Setting up a private endpoint for Azure Cognitive Search integration

Question

Pulumi · Accepted Answer

To set up a private endpoint for Azure Cognitive Search integration using Pulumi, we'll need to create a few resources including an Azure Search Service, a VNet with a subnet, and a Private Endpoint resource. We'll use the `azure-native` Pulumi provider, which allows us to interact with the resources in the Azure Cloud.

The following TypeScript program with Pulumi will set up the necessary resources:

1. **Azure Search Service**: A managed search service that allows you to index and query data.
2. **Virtual Network (VNet) & Subnet**: A VNet is necessary for the Private Endpoint to ensure traffic stays inside the Azure network, and a subnet is a range of IP addresses in the VNet.
3. **Private Endpoint**: This enables a private connection to your Azure Cognitive Search service.

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

// Create an Azure Resource Group
const resourceGroup = new azure.resources.ResourceGroup("my-resource-group");

// Create an Azure Search Service
const searchService = new azure.search.SearchService("my-search-service", {
    resourceGroupName: resourceGroup.name,
    sku: {
        // Set the SKU to Basic or Standard for production use cases
        name: "basic",
    },
    // Set to 'none' to disable public network access. When using a private endpoint, set this to 'enabled'.
    publicNetworkAccess: "enabled",
});

// Create a Virtual Network with a Subnet for the private endpoint
const vnet = new azure.network.VirtualNetwork("my-vnet", {
    resourceGroupName: resourceGroup.name,
    addressSpace: {
        addressPrefixes: ["10.0.0.0/16"],
    },
    subnets: [{
        name: "my-subnet",
        // The address range for the subnet, within the VNet address space
        addressPrefix: "10.0.0.0/24",
        // Enable the subnet to create private endpoint on it
        privateEndpointNetworkPolicies: "Disabled",
    }],
});

// Create a Private Endpoint for the Azure Cognitive Search
const privateEndpoint = new azure.network.PrivateEndpoint("my-private-endpoint", {
    resourceGroupName: resourceGroup.name,
    subnet: {
        id: vnet.subnets[0].id,
    },
    privateLinkServiceConnections: [{
        name: "searchConnection",
        privateLinkServiceId: searchService.id,
        groupIds: ["search"],
    }],
    manualPrivateLinkServiceConnections: [],
    // Locate the Private Endpoint in the same location as the Resource Group
    location: resourceGroup.location,
});

// Export the URL of the Azure Search Service to access it in your application
export const searchServiceUrl = pulumi.interpolate`https://${searchService.name}.search.windows.net/`;

// Export the ID of the private endpoint
export const privateEndpointId = privateEndpoint.id;
```

Explanation of the code:

- We start by creating a new Azure Resource Group, which is a container that holds related resources for an Azure solution.
- Next, we set up an Azure Search Service which is a managed service provided by Azure for indexing and searching data.
- We then create an Azure Virtual Network and a Subnet. The Azure Virtual Network (VNet) is the fundamental building block for private networks in Azure, while the subnet is a required resource that allows us to create the Private Endpoint for the Azure Cognitive Search service.
- The Private Endpoint is created to establish a private access to the Azure Cognitive Search service. We link it to the subnet we created earlier and the Search Service.
- We then export two key values as outputs: the URL of the Search Service and the ID of the Private Endpoint.

After running your Pulumi program, you'll have the necessary infrastructure in place to securely integrate your applications with the Azure Cognitive Search service using a private endpoint, thereby enhancing security and reducing exposure to the public internet.