1. Deploy the cloudbees-core helm chart on Azure Kubernetes Service (AKS)

    TypeScript

    In order to deploy the CloudBees Core Helm chart on AKS using Pulumi, we'll perform the following steps:

    1. Set up the Azure Kubernetes Service (AKS): First, we need to create an AKS cluster to deploy our applications to. We will use ProvisionedCluster from the azure-native package which represents an AKS cluster.

    2. Deploy the CloudBees Core Helm chart: Once the AKS cluster is up, we will deploy the CloudBees Core Helm chart using the Chart resource from the kubernetes package.

    Here's a step-by-step guide on how this can be achieved using Pulumi with TypeScript:

    Step 1: Import Required Pulumi Libraries

    We need to import the Pulumi packages for Azure and Kubernetes. Make sure you have the Pulumi CLI installed and configured for Azure access.

    Step 2: Create a New Pulumi Project

    Initialize a new Pulumi project and install dependencies. You can do this by running the Pulumi CLI commands:

    pulumi new azure-typescript

    After choosing 'yes' to installing dependencies, you will also need to add the Kubernetes package:

    npm install @pulumi/kubernetes

    Step 3: Write the Pulumi Program

    Now, we write the Pulumi program that will create an AKS cluster and deploy the CloudBees Core Helm chart onto it.

    import * as pulumi from "@pulumi/pulumi"; import * as azure_native from "@pulumi/azure-native"; import * as k8s from "@pulumi/kubernetes"; // Step 1: Create an AKS cluster const resourceGroup = new azure_native.resources.ResourceGroup("resourceGroup"); const aksCluster = new azure_native.hybridcontainerservice.ProvisionedCluster("aksCluster", { resourceName: "myAKSCluster", resourceGroupName: resourceGroup.name, location: resourceGroup.location, properties: { controlPlane: { mode: "System", count: 1, vmSize: "Standard_D2s_v3", }, }, }); // Export the kubeconfig for the newly created AKS cluster export const kubeconfig = aksCluster.properties.controlPlane.endpoint.kubeConfig; // Step 2: Deploy the CloudBees Core Helm chart onto the AKS cluster const cloudbeesChart = new k8s.helm.v3.Chart("cloudbees-core", { chart: "cloudbees-core", version: "<version>", // specify the version of CloudBees Core you wish to deploy fetchOpts: { repo: "https://downloads.cloudbees.com/cloudbees-core/cloud/official/helm-charts/", }, }, { provider: new k8s.Provider("k8s-provider", { kubeconfig: kubeconfig }) }); // Export the AKS cluster name export const clusterName = pulumi.output(aksCluster).name;

    Step 4: Deploy the Pulumi Program

    Deploy the Pulumi program using the Pulumi CLI:

    pulumi up

    This command will show a preview of the resources that Pulumi will create or modify. After reviewing the changes, you can select 'yes' to proceed with the deployment.

    Explanation of the Program

    • Resource Group: We create a new Azure Resource Group to manage all the resources in a grouped way.

    • AKS Cluster: The ProvisionedCluster resource from the azure-native.hybridcontainerservice package is used to create the AKS cluster. We configure the controlPlane with a single node of the Standard_D2s_v3 size.

    • Kubeconfig: We export the kubeconfig of the created AKS cluster, which allows us to interact with the cluster using kubectl or other Kubernetes tooling.

    • Helm Chart: The Chart resource from the kubernetes.helm.sh/v3 package is used to deploy the CloudBees Core Helm chart to the AKS cluster. The kubeconfig is used by the Kubernetes provider to connect to the AKS cluster.

    • CloudBees Helm Chart: We specify the chart name, version, and the Helm repo URL where the chart is located. This will pull the specified version of the helm chart from the CloudBees Helm chart repository.

    • Exports: We export the kubeconfig and the cluster name, which can be used for managing the cluster after the deployment.

    After Deployment

    Once the chart is deployed, CloudBees Core will be running on your AKS cluster. You can manage and access it using tools that interact with Kubernetes, such as kubectl, or the Kubernetes dashboard.

    Remember, this is a basic setup, and for any production environment, you should consider additional factors such as node scaling options, networking configuration, security settings, and proper identity management.