Verkada connector FAQ
This feature is in Beta. Workspace admins can control access to this feature from the Previews page. See Manage Databricks previews.
This page answers frequently asked questions about the managed Verkada ingestion connector in Lakeflow Connect. For FAQs that apply to all managed connectors, see Managed connector FAQs.
Which tables does the connector support?
The connector supports the audit_log and users tables. For the schema of each table, see Supported source tables.
Does the connector support incremental ingestion?
Yes, for the audit_log table, using the processed_timestamp cursor field. The connector refreshes the users table with a full snapshot on each pipeline update.
How far back can the connector ingest data?
For the incremental audit_log table, the first sync ingests events from the previous 365 days, and no earlier than August 12, 2025. Each later sync ingests events recorded after the last run. The users table reingests all records on every run.
Which authentication methods does the connector support?
The connector authenticates with a Verkada organization API key and exchanges it for a short-lived API token automatically. OAuth U2M, OAuth M2M, and basic username/password authentication are not supported.
Which Verkada permissions does the connector require?
A Verkada organization admin must create an API key with Read-only access to Core for the audit_log table and Access Control for the users table. See Configure Verkada.