Module 7: Optional Features for OpenShift 4.18/4.19

# Create HyperConverged instance to enable virtualization
apiVersion: hco.kubevirt.io/v1beta1
kind: HyperConverged
metadata:
  name: kubevirt-hyperconverged
  annotations:
    deployOVS: 'false'
  namespace: openshift-cnv
spec:
  virtualMachineOptions:
    disableFreePageReporting: false
    disableSerialConsoleLog: true
  higherWorkloadDensity:
    memoryOvercommitPercentage: 100
  liveMigrationConfig:
    allowAutoConverge: false
    allowPostCopy: false
    completionTimeoutPerGiB: 150
    parallelMigrationsPerCluster: 5
    parallelOutboundMigrationsPerNode: 2
    progressTimeout: 150
  certConfig:
    ca:
      duration: 48h0m0s
      renewBefore: 24h0m0s
    server:
      duration: 24h0m0s
      renewBefore: 12h0m0s
  applicationAwareConfig:
    allowApplicationAwareClusterResourceQuota: false
    vmiCalcConfigName: DedicatedVirtualResources
  featureGates:
    enableCommonBootImageImport: true
    downwardMetrics: false
    disableMDevConfiguration: false
    enableApplicationAwareQuota: false
    deployKubeSecondaryDNS: false
    alignCPUs: false
    deployVmConsoleProxy: false
    persistentReservation: false
    autoResourceLimits: false
  workloadUpdateStrategy:
    batchEvictionInterval: 1m0s
    batchEvictionSize: 10
    workloadUpdateMethods:
      - LiveMigrate
  uninstallStrategy: BlockUninstallIfWorkloadsExist
  resourceRequirements:
    vmiCPUAllocationRatio: 10

# Check virtualization pods
oc get pods -n openshift-cnv

# Verify HyperConverged status
oc get hco -n openshift-cnv kubevirt-hyperconverged -o yaml

# Check node virtualization capabilities
oc get nodes -o custom-columns=NAME:.metadata.name,VIRT:.status.allocatable.devices\\.kubevirt\\.io/kvm

# Example VM configuration
apiVersion: kubevirt.io/v1
kind: VirtualMachine
metadata:
  name: rhel8-vm
  namespace: default
spec:
  running: true
  template:
    metadata:
      labels:
        kubevirt.io/vm: rhel8-vm
    spec:
      domain:
        cpu:
          cores: 2
        memory:
          guest: 4Gi
        devices:
          disks:
          - name: rootdisk
            disk:
              bus: virtio
          - name: cloudinitdisk
            disk:
              bus: virtio
          interfaces:
          - name: default
            masquerade: {}
        machine:
          type: pc-q35-rhel8.4.0
      networks:
      - name: default
        pod: {}
      volumes:
      - name: rootdisk
        containerDisk:
          image: quay.io/containerdisks/rhel:8-latest
      - name: cloudinitdisk
        cloudInitNoCloud:
          userData: |
            #cloud-config
            user: cloud-user
            password: redhat
            chpasswd: { expire: False }

# Start a virtual machine
virtctl start rhel8-vm

# Stop a virtual machine
virtctl stop rhel8-vm

# Connect to VM console
virtctl console rhel8-vm

# SSH into VM (if configured)
virtctl ssh cloud-user@rhel8-vm

# Create a migration plan that will use VDDK
# This is typically done through the Migration Toolkit for Virtualization UI
# The migration will automatically detect and use the VDDK image

# Monitor migration progress
oc get migration -n openshift-mtv

# Check migration logs for VDDK usage
oc logs -l app=migration-controller -n openshift-mtv | grep -i vddk

# Configure live migration policy
apiVersion: kubevirt.io/v1
kind: KubeVirt
metadata:
  name: kubevirt
  namespace: openshift-cnv
spec:
  configuration:
    migrations:
      allowAutoConverge: true
      allowPostCopy: true
      completionTimeoutPerGiB: 800
      parallelMigrationsPerCluster: 5
      parallelOutboundMigrationsPerNode: 2
      progressTimeout: 150

# Label nodes with GPU resources
oc label node worker-gpu-1 nvidia.com/gpu.present=true

# Configure GPU passthrough
oc patch hco kubevirt-hyperconverged -n openshift-cnv --type=merge --patch='
{
  "spec": {
    "permittedHostDevices": {
      "pciHostDevices": [
        {
          "pciDeviceSelector": "10DE:1EB8",
          "resourceName": "nvidia.com/TU104GL_Tesla_T4"
        }
      ]
    }
  }
}'

