1. Deploy the pypi-server helm chart on AWS EKS

    TypeScript

    To deploy the pypi-server Helm chart on AWS EKS (Elastic Kubernetes Service), you'll need to follow several steps. These include setting up the EKS cluster, configuring your Kubernetes provider to interact with the cluster, and then deploying the Helm chart to the EKS cluster. I'll provide a detailed Pulumi program in TypeScript that demonstrates how to perform each of these steps.

    Firstly, you'll need to create an EKS cluster using the aws.eks.Cluster resource. You'll also need an IAM role that the EKS service can assume to create AWS resources for Kubernetes workloads.

    Once the EKS cluster is ready, you'll configure a Kubernetes provider to interact with your cluster. This provider will be used to deploy the pypi-server Helm chart.

    Note: The pypi-server Helm chart should be available in a Helm repository. In this example, we'll assume that you've added the repository and that the chart is ready to be deployed. If the chart requires specific values, you would pass them using the values property when creating the Helm chart resource.

    Now let's begin writing the Pulumi program in TypeScript:

    import * as aws from "@pulumi/aws"; import * as awsx from "@pulumi/awsx"; import * as eks from "@pulumi/eks"; import * as k8s from "@pulumi/kubernetes"; import * as pulumi from "@pulumi/pulumi"; // Create an EKS cluster. const cluster = new eks.Cluster("pypi-cluster", { instanceType: "t2.medium", desiredCapacity: 2, minSize: 1, maxSize: 3, storageClasses: "gp2", deployDashboard: false, // Dashboard is optional. }); // Export the cluster's kubeconfig. export const kubeconfig = cluster.kubeconfig; // Create a Kubernetes provider instance that uses our EKS cluster. const provider = new k8s.Provider("pypi-provider", { kubeconfig: cluster.kubeconfig.apply(JSON.stringify), }); // Deploy the pypi-server Helm chart to the EKS cluster. const pypiServerChart = new k8s.helm.v3.Chart("pypi-server", { chart: "pypi-server", version: "1.2.3", // Replace with the actual chart version you want to deploy. fetchOpts: { repo: "https://helm-repo-url.com", // Replace with the actual Helm repo URL. }, // Specify required values according to the pypi-server chart's documentation. values: { // ... Specify your custom values here }, }, { provider }); // Make sure to pass the provider we created earlier. // Export the pypi-server service endpoint to access the deployed server externally. export const pypiServerEndpoint = pypiServerChart.getResource("v1/Service", "pypi-server").status.loadBalancer.ingress[0].hostname;

    In the program above:

    • We define an EKS cluster with a desired capacity of 2 worker nodes.
    • We export the cluster's kubeconfig, which provides the necessary details to connect to the Kubernetes cluster with kubectl or any Kubernetes client library.
    • We create a new Provider that is configured to connect to our EKS cluster.
    • We deploy the pypi-server Helm chart using Pulumi's Kubernetes provider. We specify the chart's name and version and provide a repository URL where the Helm chart is located.
    • We export the endpoint that can be used to interact with the pypi-server once it is deployed.

    Make sure to replace the placeholders, like chart version and repo, with the actual values corresponding to the pypi-server Helm chart you wish to deploy. The values property should contain configuration specific to your needs, following the Helm chart's documentation.

    When you run this Pulumi program, it will provision all the required AWS and Kubernetes resources, and then deploy the pypi-server Helm chart on the EKS cluster. Once deployed, you can access the pypi-server using the exported hostname.

    For more information about the individual resources used in this Pulumi program, you can refer to the following documentation:

    The specific classes and properties used in the code ensure you have an appropriate setup for running the pypi-server Kubernetes application, complete with an EKS cluster and Helm chart deployment.