[G1-Sync] Manual knowledge update
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Antigravity Agent
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---
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id: quality-engineering-excellence
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title: Engineering Excellence — DORA / SPACE / DX metric
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category: Coding
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status: draft
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source_trust_level: B
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verification_status: conceptual
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created_at: 2026-05-09
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updated_at: 2026-05-09
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tags: [quality, productivity, vibe-coding]
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tech_stack: { language: "process", applicable_to: ["Engineering"] }
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applied_in: []
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aliases: [DORA, DORA metrics, SPACE, DX, developer experience, deployment frequency, lead time, MTTR]
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---
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# Engineering Excellence (DORA / SPACE / DX)
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> "Good team 가 무엇 측정?" **DORA 4 가 baseline. SPACE 가 holistic. DX 가 modern**. Vanity metric (LOC, commit count) 안.
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## 📖 핵심 개념
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- DORA: Delivery + reliability.
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- SPACE: 5 dimension (satisfaction, performance, activity, communication, efficiency).
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- DX: developer experience.
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## 💻 코드 패턴
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### DORA 4 metrics
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```
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1. Deployment Frequency: 매 day vs 매 month.
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2. Lead Time for Changes: PR open → prod.
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3. Change Failure Rate: deploy 의 % 가 incident.
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4. MTTR (Mean Time To Recovery): incident → fix.
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```
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### Elite vs Low
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```
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Elite:
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- Daily+ deploy.
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- < 1 hour lead time.
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- < 5% failure.
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- < 1 hour MTTR.
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Low:
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- Monthly deploy.
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- 1+ month lead time.
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- 16-30% failure.
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- 1+ week MTTR.
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→ Elite team 가 2x 더 많이 ship + 2x 적은 incident.
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```
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→ "Accelerate" book (Forsgren).
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### Measure (자동)
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```yaml
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# GitHub
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- PR open: timestamp.
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- Deploy success: timestamp.
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- Lead time = deploy - first commit.
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# DataDog / Honeycomb / Sleuth
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- Auto-collect.
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- Per-team / per-service.
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```
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### SPACE framework
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```
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S - Satisfaction
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P - Performance (output / outcome)
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A - Activity (volume — but careful)
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C - Communication / collaboration
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E - Efficiency / flow
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```
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→ Multi-dimensional. Activity 만 = 위험 (게임).
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### Activity 의 함정
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```
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"매 dev 가 매주 X commit"
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→ Goodhart's law: target 가 measure 되면 fail.
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→ Padding commit, busy work.
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→ 측정 = activity but goal = outcome.
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```
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### DX (Developer Experience)
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```
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Build time, deploy time, dev env setup, hot reload, test time, dashboard ...
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→ "Friction" 을 측정.
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DX 가 좋음 = velocity.
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```
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→ "DX" by Abi Noda (research).
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### Build time
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```
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< 1 min: green.
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1-5 min: yellow.
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> 5 min: red.
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→ Cache + parallel + smaller bundle.
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```
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### Deploy time
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```
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< 5 min: elite.
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5-30 min: high.
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> 30 min: low.
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→ CI / CD pipeline 의 dependency.
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```
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### Local dev setup
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```
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Onboarding 의 시간:
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- < 1 hour: elite.
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- < 1 day: good.
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- > 1 week: 가짜.
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→ Docker compose, devcontainer, automated.
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```
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### Test time
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```
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Unit: < 30 sec.
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Integration: < 5 min.
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E2E: < 15 min.
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→ Slow test = skip 자주.
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```
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### Survey
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```
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"이 codebase 가 일하기 쉬운가?"
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"매 PR 가 review 빠른가?"
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"Tooling 가 좋은가?"
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→ Quarterly survey + score.
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```
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### Lighthouse / Web Vitals (UX)
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```
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LCP: < 2.5s.
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FID: < 100ms.
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CLS: < 0.1.
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→ User experience metric.
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```
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### SLO (Service Level Objective)
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```
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99.9% uptime = 4 hour 22 min / month down.
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99.95% = 21.6 min.
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99.99% = 4.32 min.
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99.999% (5 9's) = 26 sec — 매우 어려움.
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→ Match SLA / cost.
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```
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### Incident (MTTR breakdown)
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```
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Detection time: alert → human aware.
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Acknowledgement: human aware → action.
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Resolution: action → fix.
