How to configure a private link for Azure AI hub

Article
04/10/2024

Note

Azure AI Studio is currently in public preview. This preview is provided without a service-level agreement, and we don't recommend it for production workloads. Certain features might not be supported or might have constrained capabilities. For more information, see Supplemental Terms of Use for Microsoft Azure Previews.

We have two network isolation aspects. One is the network isolation to access an Azure AI hub. Another is the network isolation of computing resources in your Azure AI hub and Azure AI projects such as compute instances, serverless, and managed online endpoints. This article explains the former highlighted in the diagram. You can use private link to establish the private connection to your Azure AI hub and its default resources. This article is for Azure AI Studio (AI hub and AI projects). For information on Azure AI Services, see the Azure AI Services documentation.

You get several Azure AI hub default resources in your resource group. You need to configure following network isolation configurations.

Disable public network access of Azure AI hub default resources such as Azure Storage, Azure Key Vault, and Azure Container Registry.
Establish private endpoint connection to Azure AI hub default resources. You need to have both a blob and file private endpoint for the default storage account.
Managed identity configurations to allow Azure AI hub resources access your storage account if it's private.
Azure AI Services and Azure AI Search should be public.

Prerequisites

You must have an existing Azure Virtual Network to create the private endpoint in.

Important

We do not recommend using the 172.17.0.0/16 IP address range for your VNet. This is the default subnet range used by the Docker bridge network or on-premises.
Disable network policies for private endpoints before adding the private endpoint.

Create an Azure AI that uses a private endpoint

Use one of the following methods to create an Azure AI hub resource with a private endpoint. Each of these methods requires an existing virtual network:

Azure portal
Azure CLI

From the Azure portal, go to Azure AI Studio and choose + New Azure AI.
Choose network isolation mode in Networking tab.
Scroll down to Workspace Inbound access and choose + Add.
Input required fields. When selecting the Region, select the same region as your virtual network.

Create your Azure AI hub resource with the Azure AI CLI. Run the following command and follow the prompts. For more information, see Get started with Azure AI CLI.

ai init

After creating the Azure AI hub, use the Azure networking CLI commands to create a private link endpoint for the Azure AI.

az network private-endpoint create \
    --name <private-endpoint-name> \
    --vnet-name <vnet-name> \
    --subnet <subnet-name> \
    --private-connection-resource-id "/subscriptions/<subscription>/resourceGroups/<resource-group-name>/providers/Microsoft.MachineLearningServices/workspaces/<workspace-name>" \
    --group-id amlworkspace \
    --connection-name workspace -l <location>

To create the private DNS zone entries for the workspace, use the following commands:

# Add privatelink.api.azureml.ms
az network private-dns zone create \
    -g <resource-group-name> \
    --name privatelink.api.azureml.ms

az network private-dns link vnet create \
    -g <resource-group-name> \
    --zone-name privatelink.api.azureml.ms \
    --name <link-name> \
    --virtual-network <vnet-name> \
    --registration-enabled false

az network private-endpoint dns-zone-group create \
    -g <resource-group-name> \
    --endpoint-name <private-endpoint-name> \
    --name myzonegroup \
    --private-dns-zone privatelink.api.azureml.ms \
    --zone-name privatelink.api.azureml.ms

# Add privatelink.notebooks.azure.net
az network private-dns zone create \
    -g <resource-group-name> \
    --name privatelink.notebooks.azure.net

az network private-dns link vnet create \
    -g <resource-group-name> \
    --zone-name privatelink.notebooks.azure.net \
    --name <link-name> \
    --virtual-network <vnet-name> \
    --registration-enabled false

az network private-endpoint dns-zone-group add \
    -g <resource-group-name> \
    --endpoint-name <private-endpoint-name> \
    --name myzonegroup \
    --private-dns-zone privatelink.notebooks.azure.net \
    --zone-name privatelink.notebooks.azure.net

Add a private endpoint to an Azure AI hub

Use one of the following methods to add a private endpoint to an existing Azure AI hub:

Azure portal
Azure CLI

From the Azure portal, select your Azure AI hub.
From the left side of the page, select Networking and then select the Private endpoint connections tab.
When selecting the Region, select the same region as your virtual network.
When selecting Resource type, use azuremlworkspace.
Set the Resource to your workspace name.

Finally, select Create to create the private endpoint.

Use the Azure networking CLI commands to create a private link endpoint for the Azure AI hub.

az network private-endpoint create \
    --name <private-endpoint-name> \
    --vnet-name <vnet-name> \
    --subnet <subnet-name> \
    --private-connection-resource-id "/subscriptions/<subscription>/resourceGroups/<resource-group-name>/providers/Microsoft.MachineLearningServices/workspaces/<workspace-name>" \
    --group-id amlworkspace \
    --connection-name workspace -l <location>

To create the private DNS zone entries for the workspace, use the following commands:

# Add privatelink.api.azureml.ms
az network private-dns zone create \
    -g <resource-group-name> \
    --name 'privatelink.api.azureml.ms'

az network private-dns link vnet create \
    -g <resource-group-name> \
    --zone-name 'privatelink.api.azureml.ms' \
    --name <link-name> \
    --virtual-network <vnet-name> \
    --registration-enabled false

az network private-endpoint dns-zone-group create \
    -g <resource-group-name> \
    --endpoint-name <private-endpoint-name> \
    --name myzonegroup \
    --private-dns-zone 'privatelink.api.azureml.ms' \
    --zone-name 'privatelink.api.azureml.ms'

