refactor(topics): 멀티 에이전트용 지식 재편 — _Common(공통 기본기) + Domain_* 구조
에이전트 8종(대화형/프로그래머 C·S/디자이너/설계자/기획자/QA/PD/PM)에게 [공통 기본 능력 + 롤별 Specialty] 2층으로 지식을 주입하기 위한 재분류. 문서 내용·포맷은 무수정, 폴더 이동만 (6,372개 문서 수 보존 확인). - Topic_Programming → Domain_Programming (내부 구조 보존) - Topic_Graphic → Domain_Design - Topic_Business → Domain_Product - Topic_General → Domain_General - _Common 신설: Math(구 Topic_Math_Specialty), Reasoning(구 General/From_Thinking & Reasoning), Reasoning_Creativity(구 General/From_창의성), Communication(Poetic_Blog_Writing + From_writing) - 타 도메인의 From_* 폴더는 유지 (출처 표기일 뿐, 이미 도메인에 맞게 분류된 문서) - 빈 폴더 정리 (memory/procedures) - 에이전트→폴더 매핑은 workspace의 .astra/agent-knowledge-map.json (9개 에이전트) Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
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---
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id: wiki-2026-0508-enterprise-software-engineering
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title: Enterprise Software Engineering
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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: [enterprise SE, SDLC, large-scale software, enterprise architecture]
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duplicate_of: none
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source_trust_level: A
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confidence_score: 0.95
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verification_status: applied
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tags: [software-engineering, enterprise, sdlc, process, architecture, scale]
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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: Universal
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applicable_to: [Enterprise, Large-scale, Regulated]
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---
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# Enterprise Software Engineering
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## 매 한 줄
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> **"매 scale + 매 compliance + 매 long-lifecycle 의 software"**. 매 startup velocity 의 X — 매 audit + 매 SLA + 매 multi-team. 매 modern: 매 platform engineering + DevSecOps + observability + AI-augmented (Copilot, Cursor, Anthropic).
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## 매 핵심
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### 매 challenge
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- **Scale**: 매 100s of teams.
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- **Compliance**: SOX, HIPAA, GDPR, PCI.
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- **Legacy**: 매 monolith + 매 mainframe.
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- **Multi-stakeholder**: 매 product + ops + security + legal.
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- **Long lifecycle**: 매 10년+.
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### 매 modern paradigm
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- **Platform engineering**: 매 IDP (Internal Dev Platform).
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- **DevSecOps**: 매 security shift-left.
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- **GitOps**: 매 declarative infra.
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- **SRE**: 매 reliability budget.
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- **DORA metrics**: 매 4 key.
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- **Team Topologies**: 매 stream-aligned + platform.
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### 매 architecture
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- **Monolith → Microservice**: 매 strangler.
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- **Modular monolith**: 매 alternative.
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- **Event-driven**: 매 Kafka, EDA.
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- **API-first**: 매 OpenAPI, gRPC.
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- **Data mesh**: 매 domain-owned data.
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### 매 process
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- **Agile / Scrum**: 매 small batch.
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- **SAFe**: 매 enterprise scale (controversial).
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- **Trunk-based**: 매 modern CI/CD.
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- **DORA**: 매 deploy frequency, lead time, MTTR, change fail rate.
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### 매 응용
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1. **Banking**: 매 core system.
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2. **Telco**: 매 BSS / OSS.
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3. **Healthcare**: 매 EHR.
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4. **Government**: 매 procurement.
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5. **Insurance**: 매 claim.
