Part 2: Workload

What Will You Do¶

In this part of the self-paced exercise, you will deploy a Windows workload to the Windows node on the MKS Cluster.

Step 1: Create Namespace¶

In this step, we will create a namespace using the web console. The namespace will be used to deploy workloads in future steps.

Navigate to the project in your Org where the cluster is located.
Select Infrastructure -> Namespaces
Click "New Namespace"
Enter "windows" for the name
Select "Wizard" for the Type
Click "Save"

UI Namespace

Click "Save & Go To Placement"

UI Namespace

Select the cluster to create the namespace on
Click "Save & Go To Publish"

UI Namespace

Click "Publish"

The namespace is now published on the cluster.

UI Namespace

Click "Exit"

Step 2: Deploy Windows Workload¶

In this step, we will deploy a Windows workload into the previously created namespace.

Navigate to the project in your Org where the cluster is located.
Select Applications -> Workloads
Click "New Workload" -> "Create New Workload"
Enter "windows-workload" for the name
Select "k8s YAML" for the Package Type
Select "Upload files manually"
Select the "Windows" namespace
Click "Continue"

UI Workload

Save the below specification file to your computer as "windows-workload.yaml".

Important

The 'nodeSelector' section, lines 40 & 41, specifies which OS to use. This is an important configuration to specify to avoid scheduling issues. Without a nodeSelector configuration, this deployment could be scheduled on a Linux node, causing it to fail. Kubernetes scheduling doesn't recognize Operating System, rather it is based on scores. For more information, please visit https://kubernetes.io/docs/concepts/scheduling-eviction/kube-scheduler/ .


apiVersion: v1
kind: Service
metadata:
  name: win-webserver
  labels:
    app: win-webserver
spec:
  ports:
    # the port that this service should serve on
    - port: 80
      targetPort: 80
  selector:
    app: win-webserver
  type: NodePort
---
apiVersion: apps/v1
kind: Deployment
metadata:
  labels:
    app: win-webserver
  name: win-webserver
spec:
  replicas: 2
  selector:
    matchLabels:
      app: win-webserver
  template:
    metadata:
      labels:
        app: win-webserver
      name: win-webserver
    spec:
     containers:
      - name: windowswebserver
        image: mcr.microsoft.com/windows/servercore:ltsc2019
        command:
        - powershell.exe
        - -command
        - "<#code used from https://gist.github.com/19WAS85/5424431#> ; $$listener = New-Object System.Net.HttpListener ; $$listener.Prefixes.Add('http://*:80/') ; $$listener.Start() ; $$callerCounts = @{} ; Write-Host('Listening at http://*:80/') ; while ($$listener.IsListening) { ;$$context = $$listener.GetContext() ;$$requestUrl = $$context.Request.Url ;$$clientIP = $$context.Request.RemoteEndPoint.Address ;$$response = $$context.Response ;Write-Host '' ;Write-Host('> {0}' -f $$requestUrl) ;  ;$$count = 1 ;$$k=$$callerCounts.Get_Item($$clientIP) ;if ($$k -ne $$null) { $$count += $$k } ;$$callerCounts.Set_Item($$clientIP, $$count) ;$$ip=(Get-NetAdapter | Get-NetIpAddress); $$header='<html><body><H1>Windows Container Web Server</H1>' ;$$callerCountsString='' ;$$callerCounts.Keys | % { $$callerCountsString+='<p>IP {0} callerCount {1} ' -f $$ip[1].IPAddress,$$callerCounts.Item($$_) } ;$$footer='</body></html>' ;$$content='{0}{1}{2}' -f $$header,$$callerCountsString,$$footer ;Write-Output $$content ;$$buffer = [System.Text.Encoding]::UTF8.GetBytes($$content) ;$$response.ContentLength64 = $$buffer.Length ;$$response.OutputStream.Write($$buffer, 0, $$buffer.Length) ;$$response.Close() ;$$responseStatus = $$response.StatusCode ;Write-Host('< {0}' -f $$responseStatus)  } ; "
     nodeSelector:
      kubernetes.io/os: windows

Click "Choose File" to upload the previously created YAML file
Click "Save and Go To Placement"

UI Workload

Select the cluster to deploy the workload on
Click "Save & Go To Publish"

UI Workload

Click "Publish"

The workload is now published on the cluster.

UI Workload

Click "Exit"

Step 3: Validate Workload¶

In this step, we will verify the Windows workload is running and accessible.

Navigate to the project in your Org where the cluster is located.
Select Infrastructure -> Clusters
Click on the kubectl link of the cluster and type the following command


kubectl get pods -n windows

You should see output similar to the following showing the windows workload running


NAME                            READY   STATUS    RESTARTS   AGE
win-webserver-df5876b96-4d7vm   1/1     Running   0          118s
win-webserver-df5876b96-6jt26   1/1     Running   0          118s

Enter the following command


kubectl get services -n windows

You should see output similar to the following showing the Cluster IP address of the service the workload is using.


NAME            TYPE       CLUSTER-IP      EXTERNAL-IP   PORT(S)        AGE
win-webserver   NodePort   10.108.133.57   <none>        80:31125/TCP   2m38s

Enter the following command on the linux node. Be sure to update the cluster-ip address with the ip address previously obtained.


curl <cluster-ip>

You should see output similar to the following showing the web response from the windows workload.


<html><body><H1>Windows Container Web Server</H1><p>IP 10.244.138.9 callerCount 1 </body></html>

Recap¶

Congratulations! At this point, you have successfully provisioned a Windows workload running on an MKS cluster.