Note
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Access to this page requires authorization. You can try changing directories.
Important
This feature is in Beta. Workspace admins can control access to this feature from the Previews page. See Manage Azure Databricks previews.
The managed PagerDuty connector in Lakeflow Connect ingests incident, on-call, service, and audit data from PagerDuty into Azure Databricks.
Feature availability
| Feature | Availability |
|---|---|
| UI-based pipeline authoring |  Supported |
| API-based pipeline authoring | Supported |
| Declarative Automation Bundles | Supported |
| Incremental ingestion | Supported |
| Unity Catalog governance | Supported |
| Orchestration using Databricks Workflows | Supported |
| API-based column selection and deselection | Supported |
| API-based row filtering |  Not supported |
| SCD Type 2 | Supported |
| Automated schema evolution: New and deleted columns | Supported |
| Automated schema evolution: Data type changes | Not supported |
| Automated schema evolution: Column renames | Not supported Requires a full refresh. |
Authentication methods
| Authentication method | Availability |
|---|---|
| OAuth U2M | Not supported |
| OAuth M2M | Supported |
| Basic authentication (username/password) | Not supported |
Ingest from PagerDuty in 3 steps
Note
Before starting, review the Azure Databricks user persona, supported interfaces, ingestion frequency, and common patterns.
- Configure PagerDuty for ingestion (Admins) — Set up PagerDuty to authenticate with Azure Databricks.
- Create a Unity Catalog connection (Admins) — Create a connection in Catalog Explorer to store credentials for Azure Databricks to authenticate with PagerDuty.
- Create an ingestion pipeline (Admins or non-admins) — Select any supported interface and create a pipeline from an existing connection.