Performance Profiler

Systematic performance profiling for Node.js, Python, and Go applications. Identifies CPU bottlenecks with flamegraphs, detects memory leaks with heap snapshots, analyzes bundle sizes, optimizes database queries, detects N+1 patterns, and runs load tests with k6 and Artillery. Enforces a measure-first methodology: establish baseline, identify bottleneck, fix, and verify improvement.

Golden Rule — Measure First: Profile → Confirm bottleneck → Fix → Measure again → Verify improvement. Every optimization needs baseline metrics, profiler evidence, the fix, post-fix metrics, and a delta. Full rule in references/cpu-and-memory-profiling.md.

Core Capabilities

• CPU profiling — Clinic.js/V8 flamegraphs (Node), py-spy/cProfile/scalene (Python), pprof (Go), Chrome DevTools (browser).
• Memory profiling — heap snapshots and before/after comparison, GC pressure analysis, leak detection, retained object graphs.
• Database optimization — EXPLAIN ANALYZE plan reading, N+1 detection and batching, slow query logs, missing-index identification, connection pool sizing.
• Bundle analysis — webpack/Next.js analyzers, tree-shaking, dynamic imports, heavy dependency identification.
• Load testing — k6 ramp-up scripts, SLA threshold enforcement in CI, P50/P95/P99 latency tracking, concurrent user simulation.

When to Use