1. AI Workload Migration Across Kubernetes Clusters


    Migrating workloads across Kubernetes clusters involves moving resources such as deployments, services, persistent volumes, secrets, and configuration from one cluster to another. Using Pulumi, this process involves several steps:

    1. Exporting Resources from the Source Cluster: We need to capture the current state of the workloads from the source cluster. This can be done using the pulumi stack export command, which outputs the state of resources in a stack to a file.

    2. Modifying the Exported Stack: The exported stack may need some modifications to fit the context of the target cluster. For example, you might need to change the resource names, namespaces, or specific annotations that are cluster-specific.

    3. Importing Resources to the Target Cluster: With the modified stack, you can import the resources into the target cluster using the pulumi stack import command. This will attempt to create all the resources in the target cluster as per the modified stack file.

    4. Verifying the Migration: After importing, it's crucial to verify that the resources are functioning correctly in the new cluster. This might involve checking the services' statuses, ensuring persistent volumes are correctly attached, and testing the applications.

    Below is an example Pulumi Python program which does not perform the migration itself but sets up the necessary resources for a Kubernetes cluster that you could use in a migration. The example demonstrates how to declare a Kubernetes cluster and associated resources in Pulumi.

    For migration, you would first capture the existing cluster's state, then modify the configurations to fit the new cluster's specifications and apply the modified configurations to the new cluster.

    Pulumi Python Program Setup for Kubernetes Clusters

    import pulumi from pulumi_kubernetes import Provider from pulumi_kubernetes.apps.v1 import Deployment from pulumi_kubernetes.core.v1 import Namespace, Service # Configure the Kubernetes provider for the source cluster source_kubeconfig = "..." # This should be replaced with the actual kubeconfig content or file path source_cluster_provider = Provider("source-provider", kubeconfig=source_kubeconfig) # Configure the Kubernetes provider for the target cluster target_kubeconfig = "..." # This should be replaced with the actual kubeconfig content or file path target_cluster_provider = Provider("target-provider", kubeconfig=target_kubeconfig) # Deploy a sample namespace to the source cluster source_namespace = Namespace("source-namespace", metadata={"name": "source-workloads"}, opts=pulumi.ResourceOptions(provider=source_cluster_provider)) # Deploy a sample deployment to the source cluster source_deployment = Deployment("source-deployment", metadata={"namespace": source_namespace.metadata["name"]}, spec={ "selector": {"matchLabels": {"app": "source-app"}}, "replicas": 1, "template": { "metadata": {"labels": {"app": "source-app"}}, "spec": {"containers": [{"name": "nginx", "image": "nginx"}]} } }, opts=pulumi.ResourceOptions(provider=source_cluster_provider)) # Deploy a sample service to the source cluster source_service = Service("source-service", metadata={"namespace": source_namespace.metadata["name"]}, spec={ "selector": {"app": "source-app"}, "ports": [{"port": 80}] }, opts=pulumi.ResourceOptions(provider=source_cluster_provider)) # Here you would normally have code for the target cluster resources # Export the source deployment and service details pulumi.export("source_deployment_name", source_deployment.metadata["name"]) pulumi.export("source_service_name", source_service.metadata["name"])

    To perform a migration using Pulumi, you'd follow these high-level steps:

    1. Use pulumi stack export on the source cluster to generate a stack file.
    2. Modify the stack file as necessary for the target cluster's context.
    3. Use pulumi stack import on the target cluster to initiate the migration.
    4. Monitor the migration and troubleshoot any issues that arise.

    Remember that actual workloads may need more detailed adjustment, including persistent volume handling, secret rotations, updating DNS entries, and ensuring consistent network policies. Always plan and test your migration strategies thoroughly in a staging environment before executing them in production.