Using azure appconfiguration with databricks

Question

Pulumi · Accepted Answer

In order to use Azure App Configuration with Databricks using Pulumi, you will need to create the App Configuration resource within Azure and then make it available to your Databricks workspace and jobs. There isn't a direct resource for configuring App Configuration integration within the Databricks resource on Pulumi, but I'll guide you through setting up the App Configuration Service and accessing its values from a Databricks job.

### Azure App Configuration

Azure App Configuration is a managed service that helps developers centralize their application and feature settings simply and securely. It provides a way to import, export, and manage application settings across environments and applications.

### Databricks

Azure Databricks is an analytics platform powered by Apache Spark. It's optimized for the Microsoft Azure cloud services platform and is used to process and transform massive quantities of data and integrate with other Azure services.

Here's a program written in TypeScript that sets up an Azure App Configuration and integrates it with Databricks. Keep in mind that you will need to have the Pulumi CLI configured with your Azure account credentials.

First, you will start by creating an App Configuration resource, and then you will reference the connection strings needed to access this configuration within a Databricks workspace or job.

```typescript
import * as azure from "@pulumi/azure-native";
import * as databricks from "@pulumi/databricks";

// Create an Azure Resource Group
const resourceGroup = new azure.resources.ResourceGroup("appconfigResourceGroup");

// Create an Azure App Configuration
const appConfig = new azure.appconfiguration.ConfigurationStore("appConfigStore", {
    resourceGroupName: resourceGroup.name,
    location: resourceGroup.location, // Use the same location as the resource group
    sku: {
        name: "Standard", // The SKU of the App Configuration
    },
});

// Create an Azure Databricks workspace
const workspace = new azure.databricks.Workspace("databricksWorkspace", {
    resourceGroupName: resourceGroup.name,
    location: resourceGroup.location,
    sku: {
        name: "standard", // Choose an appropriate SKU for your usage
    },
    // Other necessary configurations here
});

// The following steps are conceptual and require setting up access to Azure App Configuration from inside the Databricks notebooks, jobs, or clusters.
// For example, you may have a Databricks job that needs to pull configuration settings
// You will have to pass the connection string or App Configuration details to the Databricks job using environment variables or Databricks secrets

// Since there is no direct support in Pulumi's databricks provider for App Configuration,
// you will typically manage configuration details programmatically within your Databricks notebooks or jobs,
// such as using `dbutils` or the `databricks-cli`.

// Output the connection string of the App Configuration to use in the Databricks job
export const appConfigConnectionString = appConfig.primaryReadKey.apply(key => key.connectionString);

// Be sure to secure your connection string and consider using Azure Key Vault or Databricks secrets for storing sensitive information
```

### Explanation

1. **Resource Group**: A resource group is a container that holds related resources for an Azure solution. In the example, a new resource group is created to keep the resources organized.

2. **App Configuration**: This is the Azure App Configuration instance that stores configuration data.

3. **Databricks Workspace**: A Databricks workspace is an environment for accessing all of your Databricks assets. The workspace organizes objects (notebooks, libraries, and experiments) into folders and provides access to data and computational resources such as clusters and jobs.

4. **Connection String Export**: At the end of the script, the connection string for the App Configuration is exported. This connection string is used to connect to the App Configuration from your application or service. It's important to handle this connection string securely.

5. **Security**: Remember to secure your secrets. Instead of exporting the connection string, which might expose sensitive data, consider using [Azure Key Vault](https://www.pulumi.com/registry/packages/azure-native/api-docs/keyvault/vault/) to store and manage secrets that you can reference in your Databricks jobs.

### Next Steps

- Install the necessary packages like `@pulumi/azure-native` and `@pulumi/databricks` if you haven't already.
- Write the actual data processing or analytics tasks within Databricks notebooks or jobs.
- Use the App Configuration within your Databricks job by fetching the configurations from the App Configuration using the connection string and applying them to your application logic.

This program is a starting point and sets up the necessary infrastructure to use Azure App Configuration with Databricks. You would need to add additional logic within your Databricks notebooks, jobs, or clusters to consume the configuration values you've stored in the Azure App Configuration.