Performance Profiler
Tier: POWERFUL
Category: Engineering
Domain: Performance Engineering
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
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
Quick Start
# Analyze a project for performance risk indicators
python3 scripts/performance_profiler.py /path/to/project
# JSON output for CI integration
python3 scripts/performance_profiler.py /path/to/project --json
# Custom large-file threshold
python3 scripts/performance_profiler.py /path/to/project --large-file-threshold-kb 256
Golden Rule: Measure First
# 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
Node.js Profiling
→ See references/profiling-recipes.md for details
References
- references/profiling-recipes.md — Node.js/Python/Go profiling commands, flamegraph generation, heap snapshots
- references/optimization-playbook.md — before/after measurement template, quick-win optimization checklist (DB/Node/bundle/API), common pitfalls, best practices
1---2name: performance-profiler3description: 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, runs load tests with k6 and Artillery. Always measure...4license: MIT5---6
7# Performance Profiler
8
9**Tier:** POWERFUL
10**Category:** Engineering
11**Domain:** Performance Engineering
12
13---
14
15## Overview
16
17Systematic 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.
18
19## Core Capabilities
20
21- **CPU profiling** — flamegraphs for Node.js, py-spy for Python, pprof for Go
22- **Memory profiling** — heap snapshots, leak detection, GC pressure
23- **Bundle analysis** — webpack-bundle-analyzer, Next.js bundle analyzer
24- **Database optimization** — EXPLAIN ANALYZE, slow query log, N+1 detection
25- **Load testing** — k6 scripts, Artillery scenarios, ramp-up patterns
26- **Before/after measurement** — establish baseline, profile, optimize, verify
27
28---
29
30## When to Use
31
32- App is slow and you don't know where the bottleneck is
33- P99 latency exceeds SLA before a release
34- Memory usage grows over time (suspected leak)
35- Bundle size increased after adding dependencies
36- Preparing for a traffic spike (load test before launch)
37- Database queries taking >100ms
38
39---
40
41## Quick Start
42
43```bash
44# Analyze a project for performance risk indicators
45python3 scripts/performance_profiler.py /path/to/project
46
47# JSON output for CI integration
48python3 scripts/performance_profiler.py /path/to/project --json
49
50# Custom large-file threshold
51python3 scripts/performance_profiler.py /path/to/project --large-file-threshold-kb 256
52```
53
54---
55
56## Golden Rule: Measure First
57
58```bash
59# Establish baseline BEFORE any optimization
60# Record: P50, P95, P99 latency | RPS | error rate | memory usage
61
62# Wrong: "I think the N+1 query is slow, let me fix it"
63# Right: Profile → confirm bottleneck → fix → measure again → verify improvement
64```
65
66---
67
68## Node.js Profiling
69→ See references/profiling-recipes.md for details
70
71## References
72
73- [references/profiling-recipes.md](references/profiling-recipes.md) — Node.js/Python/Go profiling commands, flamegraph generation, heap snapshots
74- [references/optimization-playbook.md](references/optimization-playbook.md) — before/after measurement template, quick-win optimization checklist (DB/Node/bundle/API), common pitfalls, best practices
nous-hermeshub