architecture-decision-records

Architecture Decision Records

重要な技術的決定の背景と根拠を記録するArchitecture Decision Records（ADR）の作成、維持、管理のための包括的なパターンです。

このスキルを使用するタイミング

• 重要なアーキテクチャ上の決定を行うとき
• 技術選定を文書化するとき
• 設計上のトレードオフを記録するとき
• 新しいチームメンバーをオンボーディングするとき
• 過去の決定をレビューするとき
• 意思決定プロセスを確立するとき

このスキルを使用しないタイミング

• 小規模な実装の詳細のみを文書化する必要があるとき
• 変更が軽微なパッチor定常的なメンテナンスであるとき
• 記録すべきアーキテクチャ上の決定がないとき

手順

1. 決定の背景、制約、推進要因を記録します。
2. 検討した選択肢とそのトレードオフを文書化します。
3. 決定事項、根拠、および結果を記録します。
4. 関連するADRをリンクし、時間の経過とともにステータスを更新します。

基本概念

1. ADRとは何か

Architecture Decision Recordには以下を記録します。

• Context（背景）: なぜその決定が必要になったのか
• Decision（決定）: 何を決定したのか
• Consequences（結果）: その結果として何が起こるのか

2. ADRを作成するタイミング

ADRを作成する	ADRを省略する
新しいフレームワークの採用	マイナーバージョンのアップグレード
データベース技術の選定	バグ修正
APIデザインパターン	実装の詳細
セキュリティアーキテクチャ	定常的なメンテナンス
統合パターン	設定変更

3. ADRのライフサイクル

Proposed → Accepted → Deprecated → Superseded
              ↓
           Rejected

テンプレート

テンプレート1: 標準ADR（MADR形式）

# ADR-0001: Use PostgreSQL as Primary Database

## Status

Accepted

## Context

We need to select a primary database for our new e-commerce platform. The system
will handle:
- ~10,000 concurrent users
- Complex product catalog with hierarchical categories
- Transaction processing for orders and payments
- Full-text search for products
- Geospatial queries for store locator

The team has experience with MySQL, PostgreSQL, and MongoDB. We need ACID
compliance for financial transactions.

## Decision Drivers

* **Must have ACID compliance** for payment processing
* **Must support complex queries** for reporting
* **Should support full-text search** to reduce infrastructure complexity
* **Should have good JSON support** for flexible product attributes
* **Team familiarity** reduces onboarding time

## Considered Options

### Option 1: PostgreSQL
- **Pros**: ACID compliant, excellent JSON support (JSONB), built-in full-text
  search, PostGIS for geospatial, team has experience
- **Cons**: Slightly more complex replication setup than MySQL

### Option 2: MySQL
- **Pros**: Very familiar to team, simple replication, large community
- **Cons**: Weaker JSON support, no built-in full-text search (need
  Elasticsearch), no geospatial without extensions

### Option 3: MongoDB
- **Pros**: Flexible schema, native JSON, horizontal scaling
- **Cons**: No ACID for multi-document transactions (at decision time),
  team has limited experience, requires schema design discipline

## Decision

We will use **PostgreSQL 15** as our primary database.

## Rationale

PostgreSQL provides the best balance of:
1. **ACID compliance** essential for e-commerce transactions
2. **Built-in capabilities** (full-text search, JSONB, PostGIS) reduce
   infrastructure complexity
3. **Team familiarity** with SQL databases reduces learning curve
4. **Mature ecosystem** with excellent tooling and community support

The slight complexity in replication is outweighed by the reduction in
additional services (no separate Elasticsearch needed).