# Install Migration Toolkit for Virtualization
oc apply -f - <<EOF
apiVersion: operators.coreos.com/v1alpha1
kind: Subscription
metadata:
  name: mtv-operator
  namespace: openshift-mtv
spec:
  channel: release-v2.6
  name: mtv-operator
  source: redhat-operators
  sourceNamespace: openshift-marketplace
EOF

# Example VM template
apiVersion: template.openshift.io/v1
kind: Template
metadata:
  name: rhel8-server-template
  namespace: openshift
objects:
- apiVersion: kubevirt.io/v1
  kind: VirtualMachine
  metadata:
    name: ${NAME}
  spec:
    running: false
    template:
      metadata:
        labels:
          kubevirt.io/vm: ${NAME}
      spec:
        domain:
          cpu:
            cores: ${{CPU_CORES}}
          memory:
            guest: ${MEMORY}
          devices:
            disks:
            - name: rootdisk
              disk:
                bus: virtio
            interfaces:
            - name: default
              masquerade: {}
        networks:
        - name: default
          pod: {}
        volumes:
        - name: rootdisk
          containerDisk:
            image: ${DISK_IMAGE}
parameters:
- name: NAME
  description: VM name
  required: true
- name: CPU_CORES
  description: Number of CPU cores
  value: "2"
- name: MEMORY
  description: Memory size
  value: "4Gi"
- name: DISK_IMAGE
  description: Container disk image
  value: "quay.io/containerdisks/rhel:8-latest"

# Install OpenShift AI Operator
oc apply -f - <<EOF
apiVersion: operators.coreos.com/v1alpha1
kind: Subscription
metadata:
  name: rhods-operator
  namespace: redhat-ods-operator
spec:
  channel: stable
  name: rhods-operator
  source: redhat-operators
  sourceNamespace: openshift-marketplace
EOF

# Create DataScienceCluster instance
apiVersion: datasciencecluster.opendatahub.io/v1
kind: DataScienceCluster
metadata:
  name: default-dsc
spec:
  components:
    codeflare:
      managementState: Managed
    dashboard:
      managementState: Managed
    datasciencepipelines:
      managementState: Managed
    kserve:
      managementState: Managed
    modelmeshserving:
      managementState: Managed
    ray:
      managementState: Managed
    workbenches:
      managementState: Managed

# Install NVIDIA GPU Operator
oc apply -f - <<EOF
apiVersion: operators.coreos.com/v1alpha1
kind: Subscription
metadata:
  name: gpu-operator-certified
  namespace: nvidia-gpu-operator
spec:
  channel: stable
  name: gpu-operator-certified
  source: certified-operators
  sourceNamespace: openshift-marketplace
EOF

# Create a data science project
apiVersion: v1
kind: Namespace
metadata:
  name: ml-project
  labels:
    opendatahub.io/dashboard: "true"
  annotations:
    openshift.io/description: "Machine Learning Project"
    openshift.io/display-name: "ML Project"

# Deploy Jupyter notebook server
apiVersion: kubeflow.org/v1
kind: Notebook
metadata:
  name: ml-notebook
  namespace: ml-project
spec:
  template:
    spec:
      containers:
      - name: ml-notebook
        image: quay.io/opendatahub/workbench-images:jupyter-datascience-c9s-py311_2023c_latest
        resources:
          requests:
            cpu: "1"
            memory: "4Gi"
            nvidia.com/gpu: "1"
          limits:
            cpu: "2"
            memory: "8Gi"
            nvidia.com/gpu: "1"
        volumeMounts:
        - name: workspace
          mountPath: /opt/app-root/src
      volumes:
      - name: workspace
        persistentVolumeClaim:
          claimName: ml-workspace-pvc

# Deploy a model using KServe
apiVersion: serving.kserve.io/v1beta1
kind: InferenceService
metadata:
  name: sklearn-iris
  namespace: ml-project
spec:
  predictor:
    sklearn:
      storageUri: "gs://kfserving-examples/models/sklearn/1.0/model"
      resources:
        requests:
          cpu: "100m"
          memory: "256Mi"
        limits:
          cpu: "1"
          memory: "1Gi"