PagerDuty connector
This feature is in Beta. Workspace admins can control access to this feature from the Previews page. See Manage Databricks previews.
The managed PagerDuty connector in Lakeflow Connect ingests incident, on-call, service, and audit data from PagerDuty into Databricks.
Feature availability
Feature | Availability |
|---|---|
UI-based pipeline authoring |
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API-based pipeline authoring |
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Declarative Automation Bundles |
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Incremental ingestion |
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Unity Catalog governance |
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Orchestration using Databricks Workflows |
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API-based column selection and deselection |
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API-based row filtering |
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SCD Type 2 |
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Automated schema evolution: New and deleted columns |
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Automated schema evolution: Data type changes |
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Automated schema evolution: Column renames |
Requires a full refresh. |
Authentication methods
Authentication method | Availability |
|---|---|
OAuth U2M |
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OAuth M2M |
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Basic authentication (username/password) |
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Ingest from PagerDuty in 3 steps
Before starting, review the Databricks user persona, supported interfaces, ingestion frequency, and common patterns.
- Configure PagerDuty for ingestion (Admins) — Set up PagerDuty to authenticate with Databricks.
- Create a Unity Catalog connection (Admins) — Create a connection in Catalog Explorer to store credentials for 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.