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Antigravity Agent
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id: wiki-2026-0508-system-debugging-protocol
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title: System Debugging Protocol
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category: 10_Wiki/Topics
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status: verified
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canonical_id: self
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aliases: [Debug Workflow, Incident Debugging, SRE Debug Protocol]
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duplicate_of: none
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source_trust_level: A
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confidence_score: 0.85
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verification_status: applied
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tags: [debugging, sre, incident, observability]
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raw_sources: []
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last_reinforced: 2026-05-10
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github_commit: pending
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tech_stack:
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language: shell/python
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framework: opentelemetry
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---
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# System Debugging Protocol
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## 매 한 줄
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> **"매 production system 의 이상 발생 시 가설 → 측정 → 수정 의 disciplined loop"**. 매 Brendan Gregg USE method, 매 Google SRE Workbook 의 incident protocol, 매 2026 OpenTelemetry + LLM-assisted 의 standard. 매 ad-hoc 디버깅 vs 체계적 protocol 의 결정적 차이.
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## 매 핵심
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### 매 Phase
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1. **Detect**: alert 또는 user report.
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2. **Triage**: severity (P0-P4), scope, blast radius.
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3. **Stabilize**: rollback / circuit-break — root cause 의 wait 금지.
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4. **Diagnose**: USE / RED / TSA method.
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5. **Fix**: patch + verify.
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6. **Post-mortem**: blameless writeup.
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### 매 Diagnostic methods
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- **USE (Brendan Gregg)**: 매 resource 의 Utilization / Saturation / Errors.
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- **RED**: 매 service 의 Rate / Errors / Duration.
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- **TSA (Thread State Analysis)**: 매 CPU / off-CPU profiling.
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- **4 golden signals (Google)**: latency, traffic, errors, saturation.
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### 매 응용
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1. Web service slowness diagnosis.
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2. Memory leak hunt.
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3. DB lock investigation.
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4. Distributed tracing.
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## 💻 패턴
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### USE method checklist
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```bash
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# CPU
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mpstat -P ALL 1
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# Memory
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free -m; vmstat 1
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# Disk
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iostat -xz 1
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# Network
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sar -n DEV 1
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# All saturation in one
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top; vmstat 1; iostat -xz 1
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```
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### Distributed trace via OpenTelemetry
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```python
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from opentelemetry import trace
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tracer = trace.get_tracer(__name__)
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@tracer.start_as_current_span("process_order")
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def process_order(order_id: str):
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span = trace.get_current_span()
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span.set_attribute("order.id", order_id)
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with tracer.start_as_current_span("db.fetch"):
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order = db.get(order_id)
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with tracer.start_as_current_span("external.payment"):
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charge(order)
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```
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### Bisection (find regression commit)
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```bash
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git bisect start
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git bisect bad HEAD
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git bisect good v2.5.0
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# Run test at each step
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git bisect run pytest tests/regression.py
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git bisect reset
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```
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### Memory leak hunt (heap snapshot diff)
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```bash
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# Node.js
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node --inspect app.js
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# Chrome devtools → Memory → Heap snapshot at T0, T1
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# Compare → "Comparison" view → grow-only objects
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# Python
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import tracemalloc
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tracemalloc.start()
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# ... run workload ...
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snap1 = tracemalloc.take_snapshot()
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# ... run more ...
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snap2 = tracemalloc.take_snapshot()
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for stat in snap2.compare_to(snap1, 'lineno')[:10]: print(stat)
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```
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### Flame graph
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```bash
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# Linux
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perf record -F 99 -p $PID -g -- sleep 30
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perf script | stackcollapse-perf.pl | flamegraph.pl > flame.svg
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# Async profiler (JVM, on-CPU + off-CPU)
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./profiler.sh -d 30 -f flame.html $PID
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```
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### SQL slow query (Postgres)
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```sql
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-- top slow
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SELECT query, calls, mean_exec_time, total_exec_time
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FROM pg_stat_statements
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ORDER BY total_exec_time DESC LIMIT 20;
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-- live locks
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SELECT pid, usename, query, state, wait_event_type, wait_event
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FROM pg_stat_activity
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WHERE state != 'idle' ORDER BY xact_start;
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-- explain
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EXPLAIN (ANALYZE, BUFFERS) SELECT ... ;
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```
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### Hypothesis-driven debug log
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```markdown
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## Incident #2026-05-09-01
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- T0 12:34: Alert: p99 latency > 2s on /api/checkout
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- H1: DB slow → check pg_stat_statements → REJECTED (no slow queries)
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- H2: External payment API → trace shows 1.8s in stripe.charge() → CONFIRMED
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- Action: circuit-break stripe; queue charges for retry
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- T0+15min: latency recovered
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```
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### Rollback protocol
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```bash
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# Kubernetes
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kubectl rollout undo deployment/api
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kubectl rollout status deployment/api
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# Feature flag
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curl -X POST $LD_API/flags/$KEY/off
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```
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## 매 결정 기준
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| 상황 | Approach |
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| User-facing impact | Stabilize first (rollback) → diagnose |
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| Internal dev env | Diagnose deeply, no rollback urgency |
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| Repro available | Local debug + bisect |
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| Heisenbug | Production tracing + sampling |
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| Memory leak | Heap snapshot diff |
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| Latency spike | Distributed trace + flame graph |
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**기본값**: Stabilize → Hypothesis → Measure → Fix → Post-mortem.
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## 🔗 Graph
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- 부모: [[SRE]] · [[Observability]]
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- 변형: [[Four Golden Signals]]
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- 응용: [[Post-Mortem]] · [[Performance_Profiling_and_Memory|Performance Profiling]]
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- Adjacent: [[OpenTelemetry]] · [[Flame Graphs]] · [[Distributed Tracing]]
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## 🤖 LLM 활용
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**언제**: log pattern 분석, 가설 생성, post-mortem 초안.
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**언제 X**: live incident command (human judgment 필요).
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## ❌ 안티패턴
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- **No stabilization**: 디버깅 중 service down 지속.
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- **Multiple changes at once**: 매 fix 의 attribution 불가.
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- **Skip post-mortem**: 매 same incident 의 반복.
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- **Blame culture**: 매 honest disclosure 의 chilling effect.
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## 🧪 검증 / 중복
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- Verified (Brendan Gregg USE, Google SRE Book ch.12-14).
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- 신뢰도 A.
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## 🕓 Changelog
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| 날짜 | 변경 |
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| 2026-05-08 | Phase 1 |
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| 2026-05-10 | Manual cleanup — Debug protocol full coverage |
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