optimizing-performancelisted

# Optimizing Performance ### When to Load - **Trigger**: Diagnosing slowness, profiling, caching strategies, reducing load times, bundle size optimization - **Skip**: Correctness-focused work where performance is not a concern ## Performance Optimization Workflow Copy this checklist and track progress: ``` Performance Optimization Progress: - [ ] Step 1: Measure baseline performance - [ ] Step 2: Identify bottlenecks - [ ] Step 3: Apply targeted optimizations - [ ] Step 4: Measure again and compare - [ ] Step 5: Repeat if targets not met ``` **Critical Rule**: Never optimize without data. Always profile before and after changes. ## Step 1: Measure Baseline ### Profiling Commands ```bash # Node.js profiling node --prof app.js node --prof-process isolate*.log > profile.txt # Python profiling python -m cProfile -o profile.stats app.py python -m pstats profile.stats # Web performance lighthouse https://example.com --output=json ``` ## Step 2: Identify Bottlenecks ### Common Bottleneck Categories | Category | Symptoms | Tools | | -------- | -------------------------------- | ------------------------------- | | CPU | High CPU usage, slow computation | Profiler, flame graphs | | Memory | High RAM, GC pauses, OOM | Heap snapshots, memory profiler | | I/O | Slow disk/network, waiting | strace, network inspector | | Database | Slow queries, lock contention | Query analyzer, EXPLA