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

Question

Pulumi · Accepted Answer

To deploy the `mlflow-server` Helm chart on Azure Kubernetes Service (AKS), you will first need to set up an AKS cluster using Pulumi, and then deploy the chart to this cluster. The Pulumi program below will guide you through these steps. We use the `@pulumi/azure-native` package to create the AKS cluster and `@pulumi/kubernetes` to manage Kubernetes resources like the Helm chart.

Here's how the process will unfold:
1. **Setting up an AKS Cluster**: We set up a new AKS cluster with a specified node count, VM size, and Kubernetes version. We include an SSH key for accessing nodes.
2. **Deploying the mlflow-server Helm Chart**: Once the AKS cluster is available, we configure Kubernetes provider to deploy Helm charts to that cluster. Then we deploy `mlflow-server` using the Helm chart available in a public repository.

Below is the program in TypeScript. I've provided comments throughout the code to explain each step.

```typescript
import * as pulumi from '@pulumi/pulumi';
import * as azureNative from '@pulumi/azure-native';
import * as k8s from '@pulumi/kubernetes';

// Step 1: Create a new AKS cluster
const resourceGroup = new azureNative.resources.ResourceGroup('myResourceGroup');

const aksCluster = new azureNative.containerservice.ManagedCluster('myAksCluster', {
    resourceGroupName: resourceGroup.name,
    agentPoolProfiles: [{
        count: 2, // Number of nodes in the Node Pool
        vmSize: 'Standard_DS2_v2', // VM size for the nodes
        mode: 'System', // Mode for the agent pool
        name: 'agentpool', // Name of the agent pool
    }],
    dnsPrefix: 'myakscluster', // DNS prefix for AKS
    enableRBAC: true, // Enable RBAC for the cluster
    kubernetesVersion: '1.19.11', // Specify the version of Kubernetes
    linuxProfile: {
        adminUsername: 'adminuser', // Admin username for the nodes
        ssh: {
            publicKeys: [{ keyData: 'ssh-rsa ...' }], // SSH public key to access the nodes
        },
    },
    // ... other necessary configurations for the cluster
});

// Export the cluster's kubeconfig
export const kubeconfig = aksCluster.kubeConfig;

// Step 2: Deploy the mlflow-server Helm chart
const myK8sProvider = new k8s.Provider('myK8sProvider', {
    kubeconfig: kubeconfig,
});

const mlflowServerChart = new k8s.helm.v3.Chart('mlflowServer', {
    chart: 'mlflow',
    version: '1.0.0', // Specify the version of the Helm chart
    fetchOpts: {
        repo: 'http://your-helm-chart-repository/', // Replace with Helm chart repository containing mlflow
    },
}, { provider: myK8sProvider });

// Export the endpoint of the mlflow server
export const mlflowServerEndpoint = mlflowServerChart.getResourceProperty('v1/Service', 'mlflow-server', 'status').apply(status => status.loadBalancer?.ingress[0]?.ip);
```

Ensure you have the correct SSH public key and the Helm chart repository URL before trying to run this Pulumi program. If you don't have a specific version for the `mlflow-server` Helm chart, you might need to check the chart repository for the available versions or omit the `version` property to use the latest one.

To apply this Pulumi program:
1. Save the code to a file with a `.ts` extension, for example `deployMlflowServer.ts`.
2. Run `pulumi up` from the command line in the same directory as your code, making sure you've selected the correct subscription and authenticated with Azure.

After running the program, Pulumi will provide you with the endpoint for the deployed MLflow server, which you can use to interact with your MLflow instance.