Create an Azure connection to an Edge or Collibra Cloud site

Prerequisites

In your Collibra environment

• You either created and installed an Edge site or were granted a Collibra Cloud site.
  Note 

  If you have defined an outbound (forward) proxy on your Edge site, the integration will take that configuration into account when connecting to the AI platform. The following proxies are supported, using either a HTTP or HTTPS proxy URL:

  • Pass through (No authentication)
  • Pass through (Basic authentication)
  • No proxy for noProxy hosts defined by Edge

  This integration is not supported on Edge sites installed using a Man-in-the-middle (MITM) proxy.

• You have created and installed an Edge site.
If you want to add connection values from a vault, you have added the vault to your Edge site. If your data source connection requires a file from your vault, the file must be encoded into Base64 and stored as a regular secret in your vault. For more information, go to the Vault documentation.
Note  Vaults are not supported on Collibra Cloud sites.
• You have a global role that has the Manage connections and capabilities global permission, for example, Edge integration engineer.

In your Azure ML environment

To integrate Azure ML assets, the service principal must have the following permissions on the Azure ML workspace:

• Microsoft.MachineLearningServices/workspaces/models/versions/read, used to list model containers and read model versions.
• Microsoft.MachineLearningServices/workspaces/jobs/read, used to resolve job run IDs and call the MLflow tracking server endpoint.

These permissions are included in the built-in AzureML Data Scientist role. The Reader role covers model listing only, without MLflow metrics. For more information on role assignments, go to the Azure ML access control documentation.