Decentralized AI Model Training with Azure Private DNS Zones

Question

Pulumi · Accepted Answer

Decentralized AI model training typically involves distributing the computation across multiple machines, which may not necessarily be located within the same network or data center. To facilitate communication between these machines in a secure and reliable manner, while keeping the traffic internal to Azure, you would use Azure Private DNS zones.

Azure Private DNS provides a reliable and secure DNS service to manage and resolve domain names in a virtual network without needing to add a custom DNS solution. This enables you to use your own domain names, rather than the Azure-provided names. Using Azure Private DNS, you can ensure that the domain name resolution for your AI model training nodes is kept within the Azure network, reducing latency and maintaining privacy.

Below is a program written in Python using Pulumi, which sets up a private DNS zone in Azure. This program will:

Create a resource group to contain all the Azure resources.
Provision a Private DNS Zone within the virtual network where your AI model training resources reside.
Link the Private DNS Zone to your virtual network.

I’ll walk you through the whole process step by step.

First, make sure you have the required Pulumi imports:

import pulumi
import pulumi_azure_native as azure_native

Next, let's create a resource group:

# Create a new resource group for our DNS zone and related resources
resource_group = azure_native.resources.ResourceGroup('model-training-rg')

Then, you can proceed to create a Private DNS zone within this resource group:

# Create a Private DNS Zone where AI model training nodes can resolve DNS queries within Azure's network.
private_dns_zone = azure_native.network.PrivateZone(
    "training-dns-zone",
    resource_group_name=resource_group.name,
    location="Global", # Azure Private DNS zones are global resources
    private_zone_name="training.example.com" # Replace with your desired DNS zone name
)

# In order to manage the DNS records for a particular domain, replace "training.example.com" with your domain name.
# The resulting records would look like "node1.training.example.com", which could resolve to an internal IP.

To enable the nodes in your virtual network to resolve domain names in this private zone, create a link between the zone and the virtual network:

# Link the private DNS zone to the virtual network of your AI model training cluster
# Let's assume we have a Virtual Network called `training_vnet` in the same resource group
# Replace `<<ExistingVirtualNetworkId>>` with the actual resource ID of your virtual network.

vnet_link = azure_native.network.VirtualNetworkLink(
    "training-vnet-link",
    resource_group_name=resource_group.name,
    private_zone_name=private_dns_zone.name,
    virtual_network_link_name="traininglink",
    virtual_network=azure_native.network.SubResourceArgs(id="<<ExistingVirtualNetworkId>>"),
    registration_enabled=False # Set this to True if the virtual network should auto-register DNS records
)

# Setting `registration_enabled` to True is useful if the VMs in your network should automatically
# register their hostnames with this DNS zone. If you prefer to manually manage the DNS records,
# set it to False.

Lastly, to easily get information from these resources after deployment, or to use them in subsequent Pulumi stacks, you can export some of their attributes:

# Export the DNS zone name and the resource group name for future reference
pulumi.export("dns_zone_name", private_dns_zone.name)
pulumi.export("resource_group_name", resource_group.name)

Here's the full Pulumi program that combines all the pieces:

import pulumi
import pulumi_azure_native as azure_native

# Create a new resource group
resource_group = azure_native.resources.ResourceGroup('model-training-rg')

# Create a Private DNS Zone
private_dns_zone = azure_native.network.PrivateZone(
    "training-dns-zone",
    resource_group_name=resource_group.name,
    location="Global",  # Private DNS zones are global resources
    private_zone_name="training.example.com"  # Replace with your desired DNS zone name
)

# Link the DNS zone to a virtual network
vnet_link = azure_native.network.VirtualNetworkLink(
    "training-vnet-link",
    resource_group_name=resource_group.name,
    private_zone_name=private_dns_zone.name,
    virtual_network_link_name="traininglink",
    virtual_network=azure_native.network.SubResourceArgs(
        id="<<ExistingVirtualNetworkId>>"  # Your virtual network ID here
    ),
    registration_enabled=False  # Set to True to auto-register DNS records
)

# Export the output for easy access
pulumi.export("dns_zone_name", private_dns_zone.name)
pulumi.export("resource_group_name", resource_group.name)

Use this program to deploy a Private DNS Zone in Azure for your decentralized AI model training setup. Replace placeholders like <<ExistingVirtualNetworkId>> and "training.example.com" with your actual Virtual Network ID and desired domain respectively.

Make sure you have set up the Pulumi Azure provider and configured your environment for authentication to your Azure account. After running pulumi up, this program will create a resource group, a Private DNS zone, and link this DNS zone to your virtual network.