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Recovery: fix → user happy.
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→ 매 phase 측정 + improve.
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```
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### Postmortem
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```
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매 P0/P1 incident:
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- Timeline.
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- Root cause (5 whys).
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- Action items (concrete).
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- Public (blameless).
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→ [[Productivity_Postmortem]].
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```
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### Code review metric
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```
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- Time to first review (target < 4 hour).
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- Approval count (1-2).
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- LOC per PR (< 400).
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- Iterations per PR (< 3).
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→ Big PR = slow review = lead time ↑.
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```
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→ "Small PR culture" 가 큰 lever.
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### Test coverage
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```
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60-80% = baseline.
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100% = brittle.
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0% = scary.
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→ Coverage 가 quality 의 proxy 만.
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Mutation 가 진짜.
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```
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### Tech debt 측정
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```
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- TODO comment count.
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- Deprecated API 사용 (Snyk, Sourcegraph).
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- 큰 file (> 500 LOC).
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- Cyclomatic complexity > 10.
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→ "Debt ratio" 가 trend.
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```
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### CodeClimate / Sonar
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```
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Auto metric:
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- Maintainability.
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- Test coverage.
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- Duplication.
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- Complexity.
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→ PR 가 quality gate.
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```
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### Engineering productivity ≠ output
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```
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"Velocity = code 작성 ↑" ≠ "Productivity ↑".
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Productivity = customer outcome.
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→ 매 commit 가 가치 가져야.
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"이 PR 가 user 의 무엇 fix?"
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```
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### Goodhart 의 law
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```
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"매 dev 가 매주 X commit"
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→ Padding.
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"Coverage 100%"
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→ 가짜 test.
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"PR 매주 N 개"
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→ Big PR 가 split 가짜.
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→ Metric 가 target 가 됨 = 게임.
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```
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→ Mix of metrics + judgment.
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### Real-world
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- **Google**: monorepo + DORA + SPACE.
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- **Spotify**: tribe model + autonomy metric.
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- **Microsoft**: SPACE 의 origin.
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- **Pinterest**: DORA + DX.
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- **Intuit**: developer survey.
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### Dashboard
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```
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매 team 의:
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- Deploy / day.
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- Lead time p50.
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- Incident MTTR.
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- PR cycle time.
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- DX score.
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→ Trend track.
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```
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→ Sleuth, LinearB, Code Climate, Faros.
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### LinearB / Sleuth (managed)
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```
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GitHub / GitLab → 자동 metric.
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- Cycle time visualization.
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- Bottleneck identification.
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- Per-team comparison.
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```
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### Engineering ladder
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```
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Promotion criteria:
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- Junior: complete task.
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- Senior: own feature.
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- Staff: own system.
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- Principal: cross-team impact.
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→ Metric + qualitative.
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```
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### Avoid
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```
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- "Most active" award (commit count).
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- LOC / day target.
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- Coverage 100% gate.
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- Strict deploy frequency.
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- Comparison 가 individual (team OK).
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```
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### Best practice
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```
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1. DORA baseline.
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2. SPACE survey (quarterly).
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3. DX friction (build, deploy, test).
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4. Incident postmortem.
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5. Mix: metric + survey + judgment.
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```
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## 🤔 의사결정 기준
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| 측정 | Tool |
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| DORA | Sleuth / LinearB / GitHub Actions |
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| SPACE | Survey + dashboard |
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| DX | Build / test time + survey |
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| Code quality | Sonar / CodeClimate |
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| Test coverage | Codecov |
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| Performance | Lighthouse CI / Web Vitals |
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| Incident | PagerDuty / Linear |
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## ❌ 안티패턴
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- **Activity 만**: padding / busy work.
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- **LOC measure**: misalign.
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- **Individual leaderboard**: morale ↓.
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- **100% coverage gate**: brittle test.
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- **Strict daily deploy**: 가짜 deploy.
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- **Goodhart's law 무시**: metric 가짜.
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- **Survey 없음**: blind.
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## 🤖 LLM 활용 힌트
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- DORA 가 baseline (4 metric).
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- SPACE 가 holistic (5 dimension).
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- DX 가 modern (friction).
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- Goodhart's law 항상 인지.
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## 🔗 관련 문서
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- [[Productivity_Estimating_Effort]]
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- [[Quality_Code_Metrics]]
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- [[Productivity_OKR_Goals]]
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