Slack Access and Integration Logs connector

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 Slack Access and Integration Logs connector in Lakeflow Connect allows you to ingest workspace access logs and app integration change logs from Slack into Azure Databricks.

Feature availability

Feature Availability
UI-based pipeline authoring Red X icon Not supported
API-based pipeline authoring Green check icon Supported
Declarative Automation Bundles Green check icon Supported
Incremental ingestion Green check icon Supported
Unity Catalog governance Green check icon Supported
Orchestration using Databricks Workflows Green check icon Supported
SCD type 2 Red X icon Not supported
Slack access and integration logs are append-only.
Automated schema evolution: New and deleted columns Green check icon Supported
Automated schema evolution: Data type changes Red X icon Not supported
Automated schema evolution: Column renames Red X icon Not supported
Requires a full refresh.

Authentication methods

Authentication method Availability
OAuth U2M Green check icon Supported
OAuth M2M Red X icon Not supported
Basic authentication (username/password) Red X icon Not supported

Ingest from Slack Access and Integration Logs in 3 steps

Note

Before starting, review the Azure Databricks user persona, supported interfaces, ingestion frequency, and common patterns.

Start ingesting from Slack Access and Integration Logs

  1. Configure Slack for ingestion (Admins) — Set up Slack to authenticate with Azure Databricks.
  2. Create a Unity Catalog connection (Admins) — Create a connection in Catalog Explorer so non-admins can create pipelines.
  3. Create an ingestion pipeline (Admins or non-admins) — Select any supported interface and create a pipeline from an existing connection.
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