1. Deploy the ibm-cp4d-watson-machine-learning-instance helm chart on Opensshift


    To deploy the IBM Cloud Pak for Data (CP4D) Watson Machine Learning instance Helm chart on OpenShift using Pulumi, we'll need to execute a few steps:

    1. Set up Pulumi to interact with your Kubernetes cluster and Helm.
    2. Identify and specify the necessary Helm chart and any configurable values required by the IBM Cloud Pak for Data Watson Machine Learning instance.
    3. Use Pulumi's Chart resource to deploy the Helm chart.

    Here is what each step involves and an accompanying Pulumi TypeScript program to achieve your deployment goal.

    Step 1: Setting up Pulumi

    You would need to have Pulumi installed and configured to interact with your Kubernetes cluster. Typically, this involves having the kubectl command-line tool configured to point to your OpenShift cluster.

    Step 2: Identifying Helm Chart Details

    You would need to find the Helm chart for the IBM CP4D Watson Machine Learning instance. Usually, Helm charts are available from IBM's Helm repository, or they might be bundled with the product documentation. You would also need to gather any configurable values (parameters) that are required to customize the Helm deployment to your environment, like resource constraints, service endpoints, etc.

    Step 3: Deploying with Pulumi's Chart Resource

    Pulumi's Chart resource is used to deploy Helm charts. Below is the Pulumi program written in TypeScript that shows how you can deploy the IBM CP4D Watson Machine Learning instance Helm chart on OpenShift.

    import * as k8s from "@pulumi/kubernetes"; // Ensure that you are passing the correct Helm chart repository and chart name along with any necessary values const watsonMlChart = new k8s.helm.v3.Chart("ibm-cp4d-watson-ml", { repo: "ibm-chart-repository", // Replace with actual Helm repository chart: "ibm-cp4d-watson-machine-learning-instance", // Replace with the actual chart name // Specify namespace if needed, otherwise, it deploys to the 'default' namespace namespace: "ml-workloads", // If the chart requires you to provide specific configuration values, specify them here. values: { // Example configuration values - replace with actual values required for your deployment // resources: { // limits: { // cpu: "500m", // memory: "1024Mi" // }, // requests: { // cpu: "500m", // memory: "1024Mi" // } // }, // serviceType: "ClusterIP", // replicaCount: 1 }, // The 'fetchOpts' field allows you to perform actions such as setting up authentication for private repos fetchOpts: { // Example for a Helm repository that might require authentication // username: "<your-username>", // password: "<your-password>" } }); // Export the base URL for the Watson Machine Learning API endpoint export const apiUrl = watsonMlChart.getResourceProperty("v1/Service", "ibm-cp4d-watson-ml-service", "status").apply(status => status.loadBalancer.ingress[0].ip);

    This program defines a Chart resource that tells Pulumi to deploy the specified Helm chart to your OpenShift cluster. You'll need to replace placeholder values such as the repository URL, chart name, and any required chart values with those that are specific to the IBM CP4D Watson Machine Learning instance chart you are trying to deploy.

    Notes on the Program

    • import * as k8s from "@pulumi/kubernetes"; imports the Pulumi Kubernetes package, which provides necessary abstractions for interacting with Kubernetes clusters.

    • The Chart resource definition takes several parameters:

      • The repo field should point to the Helm repository where your chart is located.
      • The chart field should be the name of the Helm chart you wish to deploy.
      • The values field allows you to specify configuration values that the Helm chart accepts.
      • The fetchOpts field can be used to provide credentials for private Helm repositories if required.
    • Finally, this program exports the API URL as an output, which you can use to interact with the deployed service.

    Remember, this code assumes you have already set up your Pulumi account, configured the Pulumi CLI, and have access to your OpenShift cluster through kubectl.

    Execute this Pulumi program using these basic commands after navigating to the directory containing your Pulumi program file (index.ts):

    pulumi up

    This command will start the Pulumi deployment process, and you will see a preview of the resources to be created. Upon confirming the action, Pulumi will proceed with the deployment of the Helm chart to your OpenShift cluster.