1. Deploy the polyaxon helm chart on Kubernetes

    TypeScript

    Deploying a Helm chart on Kubernetes using Pulumi is a process that involves creating a Kubernetes cluster (if you don't already have one) and then managing the deployment of the Helm chart on that cluster. Polyaxon is a platform for reproducible and scalable machine learning and deep learning on Kubernetes. To deploy the Polyaxon Helm chart, you'll need access to a Kubernetes cluster and the Helm CLI installed and configured.

    Below, you will find a program written in TypeScript that uses Pulumi to deploy the Polyaxon Helm Chart on an existing Kubernetes cluster. If you don't have a cluster, you would first need to create one using Pulumi or use an existing one.

    The program uses the kubernetes.helm.v3.Chart resource from Pulumi's Kubernetes provider to deploy the Helm chart. This Pulumi resource allows us to specify the chart details, such as the chart name, version, and any custom values needed for the configuration.

    Here's a step-by-step Pulumi program for deploying the Polyaxon Helm chart:

    import * as k8s from "@pulumi/kubernetes"; // Replace the following variables with appropriate values. const chartName = "polyaxon"; const chartVersion = "YOUR_CHART_VERSION"; // Specify the chart version you wish to deploy const releaseName = "polyaxon-release"; // The release name for the chart const namespace = "polyaxon"; // The namespace where the chart should be installed // If you have custom values you want to override in the chart, put them in this object. const values = { // Provide your configuration values here. For example: // user: { // username: "admin", // password: "password", // }, // persistence: { // enabled: true, // size: "50Gi", // }, // ...other values based on Polyaxon's chart documentation }; // Create a Helm Chart resource for the Polyaxon Helm chart. const polyaxonChart = new k8s.helm.v3.Chart(releaseName, { chart: chartName, version: chartVersion, namespace: namespace, fetchOpts: { repo: "http://charts.polyaxon.com", // This is the default Polyaxon Helm chart repository. }, values: values, }); // Export the Chart's status URL, which can be used to access the Polyaxon web interface, after it gets deployed. export const polyaxonStatusUrl = polyaxonChart.getResourceProperty("v1/Service", namespace, "polyaxon-polyaxon-gateway", "status.loadBalancer.ingress[0].hostname"); // Note: The exact way to retrieve the status URL may vary depending on your cluster's configuration and the services set up by the Polyaxon chart. // You might need to adjust the `getResourceProperty` call to match the service and output you are expecting.

    Here's what the program is doing:

    1. The Kubernetes package is imported under the k8s alias.
    2. The desired chart name, version, release name, and namespace are set. These should match the chart you wish to deploy and the environment in which you want to deploy it.
    3. A values object is declared, which would contain any overrides from the default configuration of the Polyaxon Helm chart. You can customize the configuration by referring to the official Polyaxon Helm chart documentation for the configurable values.
    4. A new Helm chart resource is created using k8s.helm.v3.Chart. We specify the chart details and the repository where the Helm chart is located.
    5. Finally, the program exports the polyaxonStatusUrl, which you can use to check the status and access the Polyaxon web interface once it's up and running. Depending on how you've configured your Kubernetes Service for Polyaxon, this may manifest as an external IP or a DNS name. You will likely need to inspect your deployed resources to get the exact URL.

    To run this Pulumi program, you need to have Pulumi CLI installed and a Pulumi project set up. In the project folder, save this code in a file named index.ts, then run pulumi up to perform the deployment. Make sure you have the correct context set for kubectl if you are working with a specific cluster. You should also have the required permissions to deploy Helm charts in the target Kubernetes cluster.