1. Deploy the zotero helm chart on Azure Managed Openshift Service


    To deploy the Zotero Helm chart on an Azure Managed OpenShift service using Pulumi, you'll need to perform a few steps:

    1. Set up an Azure Managed OpenShift cluster to run your Helm charts on.
    2. Install the Helm chart for Zotero onto the OpenShift cluster.

    Azure Managed OpenShift (ARO) provides a fully managed OpenShift cluster, maintained jointly by Microsoft and Red Hat. This gives you the convenience of a managed service with the flexibility of OpenShift for orchestration.

    A Helm chart is a collection of pre-configured Kubernetes resources that can be deployed as a single unit. Zotero does not have an official Helm chart, so we will consider using a generic Helm chart as a placeholder in this example.

    Below, I'll provide a Pulumi TypeScript program that sets up an ARO cluster and then deploys a generic Helm chart to this cluster. Replace the generic chart with the specific details of the Zotero Helm chart when it's available or if you have created a custom Helm chart for Zotero.

    Before you begin, make sure you have the following prerequisites met:

    • Pulumi CLI installed.
    • Azure CLI installed and configured with your credentials.
    • Pulumi account set up with an appropriate stack selected (or create a new one).

    Now, let's look at the Pulumi program:

    import * as pulumi from "@pulumi/pulumi"; import * as azureNative from "@pulumi/azure-native"; import * as kubernetes from "@pulumi/kubernetes"; import * as openshift from "@pulumi/azure-native/redhatopenshift"; // Create an Azure Resource Group const resourceGroup = new azureNative.resources.ResourceGroup("resourceGroup", { location: "eastus", // Choose the appropriate Azure region }); // Set up the Azure Red Hat OpenShift cluster const openshiftCluster = new openshift.OpenShiftCluster("openshiftCluster", { location: resourceGroup.location, resourceGroupName: resourceGroup.name, // Other necessary configurations like network profile, master and worker profiles, etc. // This is a simplified configuration, you must specify other parameters as needed. clusterProfile: { domain: "example-domain", // Replace with your domain name version: "4.3.0", // Specify the OpenShift cluster version you want to use }, masterProfile: { vmSize: "Standard_D2s_v3", // Choose the virtual machine size for master nodes }, workerProfiles: [{ name: "worker", // Name for the worker node profile count: 3, // Number of worker nodes you want to start with vmSize: "Standard_D2s_v3", // Choose the virtual machine size for worker nodes }], }); // Configure k8s provider to deploy Helm charts on top of the ARO cluster const k8sProvider = new kubernetes.Provider("k8sProvider", { kubeconfig: openshiftCluster.kubeconfig, // The kubeconfig output comes from the OpenShift cluster resource }); // Deploy a Helm chart on the OpenShift cluster const zoteroHelmChart = new kubernetes.helm.v3.Chart("zoteroHelmChart", { chart: "zotero", // Replace with the actual Helm chart name for Zotero if available version: "1.0.0", // Replace with the Helm chart version namespace: "default", // You can specify a namespace or use the default // Values here must be configured to match the expectations of the actual Zotero Helm chart values: { // Configuration values for the Helm chart, modify as needed }, }, { provider: k8sProvider }); // Export the cluster's kubeconfig export const kubeconfig = openshiftCluster.kubeconfig;

    This code sets up an Azure Resource Group, provisions an Azure Red Hat OpenShift cluster, and then deploys a Helm chart, which in this example is a placeholder for Zotero, onto that cluster using the Pulumi Kubernetes provider.

    Please ensure the details, especially the Helm chart details (chart and values), match your requirements for the Zotero Helm chart. You may need to consult the Helm chart's documentation or values file to determine what configuration options you need to set. Since Zotero does not have an official Helm chart, you would typically use a custom chart created by your team or a community chart, making sure to test it thoroughly before production use.

    Remember, when you run your Pulumi program with pulumi up, it will prompt you for confirmation before making changes to your cloud resources. Always review the proposed changes before confirming to avoid unwanted effects.