Delta Lake Table Updates

Delta Lake tables in Databricks hold the versioned data a team's pipelines read from and write to. A Beam agent reads table metadata, such as last update time and row count, and applies the team's approved freshness rule to flag a table that hasn't refreshed on schedule. Where the rule allows it, the agent notifies the table owner directly rather than waiting for someone to notice downstream. Tables feeding a production dashboard or model, or ones missing an owner, are routed to a person to look into further.

Databricks Job Run Status

Scheduled jobs in Databricks run notebooks and pipelines on a defined cadence, each producing a run outcome. A Beam agent reads the outcome of each run and, following the team's approved rule, such as escalating after two consecutive failures on the same job, opens or updates a ticket in the team's tracking tool. It notifies the job owner with the failure details already attached. Jobs tied to a production workflow, or a failure pattern the rule doesn't clearly cover, are routed to a person before further action is taken.

Unity Catalog Access Records

Unity Catalog holds the permission records for who can read or write which tables and files across a Databricks workspace. A Beam agent reads new access requests and checks each one against the team's approved access policy, such as a standard read-only grant for a named role. Where a request matches the policy exactly, the agent updates the access record and notifies the requester that access is in place. Requests for write access, access to a sensitive table, or anything outside the standard policy are routed to a person to approve directly.