Perf Lab

Optimize only after creating a measurement loop.

Workflow

1. Define the target metric: latency, throughput, memory, CPU, query count, bundle size, render frames, or startup time.
2. Build a baseline using the repo's tools first: benchmark, profiler, logs, trace, query plan, browser performance panel, or a focused script.
3. Reproduce the slow path with representative data.
4. Rank hypotheses by likely impact and cost.
5. Change one variable at a time.
6. Compare before/after numbers and preserve behavior with tests where possible.

Common Checks

• Accidental N+1 queries or missing indexes.
• Repeated parsing, serialization, regex, or filesystem work.
• Unbounded loops, deep copies, or needless allocations.
• Chatty network calls or waterfall loading.
• Large client bundles, hydration cost, and expensive renders.
• Cache invalidation that is too broad or too sticky.

Output

Include:

• Baseline command and result.
• Hypotheses considered.
• Changes made or recommended.
• After result.
• Tradeoffs and remaining bottlenecks.

If measurement is blocked, state the missing fixture, traffic shape, or profiler access instead of guessing.