Slack Access and Integration Logs connector

Beta

This feature is in Beta. Workspace admins can control access to this feature from the Previews page. See Manage 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 Databricks.

Feature availability

Feature	Availability
UI-based pipeline authoring	Not supported
API-based pipeline authoring	Supported
Declarative Automation Bundles	Supported
Incremental ingestion	Supported
Unity Catalog governance	Supported
Orchestration using Databricks Workflows	Supported
SCD type 2	Not supported Slack access and integration logs are append-only.
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	Supported
OAuth M2M	Not supported
Basic authentication (username/password)	Not supported

Ingest from Slack Access and Integration Logs in 3 steps

note

Before starting, review the 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 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.