Deploy the mlflow-helm-chart helm chart on Azure Kubernetes Service (AKS)

Question

Pulumi · Accepted Answer

To deploy the `mlflow-helm-chart` on an Azure Kubernetes Service (AKS) cluster using Pulumi, you would first need to ensure you have an AKS cluster created and configured, which you can do with Pulumi's `azure-native` package. Next, you would deploy the Helm chart to AKS using `kubernetes.helm.v3.Chart` from the `@pulumi/kubernetes` package.

Here's how this process might look:

1. **Create an AKS cluster**: Define an AKS cluster in your Pulumi program.
2. **Configure Kubernetes provider**: Use the cluster's kubeconfig to configure your Kubernetes provider so that Pulumi can communicate with your AKS cluster.
3. **Deploy Helm Chart**: Finally, use the Helm Chart resource to deploy your `mlflow-helm-chart` onto the AKS cluster.

Below is a TypeScript program that demonstrates these steps:

```typescript
import * as pulumi from "@pulumi/pulumi";
import * as azure_native from "@pulumi/azure-native";
import * as k8s from "@pulumi/kubernetes";

const config = new pulumi.Config();

// This assumes that the Pulumi program is configured with the necessary Azure settings, such as subscription, client ID, and tenant ID.

// Step 1: Create the AKS cluster
const resourceGroup = new azure_native.resources.ResourceGroup("myResourceGroup");

const cluster = new azure_native.containerservice.ManagedCluster("myAksCluster", {
    resourceGroupName: resourceGroup.name,
    kubernetesVersion: "1.18.14",
    agentPoolProfiles: [{
        count: 3,
        vmSize: "Standard_DS2_v2",
        osType: "Linux",
        mode: "System",
        name: "agentpool" // Name of the agent pool
    }],
    dnsPrefix: `${pulumi.getStack()}-kubernetes`,
    linuxProfile: {
        adminUsername: "testuser",
        ssh: {
            publicKeys: [{
                keyData: "ssh-rsa AAAAB3NzaC1yc2EAAAADAQABAAACAQD..."
            }],
        },
    },
    identity: {
        type: "SystemAssigned"
    }
});

// Export the kubeconfig
export const kubeconfig = cluster.kubeConfig;

// Step 2: Configure the Kubernetes provider to use the kubeconfig from the created AKS cluster
const k8sProvider = new k8s.Provider("k8sProvider", {
    kubeconfig: cluster.kubeConfig.apply(kc => kc),
});

// Step 3: Deploy the mlflow-helm-chart using the Helm Chart resource
const mlflowChart = new k8s.helm.v3.Chart("mlflow-helm-chart", {
    chart: "mlflow",
    // This assumes that the "mlflow" chart is available in the specified Helm repository.
    // Make sure to specify the correct Helm repository URL and chart name.
    version: "0.1.0",
    fetchOpts: {
        repo: "http://myhelmrepo.com"
    },
}, { provider: k8sProvider });

// Export the mlflow Helm chart deployment status
export const mlflowChartStatus = mlflowChart.status;
```

### Explanation:

- **Resource Group**: This is the fundamental Azure resource that contains and groups other resources like AKS clusters and other services.

- **Managed Cluster**: This AKS cluster is created with one system mode agent pool which is the node pool that the Kubernetes workloads will run on. The provided `kubernetesVersion` would be the version of Kubernetes that you want to use on your AKS cluster. The `dnsPrefix` ensures your API server has a unique DNS name within Azure.

- **Kubeconfig**: The output from the Managed Cluster, which contains credentials for accessing the Kubernetes cluster. This is required for setting up the Kubernetes provider.

- **Kubernetes Provider**: This provider allows Pulumi to interact with the Kubernetes cluster, deploying resources onto it.

- **Helm Chart**: This is a Pulumi resource that represents a Helm chart deployment. It uses the chart name and version you specify, along with the repo where the chart is hosted. You need to make sure the `mlflow` exists in the specified repository.

Remember to replace placeholder values with actual values appropriate for your scenario, such as `keyData` with your actual SSH public key, and the `repo` with the location of the Helm chart for `mlflow`.

Once the program is ready, you would run it using the Pulumi CLI. First, you would execute `pulumi up` to provision the resources. The resources will be deployed in the following order: the resource group, the AKS cluster, and then the Helm chart will be deployed to that cluster.