Dynamic CPU profiling enables targeted performance diagnostics for MongoDB during periods of high resource utilization. By triggering profiling when CPU usage crosses 80%-90%, MongoDB can log valuable diagnostic data in mongod.log or mongos.log. This helps identify bottlenecks such as slow queries or inefficiencies in resource usage, providing actionable insights during critical moments. This could be a simple script that is packaged with mongo packages.

To prevent log flooding, CPU profiling should be limited to logging once during a set interval, such as every X minutes. This ensures that logs remain manageable while still capturing meaningful data to support troubleshooting efforts. This approach immediately reveals the root cause of CPU spikes, avoiding guesswork or reliance on post-event FTDC data analysis, saving valuable time in resolving issues and eliminating the need to wait for another spike.

Additionally, CPU profiling may prove useful when memory usage approaches 90%. While it may not directly pinpoint the root cause of memory growth, it could help identify who is performing operations such as new and delete, as the profiling data shows callers of these function calls. This could provide valuable hints about memory allocation patterns contributing to high memory usage. Though not as precise as a dedicated memory profiler (which requires a restart and is not easily enabled dynamically), leveraging CPU profiling during such scenarios could still be a helpful way to uncover potential contributors to memory-related issues.