# Add privatelink.notebooks.azure.net
az network private-dns zone create \
    -g <resource-group-name> \
    --name 'privatelink.notebooks.azure.net'

az network private-dns link vnet create \
    -g <resource-group-name> \
    --zone-name 'privatelink.notebooks.azure.net' \
    --name <link-name> \
    --virtual-network <vnet-name> \
    --registration-enabled false

az network private-endpoint dns-zone-group add \
    -g <resource-group-name> \
    --endpoint-name <private-endpoint-name> \
    --name myzonegroup \
    --private-dns-zone 'privatelink.notebooks.azure.net' \
    --zone-name 'privatelink.notebooks.azure.net'

Remove a private endpoint

You can remove one or all private endpoints for an Azure AI hub. Removing a private endpoint removes the Azure AI hub from the Azure Virtual Network that the endpoint was associated with. Removing the private endpoint might prevent the Azure AI hub from accessing resources in that virtual network, or resources in the virtual network from accessing the workspace. For example, if the virtual network doesn't allow access to or from the public internet.

Warning

Removing the private endpoints for an AI hub doesn't make it publicly accessible. To make the AI hub publicly accessible, use the steps in the Enable public access section.

To remove a private endpoint, use the following information:

Azure portal
Azure CLI

From the Azure portal, select your Azure AI hub.
From the left side of the page, select Networking and then select the Private endpoint connections tab.
Select the endpoint to remove and then select Remove.

When using the Azure CLI, use the following command to remove the private endpoint:

az network private-endpoint delete \
    --name <private-endpoint-name> \
    --resource-group <resource-group-name> \

Enable public access

In some situations, you might want to allow someone to connect to your secured Azure AI hub over a public endpoint, instead of through the virtual network. Or you might want to remove the workspace from the virtual network and re-enable public access.

Important

Enabling public access doesn't remove any private endpoints that exist. All communications between components behind the virtual network that the private endpoint(s) connect to are still secured. It enables public access only to the Azure AI hub, in addition to the private access through any private endpoints.

To enable public access, use the following steps:

Azure portal
Azure CLI

From the Azure portal, select your Azure AI hub.
From the left side of the page, select Networking and then select the Public access tab.
Select Enabled from all networks, and then select Save.

Managed identity configuration

A manged identity configuration is required if you make your storage account private. Our services need to read/write data in your private storage account using Allow Azure services on the trusted services list to access this storage account with following managed identity configurations. Enable the system assigned managed identity of Azure AI Service and Azure AI Search, then configure role-based access control for each managed identity.

Role	Managed Identity	Resource	Purpose	Reference
`Storage File Data Privileged Contributor`	Azure AI project	Storage Account	Read/Write prompt flow data.	Prompt flow doc
`Storage Blob Data Contributor`	Azure AI Service	Storage Account	Read from input container, write to preprocess result to output container.	Azure OpenAI Doc
`Storage Blob Data Contributor`	Azure AI Search	Storage Account	Read blob and write knowledge store	Search doc.

Custom DNS configuration

See Azure Machine Learning custom DNS article for the DNS forwarding configurations.

If you need to configure custom DNS server without DNS forwarding, use the following patterns for the required A records.

<AI-STUDIO-GUID>.workspace.<region>.cert.api.azureml.ms
<AI-PROJECT-GUID>.workspace.<region>.cert.api.azureml.ms
<AI-STUDIO-GUID>.workspace.<region>.api.azureml.ms
<AI-PROJECT-GUID>.workspace.<region>.api.azureml.ms
ml-<workspace-name, truncated>-<region>-<AI-STUDIO-GUID>.<region>.notebooks.azure.net
ml-<workspace-name, truncated>-<region>-<AI-PROJECT-GUID>.<region>.notebooks.azure.net

Note

The workspace name for this FQDN might be truncated. Truncation is done to keep ml-<workspace-name, truncated>-<region>-<workspace-guid> at 63 characters or less.
<instance-name>.<region>.instances.azureml.ms
Note
- Compute instances can be accessed only from within the virtual network.
- The IP address for this FQDN is not the IP of the compute instance. Instead, use the private IP address of the workspace private endpoint (the IP of the *.api.azureml.ms entries.)
<managed online endpoint name>.<region>.inference.ml.azure.com - Used by managed online endpoints

To find the private IP addresses for your A records, see the Azure Machine Learning custom DNS article. To check AI-PROJECT-GUID, go to the Azure portal, select your Azure AI project, settings, properties, and the workspace ID is displayed.

Limitations

Private Azure AI Services and Azure AI Search aren't supported.
The "Add your data" feature in the Azure AI Studio playground doesn't support private storage account.
You might encounter problems trying to access the private endpoint for your Azure AI hub if you're using Mozilla Firefox. This problem might be related to DNS over HTTPS in Mozilla Firefox. We recommend using Microsoft Edge or Google Chrome.