Monitor user activity in Oracle AI Data Platform Workbench with audit logs for compliance, investigations, and change tracking.
See training and documentation for audit logging and Workbench governance at the resources linked below.
In this demo, you learn how to use audit logs in Oracle AI Data Platform Workbench to monitor usage, support compliance, and investigate issues such as unauthorized access or configuration changes. The walkthrough starts on the home page, where you open Audit Logs and review how audit records track operations on key Workbench objects, including workspaces, compute clusters, catalogs, schemas, and roles.
You then review what each audit record captures, including the object, operation, timestamp, initiator, source, and status so you can confirm what changed, who initiated the action, and whether it succeeded or failed. Next, you learn how to search and filter audit logs by object, name, or payload. The demo includes an example of isolating role updates by filtering on Object Type and selecting role, which helps you focus on specific change types.
Finally, you review best practices for using audit logs effectively, including routine log reviews, watching for unusual activity patterns, and troubleshooting unexpected changes by tracing the source of actions and failures. Audit logs are especially valuable for incident response and for demonstrating governance through a clear record of who changed what and when.
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