## Consequences

### Positive
- Single database handles transactions, search, and geospatial queries
- Reduced operational complexity (fewer services to manage)
- Strong consistency guarantees for financial data
- Team can leverage existing SQL expertise

### Negative
- Need to learn PostgreSQL-specific features (JSONB, full-text search syntax)
- Vertical scaling limits may require read replicas sooner
- Some team members need PostgreSQL-specific training

### Risks
- Full-text search may not scale as well as dedicated search engines
- Mitigation: Design for potential Elasticsearch addition if needed

## Implementation Notes

- Use JSONB for flexible product attributes
- Implement connection pooling with PgBouncer
- Set up streaming replication for read replicas
- Use pg_trgm extension for fuzzy search

## Related Decisions

- ADR-0002: Caching Strategy (Redis) - complements database choice
- ADR-0005: Search Architecture - may supersede if Elasticsearch needed

## References

- [PostgreSQL JSON Documentation](https://www.postgresql.org/docs/current/datatype-json.html)
- [PostgreSQL Full Text Search](https://www.postgresql.org/docs/current/textsearch.html)
- Internal: Performance benchmarks in `/docs/benchmarks/database-comparison.md`

テンプレート2: 軽量ADR

# ADR-0012: Adopt TypeScript for Frontend Development

**Status**: Accepted
**Date**: 2024-01-15
**Deciders**: @alice, @bob, @charlie

## Context

Our React codebase has grown to 50+ components with increasing bug reports
related to prop type mismatches and undefined errors. PropTypes provide
runtime-only checking.

## Decision

Adopt TypeScript for all new frontend code. Migrate existing code incrementally.

## Consequences

**Good**: Catch type errors at compile time, better IDE support, self-documenting
code.

**Bad**: Learning curve for team, initial slowdown, build complexity increase.

**Mitigations**: TypeScript training sessions, allow gradual adoption with
`allowJs: true`.

テンプレート3: Y-Statement形式

# ADR-0015: API Gateway Selection

In the context of **building a microservices architecture**,
facing **the need for centralized API management, authentication, and rate limiting**,
we decided for **Kong Gateway**
and against **AWS API Gateway and custom Nginx solution**,
to achieve **vendor independence, plugin extensibility, and team familiarity with Lua**,
accepting that **we need to manage Kong infrastructure ourselves**.

テンプレート4: 非推奨化のためのADR

# ADR-0020: Deprecate MongoDB in Favor of PostgreSQL

## Status

Accepted (Supersedes ADR-0003)

## Context

ADR-0003 (2021) chose MongoDB for user profile storage due to schema flexibility
needs. Since then:
- MongoDB's multi-document transactions remain problematic for our use case
- Our schema has stabilized and rarely changes
- We now have PostgreSQL expertise from other services
- Maintaining two databases increases operational burden

## Decision

Deprecate MongoDB and migrate user profiles to PostgreSQL.

## Migration Plan

1. **Phase 1** (Week 1-2): Create PostgreSQL schema, dual-write enabled
2. **Phase 2** (Week 3-4): Backfill historical data, validate consistency
3. **Phase 3** (Week 5): Switch reads to PostgreSQL, monitor
4. **Phase 4** (Week 6): Remove MongoDB writes, decommission

## Consequences

### Positive
- Single database technology reduces operational complexity
- ACID transactions for user data
- Team can focus PostgreSQL expertise

### Negative
- Migration effort (~4 weeks)
- Risk of data issues during migration
- Lose some schema flexibility

## Lessons Learned

Document from ADR-0003 experience:
- Schema flexibility benefits were overestimated
- Operational cost of multiple databases was underestimated
- Consider long-term maintenance in technology decisions

テンプレート5: Request for Comments（RFC）スタイル

# RFC-0025: Adopt Event Sourcing for Order Management

## Summary

Propose adopting event sourcing pattern for the order management domain to
improve auditability, enable temporal queries, and support business analytics.

## Motivation

Current challenges:
1. Audit requirements need complete order history
2. "What was the order state at time X?" queries are impossible
3. Analytics team needs event stream for real-time dashboards
4. Order state reconstruction for customer support is manual

## Detailed Design

### Event Store

OrderCreated { orderId, customerId, items[], timestamp } OrderItemAdded { orderId, item, timestamp } OrderItemRemoved { orderId, itemId, timestamp } PaymentReceived { orderId, amount, paymentId, timestamp } OrderShipped { orderId, trackingNumber, timestamp }

### Projections

- **CurrentOrderState**: Materialized view for queries
- **OrderHistory**: Complete timeline for audit
- **DailyOrderMetrics**: Analytics aggregation

### Technology

- Event Store: EventStoreDB (purpose-built, handles projections)
- Alternative considered: Kafka + custom projection service

