Profile before optimizing (Go)

Steps

1. 1Define target metric: p95 latency? memory ceiling? throughput?
2. 2Build benchmark using PRODUCTION-shaped data volumes
3. 3Profile CPU + memory + allocations; identify top three offenders
4. 4Optimize one offender at a time; re-measure after each change
5. 5Check second-order effects: cache misses, GC pressure, lock contention
6. 6Record before/after numbers in the PR for future archaeologists
7. 7Run pprof profiles; check goroutine leaks with goleak
8. 8Enforce vet/lint gates; keep error wrapping with %w intact

Common Pitfalls

• ▲Optimizing intuition while profile shows I/O waits
• ▲Micro-benchmarks on toy data lying about production

Commands

$ npx skills add aniruddhaadak80/skills --skill code-quality-performance-profiling-go

$ npx skills add aniruddhaadak80/skills --skill code-quality-performance-profiling-go -g

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