Idea Description
OOTB loads (snapshot to target DB switch) are inherently reactive operations. However, current monitoring provides only high-level process status and lacks visibility into object-level execution.
Proposed enhancement: introduce object-level tracking (execution time, status, and DML metrics such as inserts/updates/deletes) to enable deeper insights into load behavior.
Business Justification / Value
- Enables data-driven performance optimization of inherently reactive load processes
- Helps identify high-impact objects contributing to load duration
- Supports continuous improvement across load cycles
Reduces repeated performance issues in recurring loads
Use Case
During recurring OOTB loads, some tables consistently take longer due to data volume or design constraints. Object-level metrics allow teams to identify these patterns and optimize (indexing, partitioning, data pruning), improving performance in subsequent runs.
Current Limitation
Monitoring is limited to process-level visibility, making it difficult to understand which objects drive performance overhead during load execution.
Proposed Solution
Enhance OOTB monitoring to capture:
- Object-level execution duration and status
- Record-level metrics (insert/update/delete counts)
- Historical tracking to support trend-based optimization