## Drawbacks

- Learning curve for team
- Increased complexity vs. CRUD
- Need to design events carefully (immutable once stored)
- Storage growth (events never deleted)

## Alternatives

1. **Audit tables**: Simpler but doesn't enable temporal queries
2. **CDC from existing DB**: Complex, doesn't change data model
3. **Hybrid**: Event source only for order state changes

## Unresolved Questions

- [ ] Event schema versioning strategy
- [ ] Retention policy for events
- [ ] Snapshot frequency for performance

## Implementation Plan

1. Prototype with single order type (2 weeks)
2. Team training on event sourcing (1 week)
3. Full implementation and migration (4 weeks)
4. Monitoring and optimization (ongoing)

## References

- [Event Sourcing by Martin Fowler](https://martinfowler.com/eaaDev/EventSourcing.html)
- [EventStoreDB Documentation](https://www.eventstore.com/docs)

ADRの管理

ディレクトリ構成

docs/
├── adr/
│   ├── README.md           # Index and guidelines
│   ├── template.md         # Team's ADR template
│   ├── 0001-use-postgresql.md
│   ├── 0002-caching-strategy.md
│   ├── 0003-mongodb-user-profiles.md  # [DEPRECATED]
│   └── 0020-deprecate-mongodb.md      # Supersedes 0003

ADRインデックス（README.md）

# Architecture Decision Records

This directory contains Architecture Decision Records (ADRs) for [Project Name].

## Index

| ADR | Title | Status | Date |
|-----|-------|--------|------|
| 0001 | Use PostgreSQL as Primary Database | Accepted | 2024-01-10 |
| 0002 | Caching Strategy with Redis | Accepted | 2024-01-12 |
| 0003 | MongoDB for User Profiles | Deprecated | 2023-06-15 |
| 0020 | Deprecate MongoDB | Accepted | 2024-01-15 |

## Creating a New ADR

1. Copy `template.md` to `NNNN-title-with-dashes.md`
2. Fill in the template
3. Submit PR for review
4. Update this index after approval

## ADR Status

- **Proposed**: Under discussion
- **Accepted**: Decision made, implementing
- **Deprecated**: No longer relevant
- **Superseded**: Replaced by another ADR
- **Rejected**: Considered but not adopted

自動化（adr-tools）

# Install adr-tools
brew install adr-tools

# Initialize ADR directory
adr init docs/adr

# Create new ADR
adr new "Use PostgreSQL as Primary Database"

# Supersede an ADR
adr new -s 3 "Deprecate MongoDB in Favor of PostgreSQL"

# Generate table of contents
adr generate toc > docs/adr/README.md

# Link related ADRs
adr link 2 "Complements" 1 "Is complemented by"

レビュープロセス

## ADR Review Checklist

### Before Submission
- [ ] Context clearly explains the problem
- [ ] All viable options considered
- [ ] Pros/cons balanced and honest
- [ ] Consequences (positive and negative) documented
- [ ] Related ADRs linked

### During Review
- [ ] At least 2 senior engineers reviewed
- [ ] Affected teams consulted
- [ ] Security implications considered
- [ ] Cost implications documented
- [ ] Reversibility assessed

### After Acceptance
- [ ] ADR index updated
- [ ] Team notified
- [ ] Implementation tickets created
- [ ] Related documentation updated

ベストプラクティス

推奨事項

• ADRは早期に作成する - 実装開始前に作成します
• 短く保つ - 最大1〜2ページにします
• トレードオフについて正直に記す - 実際のデメリットを含めます
• 関連する決定をリンクする - 決定のつながりを構築します
• ステータスを更新する - 置き換えられたら非推奨にします

非推奨事項

• 承認済みのADRを変更しない - 置き換える場合は新しいADRを作成します
• 背景を省略しない - 将来の読者には前提知識が必要です
• 失敗を隠さない - 却下された決定にも価値があります
• 曖昧にしない - 具体的な決定と具体的な結果を記します
• 実装を忘れない - 行動に結びつかないADRは無駄になります

リソース

• Documenting Architecture Decisions（Michael Nygard）
• MADR Template
• ADR GitHub Organization
• adr-tools