This lesson examines Monitoring, events, alarms, automation, performance diagnostics, and service integrations within Oracle AI Cloud Database Service Professional Workshop (2025). The work is framed around the practical objective of a production-ready Oracle AI Cloud Database service configured, protected, monitored, and operated through repeatable cloud workflows and uses evidence rather than assumption to judge readiness.
The demonstration traces Monitoring, events, alarms, automation, performance diagnostics, and service integrations from requirement through execution and review. Learners see where evidence should be collected, how monitoring dashboard and automated response test supports verification, and which warning signs demand investigation.
Build or execute Monitoring, events, alarms, automation, performance diagnostics, and service integrations for a defined business case. Introduce the condition “an alarm generating noise because the threshold ignores workload cycles,” inspect the resulting evidence, correct the cause without discarding the audit trail, and document the final state in monitoring dashboard and automated response test.
Diagnose Monitoring, events, alarms, automation, performance diagnostics, and service integrations by checking effective settings, ownership, source records, dependencies, and recent releases. Use monitoring dashboard and automated response test to locate the earliest divergence. Treat “an alarm generating noise because the threshold ignores workload cycles” as a hypothesis until the same test passes after correction and still passes for a boundary case.
Learners can apply Monitoring, events, alarms, automation, performance diagnostics, and service integrations, explain the decisions made, and defend the result with monitoring dashboard and automated response test.