docs(10_Wiki): Topic_Business/General/Graphic/Programming을 Topics/ 하위로 이동

최상위 10_Wiki/Topic_*였던 4개 카테고리 폴더를 10_Wiki/Topics/Topic_* 로 재배치. 콘텐츠 변경 없음(순수 폴더 이동) — Topics/ 하위 나머지 폴더는 이미 지난 커밋에서 전부 정리된 상태(잔존 항목은 에이전트 운영 상태 및 사용자가 보존을 요청한 업데이트0615/무제 3.canvas 뿐).
2026-07-05 00:44:01 +09:00
parent e9cbf23ab5
commit 9a135bd19d
6127 changed files with 0 additions and 0 deletions
@@ -0,0 +1,225 @@
+---
+id: wiki-2026-0508-텔레메트리-telemetry
+title: 텔레메트리 (Telemetry)
+category: 10_Wiki/Topics
+status: verified
+canonical_id: self
+aliases: [Telemetry, Observability data, Metrics + Traces + Logs]
+duplicate_of: none
+source_trust_level: A
+confidence_score: 0.9
+verification_status: applied
+tags: [observability, otel, metrics, traces, logs, architecture]
+raw_sources: []
+last_reinforced: 2026-05-10
+github_commit: pending
+tech_stack:
+  language: TypeScript
+  framework: OpenTelemetry 2.x
+---
+
+# 텔레메트리 (Telemetry)
+
+## 매 한 줄
+> **"매 system 이 자신의 internal state 를 외부로 emit 하는 행위 — 매 metric, trace, log 의 trinity."**. 매 Greek 어원 'tele (원격) + metron (측정)'. 2026 modern stack 의 매 de-facto standard 는 매 OpenTelemetry 2.x — 매 vendor-neutral 의 instrumentation API 와 매 OTLP wire protocol.
+
+## 매 핵심
+
+### 매 Three Pillars
+- **Metrics**: 매 numeric aggregation (counter, gauge, histogram). 매 low cardinality. 매 alerting 의 source.
+- **Traces**: 매 distributed request 의 causal chain. Span tree. 매 high cardinality.
+- **Logs**: 매 discrete event records. 매 structured (JSON) 권장.
+
+### 매 2026 추가 pillar
+- **Profiles** (continuous profiling): 매 CPU / memory flame graph 의 sampling. eBPF + pprof 의 stack. Pyroscope / Parca / Grafana Profiles.
+
+### 매 Push vs Pull
+- **Push**: agent → collector (OTLP, statsd). 매 ephemeral workload 적합.
+- **Pull**: scraper → endpoint (Prometheus). 매 long-running service 적합.
+
+### 매 응용
+1. SLO/SLI 의 측정 — 매 error budget 계산.
+2. Distributed debugging — 매 trace 로 매 cross-service latency 추적.
+3. Capacity planning — 매 historical metric 로 매 forecast.
+4. Security audit — 매 log + trace 의 incident reconstruction.
+
+## 💻 패턴
+
+### Pattern 1 — OpenTelemetry SDK setup (Node)
+```typescript
+import { NodeSDK } from '@opentelemetry/sdk-node';
+import { OTLPTraceExporter } from '@opentelemetry/exporter-trace-otlp-http';
+import { OTLPMetricExporter } from '@opentelemetry/exporter-metrics-otlp-http';
+import { PeriodicExportingMetricReader } from '@opentelemetry/sdk-metrics';
+import { resourceFromAttributes } from '@opentelemetry/resources';
+
+const sdk = new NodeSDK({
+  resource: resourceFromAttributes({
+    'service.name': 'order-api',
+    'service.version': '1.4.0',
+    'deployment.environment': process.env.ENV ?? 'dev',
+  }),
+  traceExporter: new OTLPTraceExporter({ url: 'http://otel-collector:4318/v1/traces' }),
+  metricReader: new PeriodicExportingMetricReader({
+    exporter: new OTLPMetricExporter({ url: 'http://otel-collector:4318/v1/metrics' }),
+    exportIntervalMillis: 10_000,
+  }),
+});
+
+sdk.start();
+```
+
+### Pattern 2 — Manual span
+```typescript
+import { trace, SpanStatusCode } from '@opentelemetry/api';
+
+const tracer = trace.getTracer('order-api');
+
+async function placeOrder(orderId: string) {
+  return tracer.startActiveSpan('placeOrder', async (span) => {
+    try {
+      span.setAttribute('order.id', orderId);
+      const result = await chargeCard(orderId);
+      span.setStatus({ code: SpanStatusCode.OK });
+      return result;
+    } catch (err) {
+      span.recordException(err as Error);
+      span.setStatus({ code: SpanStatusCode.ERROR });
+      throw err;
+    } finally {
+      span.end();
+    }
+  });
+}
+```
+
+### Pattern 3 — Counter / Histogram
+```typescript
+import { metrics } from '@opentelemetry/api';
+
+const meter = metrics.getMeter('order-api');
+const orderCounter = meter.createCounter('orders.placed', {
+  description: 'Total orders placed',
+});
+const latencyHist = meter.createHistogram('order.latency_ms', {
+  description: 'Order placement latency',
+  unit: 'ms',
+});
+
+const start = performance.now();
+await placeOrder(id);
+orderCounter.add(1, { region: 'kr', tier: 'premium' });
+latencyHist.record(performance.now() - start, { route: 'POST /orders' });
+```
+
+### Pattern 4 — Structured logging with trace correlation
+```typescript
+import { trace } from '@opentelemetry/api';
+import pino from 'pino';
+
+const logger = pino({
+  mixin: () => {
+    const span = trace.getActiveSpan();
+    if (!span) return {};
+    const ctx = span.spanContext();
+    return { trace_id: ctx.traceId, span_id: ctx.spanId };
+  },
+});
+
+logger.info({ orderId: '123' }, 'order placed');
+// 매 log → trace 의 매 join 가능.
