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	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

What to know before you start

Topic	Why it matters
Azure Databricks user persona	The workflow depends on your Azure Databricks user persona: Single-user: An admin user creates a Unity Catalog connection and an ingestion pipeline. Multi-user: An admin user creates a connection for non-admin users to create pipelines with.
Interface	The steps to create a pipeline depend on the interface.
Ingestion frequency	The pipeline schedule depends on your latency and cost requirements.
Common patterns	Depending on your ingestion needs, the pipeline might use configurations like history tracking, column selection, and row filtering. Supported configurations vary by connector. See Feature availability.

Start ingesting from Slack Access and Integration Logs

The following table provides an overview of the end-to-end Slack Access and Integration Logs ingestion flow, based on user type:

User	Steps
Admin	Configure Slack to enable authentication from Azure Databricks. See Configure authentication to Slack. Use Catalog Explorer to create a connection to Slack so that non-admins can create pipelines. See Create a Slack Access and Integration Logs connection.
Non-admin	Use any supported interface to create a pipeline from an existing connection. See Ingest data from Slack Access and Integration Logs.