1. Deploy the keras-env helm chart on AWS EKS


    To deploy the keras-env Helm chart on AWS Elastic Kubernetes Service (EKS), we'll create a Pulumi program in TypeScript. The program will perform the following tasks:

    1. Set up an EKS cluster using Pulumi's EKS package.
    2. Deploy the keras-env Helm chart on the EKS cluster using the Helm package from Pulumi's Kubernetes provider.

    Before we begin coding, you need to have Pulumi CLI installed, AWS credentials configured, and the necessary Pulumi packages (eks and kubernetes) installed for your project. Here's how the TypeScript program will look:

    import * as eks from "@pulumi/eks"; import * as k8s from "@pulumi/kubernetes"; // Create an EKS cluster. const cluster = new eks.Cluster("my-cluster", { // Specify the desired settings for the cluster here. // For example, you can define the number of nodes, node size, etc. }); // Export the clusters' kubeconfig. export const kubeconfig = cluster.kubeconfig; // Create a Kubernetes provider instance using the kubeconfig from the created EKS cluster. const provider = new k8s.Provider("provider", { kubeconfig: cluster.kubeconfig, }); // Deploy the keras-env chart using the Helm Chart resource. const kerasEnvChart = new k8s.helm.v3.Chart("keras-env", { chart: "keras-env", // If your Helm chart is in a Helm repository, you need to specify `repo` property. // If it's a local chart, you need to specify `path` property. // Values below are placeholders and should be updated accordingly. // repo: "http://example.com/helm", // path: "./path-to-local-helm-chart", values: { // Specify any values required by the keras-env chart here. }, }, { provider }); // Export the status URL of the deployed Helm chart. export const kerasEnvStatusUrl = kerasEnvChart.status.apply(status => status.url);


    • We first import the necessary modules from @pulumi/eks to create an EKS cluster and from @pulumi/kubernetes to handle Kubernetes resources and Helm charts.

    • Next, we create an EKS cluster with new eks.Cluster("my-cluster", {...}). This object can be customized with different parameters like the desired node count, node type, etc. For detailed customization options, refer to the EKS.Cluster documentation.

    • Once the cluster is up, we export its kubeconfig. This configuration is used by the Kubernetes provider to communicate with your cluster.

    • The new k8s.Provider("provider", {...}) instance uses the kubeconfig from the EKS cluster. This provider will allow us to deploy Kubernetes resources, including Helm charts, on the EKS cluster.

    • Then, we create a Helm chart resource with new k8s.helm.v3.Chart("keras-env", {...}, { provider }). Here, you should provide the correct chart name and the repository if it's hosted remotely, or the path to the local directory containing the chart. Additionally, any custom values that the chart requires should be specified.

    • Finally, we export a status URL (if applicable) for the Helm release. This could be a dashboard URL or some other endpoint relevant to the keras-env deployment, depending on what the chart provides.

    Remember to replace placeholder values such as chart repo or path and values with actual information pertinent to the keras-env chart you wish to deploy.