1. VNet Integration for Azure AI Platform Services

    Python

    When you want to integrate your Azure AI Platform Services with an Azure Virtual Network (VNet), you're essentially looking to ensure that resources within your AI Platform can communicate securely with resources that are contained within a VNet. This integration can be beneficial for a variety of reasons such as ensuring data stays within your private network, enhanced security, and compliance with organizational policies.

    To set up VNet Integration with Azure AI Platform Services using Pulumi, you'd typically work with resources like PrivateEndpointConnection and VirtualNetwork rules, among others, depending on the specific Azure services you're integrating. Below is an example program in Python that demonstrates how you could set up such an integration using Pulumi.

    Before diving into the code, let's briefly discuss the resources we'll use:

    1. Network and Subnet: We'll start by defining a virtual network (VNet) and a subnet, which is a range of IP addresses in the VNet where your service endpoints will reside.

    2. Private Endpoint: This allows you to secure and privately access Azure service resources from a virtual network. A private endpoint is a set of private IP addresses in a subnet within your virtual network. It provides a secure connection between clients on your VNet and your Azure services.

    3. Private DNS Zone: A DNS zone used for name resolution for a private endpoint within your VNet. It's crucial for ensuring that the network traffic between your AI services and the VNet remains on the Microsoft Azure backbone network.

    4. Private Endpoint Connection: Represents the integration between an Azure service and a private endpoint. It's a necessary step to establish the connection.

    Now let's proceed with the example Pulumi program:

    import pulumi import pulumi_azure_native as azure_native # Create a new resource group resource_group = azure_native.resources.ResourceGroup('ai-vnet-integration-rg') # Create a new virtual network (VNet) with a specified address space virtual_network = azure_native.network.VirtualNetwork( 'ai-vnet', resource_group_name=resource_group.name, address_space=azure_native.network.AddressSpaceArgs( address_prefixes=['10.0.0.0/16'], ) ) # Create a subnet in the virtual network where the AI services will be connected subnet = azure_native.network.Subnet( 'ai-subnet', resource_group_name=resource_group.name, virtual_network_name=virtual_network.name, address_prefix='10.0.1.0/24', private_endpoint_network_policies='Disabled', private_link_service_network_policies='Disabled', ) # Create a private DNS zone for the Azure AI Service private_dns_zone = azure_native.network.PrivateDnsZone( 'ai-private-dns-zone', resource_group_name=resource_group.name, zone_name='<your-AI-service>.privatelink.azure.net' # Replace with your AI service private link ) # Establish an association between the subnet and the private DNS zone subnet_dns_zone_link = azure_native.network.PrivateDnsZoneVirtualNetworkLink( 'ai-subnet-dns-zone-link', resource_group_name=resource_group.name, private_dns_zone_name=private_dns_zone.name, virtual_network_id=virtual_network.id, ) # Create a private endpoint for the AI service private_endpoint = azure_native.network.PrivateEndpoint( 'ai-private-endpoint', resource_group_name=resource_group.name, subnet=azure_native.network.SubnetArgs( id=subnet.id, ), private_link_service_connections=[azure_native.network.PrivateLinkServiceConnectionArgs( name='ai-private-link-service-connection', private_link_service_id='<resource-id-of-your-AI-service>', # Replace with the resource ID of your AI Service group_ids=['<group-id>'], # Replace with the relevant group ID for your AI service )], location=resource_group.location, ) # Output the private endpoint network interface ID pulumi.export('private_endpoint_network_interface_id', private_endpoint.network_interfaces) # When setting this up for a real service, make sure to replace placeholders such as '<your-AI-service>' with the actual values.

    This code establishes a VNet with a subnet where the AI service's private endpoint will reside. It then sets up a private DNS zone for name resolution and links it to our subnet. Lastly, we create the private endpoint and associate it with the AI service.

    Please note you need to replace placeholder values like <your-AI-service> with the actual service you're working with, and similarly, update <resource-id-of-your-AI-service> with the ID of the Azure AI service resource you want to set up VNet integration for.

    Also note that this code assumes that you've already set up your Pulumi and Azure credentials, and may need additional context (such as the AI service you're using and its specific configuration) which is beyond the scope of this example. It should, however, give you a starting point to integrate these services with Pulumi.