performance-profiler

原文涵盖的主题

• Performance Profiler
• Overview
• Core Capabilities
• When to Use
• Quick Start
• Golden Rule: Measure First
• Node.js Profiling
• References

Tier: POWERFUL Category: Engineering Domain: Performance Engineering -- Systematic performance profiling for Node.js, Python, and Go applications. Identifies CPU, memory, and I/O bottlenecks; generates flamegraphs; analyzes bundle sizes; optimizes database queries; detects memory leaks; and runs load tests with k6 and Artillery. Always measures before and after. CPU profiling — flamegraphs for Node.js, py-spy for Python, pprof for Go Memory profiling — heap snapshots, leak detection, GC pressure Bundle analysis — webpack-bundle-analyzer, Next.js bundle analyzer Database optimization — EXPLAIN ANALYZE, slow query log, N+1 detection Load testing — k6 scripts, Artillery scenarios, ramp-up patterns Before/after measurement — establish baseline, profile, optimize, verify -- App is slow and you don't know where the bottleneck is P99 latency exceeds SLA before a release Memory usage grows over time (suspected leak) Bundle size increased after adding dependencies Preparing for a traffic spike (load test before launch) Database queries taking >100ms -- -- -- → See references/profiling-recipes.md for details references/profiling-recipes.md — Node.js/Python/Go profiling commands, flamegraph g

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