performance-profiler

# Performance Profiler

**Tier:** POWERFUL  
**Category:** Engineering  
**Domain:** Performance Engineering  

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## Overview

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.

## Core Capabilities

- **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

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## When to Use

- 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

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## Golden Rule: Measure First

```bash
# Establish baseline BEFORE any optimization
# Record: P50, P95, P99 latency | RPS | error rate | memory usage

# Wrong: "I think the N+1 query is slow, let me fix it"
# Right: Profile → confirm bottleneck → fix → measure again → verify improvement
```

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## Node.js Profiling
→ See references/profiling-recipes.md for details

## Before/After Measurement Template

```markdown
## Performance Optimization: [What You Fixed]

**Date:** 2026-03-01  
**Engineer:** @username  
**Ticket:** PROJ-123  

### Problem
[1-2 sentences: what was slow, how was it observed]

### Root Cause
[What the profiler revealed]

### Baseline (Before)
| Metric | Value |
|--------|-------|
| P50 latency | 480ms |
| P95 latency | 1,240ms |
| P99 latency | 3,100ms |
| R...