+```
+
+### Pattern 5 — Sampling (head-based)
+```typescript
+import { TraceIdRatioBasedSampler, ParentBasedSampler } from '@opentelemetry/sdk-trace-base';
+
+const sdk = new NodeSDK({
+  sampler: new ParentBasedSampler({
+    root: new TraceIdRatioBasedSampler(0.1), // 매 10% sample.
+  }),
+  // ...
+});
+```
+
+### Pattern 6 — Exemplar (metric → trace link)
+```typescript
+import { ExplicitBucketHistogramAggregation } from '@opentelemetry/sdk-metrics';
+
+// 매 metric record 시 매 trace_id 첨부 — Grafana 의 매 metric → trace drill-down.
+latencyHist.record(latency, attrs);
+// 매 exemplar 는 매 SDK 가 매 active span 에서 자동 추출.
+```
+
+### Pattern 7 — Context propagation (HTTP header)
+```typescript
+import { propagation, context } from '@opentelemetry/api';
+
+// 매 outbound — header inject.
+const headers: Record<string, string> = {};
+propagation.inject(context.active(), headers);
+fetch('https://api.example.com', { headers });
+
+// 매 inbound — header extract.
+app.use((req, res, next) => {
+  const ctx = propagation.extract(context.active(), req.headers);
+  context.with(ctx, () => next());
+});
+// 매 traceparent / tracestate W3C header.
+```
+
+### Pattern 8 — RED method instrumentation
+```typescript
+// Rate, Errors, Duration — 매 service-level minimum.
+const reqCounter = meter.createCounter('http.requests');
+const errCounter = meter.createCounter('http.errors');
+const durHist = meter.createHistogram('http.duration_ms');
+
+app.use((req, res, next) => {
+  const start = performance.now();
+  res.on('finish', () => {
+    const labels = { route: req.route?.path, method: req.method, status: res.statusCode };
+    reqCounter.add(1, labels);
+    if (res.statusCode >= 500) errCounter.add(1, labels);
+    durHist.record(performance.now() - start, labels);
+  });
+  next();
+});
+```
+
+## 매 결정 기준
+| 상황 | Telemetry choice |
+|---|---|
+| 매 service-level alerting | Metrics (RED / USE) |
+| 매 cross-service latency 분석 | Traces |
+| 매 incident forensics | Logs + Traces |
+| 매 CPU hotspot | Profiles (continuous) |
+| 매 high cardinality dimension | Traces (NOT metrics) |
+| 매 cost 민감 | Sampling 0.01–0.1 |
+
+**기본값**: 매 OpenTelemetry SDK + OTLP exporter → Collector → Grafana / Datadog / Honeycomb. 매 vendor lock-in 의 회피.
+
+## 🔗 Graph
+- 변형: [[Tracing (Jaeger / Tempo)]]
+- Adjacent: [[OpenTelemetry Collector]]
+
+## 🤖 LLM 활용
+**언제**: 매 production service 의 instrumentation 설계, OTel migration, 매 cardinality 분석.
+**언제 X**: 매 dev-only script. 매 high cardinality dimension 을 metrics 에 — 매 cost explosion.
+
+## ❌ 안티패턴
+- **High cardinality on metrics**: 매 user_id 를 매 metric label — 매 storage 폭발.
+- **Trace 만 의존**: 매 trace 는 매 sampled — 매 absolute count 신뢰 X.
+- **Unstructured logs**: 매 string concat — 매 query 불가.
+- **Vendor SDK lock-in**: 매 OTel 대신 매 Datadog SDK 직접 — 매 migration 비용.
+- **No sampling**: 매 100% trace 전송 — 매 cost / latency 부담.
+
+## 🧪 검증 / 중복
+- Verified (OpenTelemetry 2.x docs 2026, CNCF observability whitepaper).
+- 신뢰도 A.
+
+## 🕓 Changelog
+| 날짜 | 변경 |
+|---|---|
+| 2026-05-08 | Phase 1 |
+| 2026-05-10 | Manual cleanup — Three Pillars + Profiles + 8 OTel patterns |