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## 💻 패턴
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### DORA metrics dashboard
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```python
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def compute_dora(deployments, incidents, period_days=30):
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return {
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'deploy_frequency': len(deployments) / period_days,
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'lead_time_p50_hours': median(d.commit_to_deploy_hours for d in deployments),
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'mttr_minutes': median(i.detect_to_resolve_min for i in incidents),
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'change_fail_rate': sum(d.caused_incident for d in deployments) / len(deployments),
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}
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```
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### Strangler fig (legacy migration)
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```typescript
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// 매 facade routes new 의 new, old 의 old
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async function getUser(id: string) {
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if (await featureFlag('new-user-service', { userId: id })) {
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return newUserService.fetch(id);
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}
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return legacyUserDao.findById(id);
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}
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```
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### Platform IDP (Backstage)
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```yaml
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# catalog-info.yaml
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apiVersion: backstage.io/v1alpha1
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kind: Component
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metadata:
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name: payments-service
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annotations:
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backstage.io/source-location: url:https://github.com/acme/payments
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spec:
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type: service
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lifecycle: production
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owner: team-payments
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system: checkout
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```
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### GitOps (ArgoCD)
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```yaml
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apiVersion: argoproj.io/v1alpha1
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kind: Application
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metadata:
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name: payments-prod
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spec:
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source:
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repoURL: https://github.com/acme/k8s-manifests
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path: prod/payments
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destination:
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server: https://kubernetes.default.svc
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namespace: payments
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syncPolicy:
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automated: { prune: true, selfHeal: true }
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```
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### SLO / Error Budget
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```yaml
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# 매 99.9% SLO → 43.2 min/month error budget
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slo:
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service: payments
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objective: 99.9%
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measurement_window: 30d
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burn_rate_alerts:
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- severity: page
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lookback: 1h
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threshold: 14.4 # 매 fast burn (consume 1d in 1h)
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- severity: ticket
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lookback: 6h
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threshold: 6
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```
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### Audit log
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```typescript
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function audit(action: string, actor: string, target: string, metadata: object) {
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auditStream.publish({
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timestamp: new Date().toISOString(),
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action, actor, target,
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metadata,
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correlationId: getRequestId(),
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});
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}
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// 매 immutable + retention 7y
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```
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### Compliance check (PII access)
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```python
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def access_pii(user_id, requester):
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if not has_role(requester, 'pii_reader'):
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raise PermissionError()
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audit('pii_read', requester, user_id, {})
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if requires_purpose(user_id):
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return prompt_for_purpose(requester)
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return fetch_user(user_id)
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```
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### Multi-tenancy (Postgres RLS)
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```sql
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ALTER TABLE orders ENABLE ROW LEVEL SECURITY;
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CREATE POLICY tenant_isolation ON orders
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USING (tenant_id = current_setting('app.tenant_id')::uuid);
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```
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### Trunk-based deploy
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```yaml
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on: { push: { branches: [main] } }
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jobs:
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deploy:
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steps:
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- run: npm test
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- run: npm run build
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- run: deploy.sh staging
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- run: smoke-test.sh staging
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- run: deploy.sh canary 5
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- run: monitor.sh canary 5m
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- run: deploy.sh prod
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```
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### Disaster recovery test
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```python
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def chaos_dr_test():
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# 매 quarterly DR drill
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primary_db.simulate_failure()
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assert app_reads_from(replica_db)
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promote(replica_db)
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assert app_writes_to(replica_db)
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rollback()
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```
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### Architecture decision record
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```markdown
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# ADR-0042: Adopt Kafka over RabbitMQ for event bus
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## Context
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50 services, growing 5/quarter, current RabbitMQ at 80% capacity.
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## Decision
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Kafka MSK with mTLS, schema registry, 7-day retention.
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## Consequences
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+ Replay capability
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+ Throughput headroom
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- Operational complexity
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- Cost +30% Year 1
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```
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### Team Topologies (boundary)
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```yaml
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teams:
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- name: payments
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type: stream-aligned
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owns: [payments-service, billing-svc]
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- name: platform
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type: platform
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provides: [k8s, observability, secrets]
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serves: [payments, checkout, ...]
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- name: security
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type: enabling
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enables: [...]
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```
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### AI-augmented dev (Copilot policies)
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```yaml
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ai_policy:
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copilot: enabled
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data_residency: eu-west-1
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excluded_paths:
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- secrets/
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- compliance/
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audit_log: true
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```
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## 매 결정 기준
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| 상황 | Approach |
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|---|---|
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| Greenfield | Cloud-native + IDP |
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| Legacy modernize | Strangler fig |
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| Compliance-heavy | DevSecOps + audit |
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| Multi-team | Platform engineering |
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| Reliability | SLO + error budget |
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| Slow deploys | Trunk-based + CI/CD |
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**기본값**: 매 platform IDP + 매 GitOps + 매 SLO + 매 DORA tracking + 매 trunk-based + 매 ADR.
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## 🔗 Graph
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- 변형: [[Platform-Engineering]] · [[CI/CD Pipeline & IDE Security Integration|DevSecOps]] · [[SRE]]
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- 응용: [[Microservices]] · [[Modular Monolith]] · [[GitOps]]
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- Adjacent: [[Team Topologies]] · [[DORA]] · [[Backstage]] · [[ArgoCD]] · [[Development Communication Standards]]
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## 🤖 LLM 활용
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**언제**: 매 large org. 매 regulated industry. 매 long-lived system.
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**언제 X**: 매 startup MVP. 매 throwaway.
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## ❌ 안티패턴
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- **Process for process sake**: 매 velocity ↓.
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- **Skip compliance**: 매 fines.
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- **Big-bang migration**: 매 risk.
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- **Single team owns all**: 매 bottleneck.
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- **No DORA measurement**: 매 improvement 의 invisible.
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## 🧪 검증 / 중복
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- Verified (Accelerate, Team Topologies, Google SRE, Platform Engineering).
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- 신뢰도 A.
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## 🕓 Changelog
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| 날짜 | 변경 |
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|---|---|
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| 2026-04-20 | Auto-reinforced |
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| 2026-05-08 | Phase 1 |
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| 2026-05-10 | Manual cleanup — DORA + 매 strangler / Backstage / GitOps / SLO / RLS code |
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