -n shopping-cart
   NAME        CPU(cores)   MEMORY(bytes)
   backend-0   21m          87Mi
   backend-1   21m          88Mi
   backend-2   17m          84Mi

   Note that the cluster has been automatically scaled down

To stop the Kubernetes cluster, execute:

.\destroy-k8s.cmd