---
id: wiki-2026-0508-root-cause-analysis-rca
title: Root Cause Analysis (RCA)
category: 10_Wiki/Topics
status: verified
canonical_id: self
aliases: [RCA, 5 Whys, Fishbone Analysis]
duplicate_of: none
source_trust_level: A
confidence_score: 0.9
verification_status: applied
tags: [debugging, problem-solving, methodology, sre]
raw_sources: []
last_reinforced: 2026-05-10
github_commit: pending
tech_stack:
  language: Methodology
  framework: SRE/DevOps
---

# Root Cause Analysis (RCA)

## 매 한 줄
> **"매 symptom 의 X, root 의 fix"**. Toyota Production System (Ohno, 1950s) 에서 originate — 매 modern SRE/DevOps 의 incident postmortem 의 standard practice (Google SRE Book, Etsy blameless postmortem).

## 매 핵심

### 매 5 Whys 기법
1. Symptom: "Server crashed."
2. Why? → "Out of memory."
3. Why? → "Memory leak in v2.3."
4. Why? → "Connection pool not closed on error."
5. Why? → "Test framework didn't cover error path."
6. Why? → "Coverage gate excluded `except` blocks." ← root.

### 매 핵심 원칙
- **Blameless**: person 의 X, system 의 attack.
- **Symptom ≠ root**: stop at first plausible cause = X RCA.
- **Multiple roots**: 매 single-root 의 myth — 매 contributing factors 의 web.

### 매 응용
1. Production incident postmortems (SRE).
2. Bug investigation (recurring crashes).
3. Quality control (manufacturing defects).
4. Process failures (project delays).

## 💻 패턴

### Postmortem template (markdown)
```markdown
# Incident: [name] — YYYY-MM-DD

## Summary
1-paragraph what happened.

## Impact
- Users affected: N
- Duration: HH:MM
- Revenue/SLO: ...

## Timeline (UTC)
- HH:MM — alert fired
- HH:MM — engineer paged
- HH:MM — mitigation
- HH:MM — resolved

## Root cause
The proximate cause was X. The underlying root cause was Y because Z.

## What went well
- Detection time was <5min thanks to alert A.

## What went poorly
- Runbook was outdated.

## Action items
- [ ] [P0] Fix Y in service S — owner @alice — due YYYY-MM-DD
- [ ] [P1] Update runbook — owner @bob

## Lessons learned
- ...
```

### Fishbone (Ishikawa) categories
```
Problem: Database queries timing out
├── People: New engineer didn't index
├── Process: Migration review missed perf check
├── Tools: ORM hides slow query
├── Environment: Prod DB has 10x test data
├── Materials: Schema changed without index
└── Measurement: No p99 latency SLO
```

### Logical inversion debugging
```python
# Don't ask "why is it broken?"
# Ask "why would it work?"
def diagnose(system):
    assumptions = list_assumptions(system)
    for a in assumptions:
        if not verify(a):
            return f"Failing assumption: {a}"
    return "All assumptions hold — symptom misread"
```

### Bisection for regression
```bash
# Git bisect: binary search for root commit
git bisect start
git bisect bad HEAD          # current is broken
git bisect good v2.2.0       # known good
# git auto-checks out commits — test each, mark good/bad
git bisect run ./test.sh     # automate
```

### Causal graph (DAG)
```python
import networkx as nx

G = nx.DiGraph()
G.add_edge("missing index", "slow query")
G.add_edge("slow query", "request timeout")
G.add_edge("request timeout", "circuit breaker open")
G.add_edge("circuit breaker open", "503 errors")

# Walk back from symptom
ancestors = nx.ancestors(G, "503 errors")
print(ancestors)  # all roots
```

### Five-whys with LLM assist (2026)
```python
from anthropic import Anthropic
client = Anthropic()

def five_whys(symptom: str, context: str):
    prompt = f"""Apply 5 Whys RCA to this incident.
Symptom: {symptom}
Context: {context}

Output 5 levels of "Why?" with concrete hypotheses.
End with a falsifiable root cause and a test to verify it."""
    return client.messages.create(
        model="claude-opus-4-7",
        max_tokens=2048,
        messages=[{"role": "user", "content": prompt}]
    ).content[0].text
```

## 매 결정 기준
| 상황 | Approach |
|---|---|
| Single failure event | 5 Whys |
| Complex multi-factor | Fishbone / Causal DAG |
| Regression in code | git bisect |
| Recurring incidents | Pareto analysis on RCA categories |
| Safety-critical (medical/aero) | Formal FMEA / FTA |

**기본값**: 5 Whys + blameless postmortem template, escalate to fishbone if multi-root.

## 🔗 Graph
- 부모: [[Problem_Solving|Problem-Solving]]
- 변형: [[Postmortem]] · [[FMEA]]
- 응용: [[Debugging]] · [[Quality-Control]]
- Adjacent: [[Wicked-Problems]] · [[Causal-Inference]]

## 🤖 LLM 활용
**언제**: Incident 후 postmortem 의 작성. Recurring bug 의 deep investigation. Symptom 의 multiple plausible causes 의 enumerate.
**언제 X**: Trivial bug (typo, off-by-one) — RCA overkill. Time-critical mitigation 의 phase — fix first, RCA later.

## ❌ 안티패턴
- **Blame culture**: "Who broke it?" → people 의 hide info → RCA 의 fail.
- **Stop at first cause**: "Engineer pushed bad code" 는 X root — process 의 why 의 ask.
- **No action items**: insight 의 doc, but X follow-up → 매 same incident 의 repeat.
- **Single-root assumption**: complex system 의 contributing factors 의 web — 매 multiple roots 의 normal.

## 🧪 검증 / 중복
- Verified (Toyota TPS, Google SRE Book Ch.15, Etsy blameless postmortem culture).
- 신뢰도 A.

## 🕓 Changelog
| 날짜 | 변경 |
|---|---|
| 2026-05-08 | Phase 1 |
| 2026-05-10 | Manual cleanup — RCA with 5 Whys, fishbone, postmortem template, LLM-assist |
