Performance Profiling & Bottleneck Analysis Questions

Techniques for measuring where time and resources go in a running system and isolating the dominant bottleneck, independent of platform, language, or role. Covers CPU, memory, and allocation profiling, including GPU utilization profiling on ML-inference services; generating and reading flame graphs; choosing sampling vs instrumentation profiling; heap dumps and GC diagnostics; and using profiler, trace, and metric output to distinguish symptom from root cause. Emphasizes the measurement methodology itself: forming a measurement-first hypothesis before optimizing and validating that a fix actually worked, rather than the optimization technique applied afterward, the platform's resource limits, or production incident triage under time pressure.