6.1 KiB
6.1 KiB
id, title, category, status, source_trust_level, verification_status, created_at, updated_at, tags, tech_stack, applied_in, aliases
| id | title | category | status | source_trust_level | verification_status | created_at | updated_at | tags | tech_stack | applied_in | aliases | |||||||||||||||
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| perf-node-profiling | Node Profiling — CPU / Memory / Async hooks | Coding | draft | B | conceptual | 2026-05-09 | 2026-05-09 |
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Node Profiling
"느림" 감으로 X — profile. CPU = clinic flame / 0x, Memory = heapdump, Event loop = clinic doctor. Production =
--inspect+ Chrome DevTools.
📖 핵심 개념
- CPU profile: 어느 함수가 시간 소모.
- Heap snapshot: 메모리 누가 보유.
- Event loop lag: 비동기 정체.
- Async hooks: async chain 추적.
💻 코드 패턴
Clinic.js (가장 단순)
yarn add -D clinic
clinic doctor -- node app.js
# 실행 → 부하 (autocannon) → Ctrl+C
# HTML report: doctor 가 진단 (CPU bound? I/O? memory?)
clinic flame -- node app.js
# Flame graph — 시간 hot spot
clinic bubbleprof -- node app.js
# Async operation 시각화
clinic heapprofiler -- node app.js
# Memory allocation
0x (flame graph)
npx 0x app.js
# 또는
0x -- node app.js
--inspect (Chrome DevTools)
node --inspect app.js
# 또는 prod (조심)
node --inspect=0.0.0.0:9229 app.js
# Chrome → chrome://inspect → DevTools
# CPU profile, heap snapshot, allocation timeline
→ Production attach 가능 (보안 주의).
CPU profile (programmatic)
import { Session } from 'node:inspector';
const session = new Session();
session.connect();
session.post('Profiler.enable', () => {
session.post('Profiler.start', () => {
setTimeout(() => {
session.post('Profiler.stop', (err, { profile }) => {
require('fs').writeFileSync('profile.cpuprofile', JSON.stringify(profile));
// Chrome DevTools → Performance → load profile
});
}, 30_000);
});
});
Heap snapshot
import { writeHeapSnapshot } from 'node:v8';
// Trigger: signal 또는 API
process.on('SIGUSR2', () => {
const path = `heap-${Date.now()}.heapsnapshot`;
writeHeapSnapshot(path);
console.log('snapshot:', path);
});
// 분석: Chrome DevTools → Memory → Load snapshot
kill -USR2 $PID
→ "Comparison" view 로 두 snapshot 비교 → leak.
Memory leak 패턴
// ❌ Global Map 만 쌓임
const cache = new Map();
app.get('/x', (req, res) => {
cache.set(req.id, req.data); // 영원 — leak
});
// ✅ TTL / LRU
import LRU from 'lru-cache';
const cache = new LRU({ max: 1000, ttl: 60_000 });
Event loop lag
import { monitorEventLoopDelay } from 'node:perf_hooks';
const h = monitorEventLoopDelay({ resolution: 20 });
h.enable();
setInterval(() => {
console.log('p99 lag:', h.percentile(99) / 1e6, 'ms');
h.reset();
}, 5000);
→ 50ms+ = problem. CPU bound 또는 sync I/O 의심.
Async hooks (실험적, 비싸)
import { createHook, executionAsyncId } from 'node:async_hooks';
const stack = new Map();
const hook = createHook({
init: (asyncId, type, triggerAsyncId) => {
stack.set(asyncId, { type, parent: triggerAsyncId });
},
destroy: (asyncId) => stack.delete(asyncId),
});
hook.enable();
→ AsyncLocalStorage 의 internal. Trace 추적.
AsyncLocalStorage (context)
import { AsyncLocalStorage } from 'node:async_hooks';
const als = new AsyncLocalStorage<{ requestId: string; userId?: string }>();
app.use((req, res, next) => {
als.run({ requestId: uuid() }, next);
});
// 어디서나
log.info({ ...als.getStore(), msg: 'event' });
Production tracing (low overhead)
// OpenTelemetry auto-instrumentation (위 OTel 문서 참조)
// Sentry profiling
import * as Sentry from '@sentry/node';
import { ProfilingIntegration } from '@sentry/profiling-node';
Sentry.init({ dsn, profilesSampleRate: 0.1, integrations: [new ProfilingIntegration()] });
→ Continuous profiling — 항상 켜져있음.
perf_hooks 측정
import { performance } from 'node:perf_hooks';
const t = performance.now();
await heavyWork();
console.log('took', performance.now() - t, 'ms');
// PerformanceObserver
import { PerformanceObserver, performance } from 'node:perf_hooks';
const obs = new PerformanceObserver((items) => {
for (const e of items.getEntries()) console.log(e.name, e.duration);
});
obs.observe({ type: 'measure' });
performance.mark('start');
await ...;
performance.mark('end');
performance.measure('myWork', 'start', 'end');
V8 flags (debugging)
node --max-old-space-size=4096 app.js # heap 4GB
node --trace-gc app.js # GC log
node --prof app.js # CPU profile (raw)
node --prof-process isolate-*.log # process
Memory limit
# Default V8 = ~1.5 GB on 64-bit
NODE_OPTIONS="--max-old-space-size=4096" node app.js
Hot path 측정 (JIT)
// 반복 측정 — JIT warmup
for (let i = 0; i < 10000; i++) myHotFn(); // warm
const t = performance.now();
for (let i = 0; i < 100000; i++) myHotFn();
console.log((performance.now() - t) / 100000, 'us per call');
🤔 의사결정 기준
| 증상 | 도구 |
|---|---|
| CPU 100% | Flame graph (0x / clinic) |
| Memory 자라남 | Heap snapshot diff |
| 응답 느려짐 점진 | Event loop lag |
| 가끔 spike | Continuous profile (Sentry) |
| Async tracing | OTel + auto-instrumentation |
| Production attach | --inspect=0.0.0.0:9229 (보안) |
❌ 안티패턴
console.time만 + 추측: 정확 X. profiler.- Production --inspect 공개: 누구나 attach. SSH tunnel.
- Async hook prod 항상: 큰 overhead. 디버깅 시만.
- Heap snapshot prod 큰 process: GC pause + freeze.
- JIT warmup 무시: 첫 call 측정.
- Memory limit 안 설정 prod: 무한 자라남.
- Sample rate 100% prod: 비용. 1-10%.
🤖 LLM 활용 힌트
- Clinic doctor 가 진단 시작.
- Heap snapshot diff 가 leak.
- Event loop lag 가 핵심 SLI.
- Production = Sentry / OTel sampled.