Databricks
Discover registered models and serving endpoints in a Databricks workspace.
Airia discovers the AI assets in a Databricks workspace: registered models (Unity Catalog) and model serving endpoints.
Authentication model
A Databricks personal access token (PAT) plus the workspace URL.
Required permissions
The PAT inherits the permissions of the principal that created it. For full results the principal needs:
| Capability | Permission on the Databricks side |
|---|---|
| Enumerate registered models and serving endpoints (core discovery) | Read access to the workspace's models and serving endpoints |
| Permission checks on model grants | Read on Unity Catalog grants |
| Permission checks on serving ACLs | Read on serving endpoint ACLs |
If the principal lacks the Unity Catalog grant-read or serving-ACL-read permissions, the two permission checks on the connection test report a warning, but authentication and discovery itself still succeed. Grant the extra read access if you want a clean bill of health on the connection test.
Customer-side setup steps
- In Databricks, create a service principal (recommended) or choose an integration user with read access to the models and serving endpoints in scope.
- Generate a personal access token for that principal (User Settings → Developer → Access tokens, or the service-principal token API).
- Copy the workspace URL (for example
https://yourworkspace.cloud.databricks.com). - In Airia, go to Discover → Connections → Databricks and create a new connection with the workspace URL and token.
Form fields the Airia UI asks for
| Field | Required | Notes |
|---|---|---|
| Workspace URL | Yes | https://<workspace>.cloud.databricks.com |
| Access token | Yes | Stored encrypted, masked on edit |
Multiple environments
Multiple Databricks connections per tenant are supported: one per workspace.
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