×

You can schedule Windows workloads to Windows compute nodes.

The WMCO is not supported in clusters that use a cluster-wide proxy because the WMCO is not able to route traffic through the proxy connection for the workloads.

Prerequisites

  • You installed the Windows Machine Config Operator (WMCO) using Operator Lifecycle Manager (OLM).

  • You are using a Windows container as the OS image with the Docker-formatted container runtime add-on enabled.

  • You have created a Windows machine set.

Currently, the Docker-formatted container runtime is used in Windows nodes. Kubernetes is deprecating Docker as a container runtime; you can reference the Kubernetes documentation for more information in Docker deprecation. Containerd will be the new supported container runtime for Windows nodes in a future release of Kubernetes.

Windows pod placement

Before deploying your Windows workloads to the cluster, you must configure your Windows node scheduling so pods are assigned correctly. Since you have a machine hosting your Windows node, it is managed the same as a Linux-based node. Likewise, scheduling a Windows pod to the appropriate Windows node is completed similarly, using mechanisms like taints, tolerations, and node selectors.

With multiple operating systems, and the ability to run multiple Windows OS variants in the same cluster, you must map your Windows pods to a base Windows OS variant by using a RuntimeClass object. For example, if you have multiple Windows nodes running on different Windows Server container versions, the cluster could schedule your Windows pods to an incompatible Windows OS variant. You must have RuntimeClass objects configured for each Windows OS variant on your cluster. Using a RuntimeClass object is also recommended if you have only one Windows OS variant available in your cluster.

For more information, see Microsoft’s documentation on Host and container version compatibility.

The container base image must be the same Windows OS version and build number that is running on the node where the conainer is to be scheduled.

Also, if you upgrade the Windows nodes from one version to another, for example going from 20H2 to 2022, you must upgrade your container base image to match the new version. For more information, see Windows container version compatibility.

Additional resources

Creating a RuntimeClass object to encapsulate scheduling mechanisms

Using a RuntimeClass object simplifies the use of scheduling mechanisms like taints and tolerations; you deploy a runtime class that encapsulates your taints and tolerations and then apply it to your pods to schedule them to the appropriate node. Creating a runtime class is also necessary in clusters that support multiple operating system variants.

Procedure
  1. Create a RuntimeClass object YAML file. For example, runtime-class.yaml:

    apiVersion: node.k8s.io/v1beta1
    kind: RuntimeClass
    metadata:
      name: <runtime_class_name> (1)
    handler: 'docker'
    scheduling:
      nodeSelector: (2)
        kubernetes.io/os: 'windows'
        kubernetes.io/arch: 'amd64'
        node.kubernetes.io/windows-build: '10.0.17763'
      tolerations: (3)
      - effect: NoSchedule
        key: os
        operator: Equal
        value: "Windows"
    1 Specify the RuntimeClass object name, which is defined in the pods you want to be managed by this runtime class.
    2 Specify labels that must be present on nodes that support this runtime class. Pods using this runtime class can only be scheduled to a node matched by this selector. The node selector of the runtime class is merged with the existing node selector of the pod. Any conflicts prevent the pod from being scheduled to the node.
    3 Specify tolerations to append to pods, excluding duplicates, running with this runtime class during admission. This combines the set of nodes tolerated by the pod and the runtime class.
  2. Create the RuntimeClass object:

    $ oc create -f <file-name>.yaml

    For example:

    $ oc create -f runtime-class.yaml
  3. Apply the RuntimeClass object to your pod to ensure it is scheduled to the appropriate operating system variant:

    apiVersion: v1
    kind: Pod
    metadata:
      name: my-windows-pod
    spec:
      runtimeClassName: <runtime_class_name> (1)
    ...
    1 Specify the runtime class to manage the scheduling of your pod.

Sample Windows container workload deployment

You can deploy Windows container workloads to your cluster once you have a Windows compute node available.

This sample deployment is provided for reference only.

Example Service object
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: LoadBalancer
Example Deployment object
apiVersion: apps/v1
kind: Deployment
metadata:
  labels:
    app: win-webserver
  name: win-webserver
spec:
  selector:
    matchLabels:
      app: win-webserver
  replicas: 1
  template:
    metadata:
      labels:
        app: win-webserver
      name: win-webserver
    spec:
      tolerations:
      - key: "os"
        value: "Windows"
        Effect: "NoSchedule"
      containers:
      - name: windowswebserver
        image: mcr.microsoft.com/windows/servercore:ltsc2019
        imagePullPolicy: IfNotPresent
        command:
        - powershell.exe
        - -command
        - $listener = New-Object System.Net.HttpListener; $listener.Prefixes.Add('http://*:80/'); $listener.Start();Write-Host('Listening at http://*:80/'); while ($listener.IsListening) { $context = $listener.GetContext(); $response = $context.Response; $content='<html><body><H1>Red Hat OpenShift + Windows Container Workloads</H1></body></html>'; $buffer = [System.Text.Encoding]::UTF8.GetBytes($content); $response.ContentLength64 = $buffer.Length; $response.OutputStream.Write($buffer, 0, $buffer.Length); $response.Close(); };
        securityContext:
          runAsNonRoot: false
          windowsOptions:
            runAsUserName: "ContainerAdministrator"
      nodeSelector:
        kubernetes.io/os: windows

When using the mcr.microsoft.com/powershell:<tag> container image, you must define the command as pwsh.exe. If you are using the mcr.microsoft.com/windows/servercore:<tag> container image, you must define the command as powershell.exe. For more information, see Microsoft’s documentation.

Scaling a machine set manually

To add or remove an instance of a machine in a machine set, you can manually scale the machine set.

This guidance is relevant to fully automated, installer-provisioned infrastructure installations. Customized, user-provisioned infrastructure installations do not have machine sets.

Prerequisites
  • Install an OpenShift Container Platform cluster and the oc command line.

  • Log in to oc as a user with cluster-admin permission.

Procedure
  1. View the machine sets that are in the cluster:

    $ oc get machinesets -n openshift-machine-api

    The machine sets are listed in the form of <clusterid>-worker-<aws-region-az>.

  2. View the machines that are in the cluster:

    $ oc get machine -n openshift-machine-api
  3. Set the annotation on the machine that you want to delete:

    $ oc annotate machine/<machine_name> -n openshift-machine-api machine.openshift.io/cluster-api-delete-machine="true"
  4. Scale the compute machine set by running one of the following commands:

    $ oc scale --replicas=2 machineset <machineset> -n openshift-machine-api

    Or:

    $ oc edit machineset <machineset> -n openshift-machine-api

    You can alternatively apply the following YAML to scale the machine set:

    apiVersion: machine.openshift.io/v1beta1
    kind: MachineSet
    metadata:
      name: <machineset>
      namespace: openshift-machine-api
    spec:
      replicas: 2

    You can scale the compute machine set up or down. It takes several minutes for the new machines to be available.

    By default, the machine controller tries to drain the node that is backed by the machine until it succeeds. In some situations, such as with a misconfigured pod disruption budget, the drain operation might not be able to succeed. If the drain operation fails, the machine controller cannot proceed removing the machine.

    You can skip draining the node by annotating machine.openshift.io/exclude-node-draining in a specific machine.

Verification
  • Verify the deletion of the intended machine:

    $ oc get machines