Performance Engineering & Optimization Topics
Backend system optimization, performance tuning, memory management, and engineering proficiency. Covers system-level performance, remote support tools, and infrastructure optimization.
Performance Profiling & Bottleneck Analysis
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.
Performance Troubleshooting & Incident Response
Diagnosing and resolving performance problems in production, often under time pressure. Covers latency and slowdown investigation, reproducing and narrowing performance regressions, reading live diagnostic evidence (logs, thread dumps, resource and network captures), runbooks and automated remediation for recurring incidents, restoring healthy behavior while preserving reliability, and communicating status and escalation decisions mid-incident. Emphasizes systematic debugging of live systems over offline experimentation.