architecture-decision-records

架构决策记录

用于创建、维护和管理架构决策记录（ADR）的综合模式，记录重大技术决策背后的背景和理由。

适用场景

• 做出重大的架构决策
• 记录技术选型
• 记录设计权衡
• 帮助新团队成员熟悉项目
• 回顾历史决策
• 建立决策流程

不适用场景

• 只需记录小型实现细节
• 变更只是小幅修补或例行维护
• 没有需要记录的架构决策

说明

1. 记录决策背景、约束条件和驱动因素。
2. 记录考虑过的选项及其权衡。
3. 记录决策、理由和后果。
4. 链接相关 ADR，并随时间更新状态。

核心概念

1. 什么是 ADR？

架构决策记录会记录：

• 背景：我们为何需要做出决策
• 决策：我们做出了什么决定
• 后果：决策带来的影响

2. 何时编写 ADR

编写 ADR	跳过 ADR
采用新框架	小幅版本升级
数据库技术选型	Bug 修复
API 设计模式	实现细节
安全架构	例行维护
集成模式	配置变更

3. ADR 生命周期

Proposed → Accepted → Deprecated → Superseded
              ↓
           Rejected

模板

模板 1：标准 ADR（MADR 格式）

# 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**: Compare version-specific JSON, full-text and spatial capabilities against measured requirements; MySQL includes full-text indexes and spatial features.

### Option 3: MongoDB
- **Pros**: Flexible schema, native JSON, horizontal scaling
- **Cons**: Multi-document transactions are supported on qualifying modern deployments; assess their overhead and topology constraints,
  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. **Capabilities** (built-in full-text search/JSONB plus the PostGIS extension) 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`

模板 2：轻量级 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`.

模板 3：Y-Statement 格式

# 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**.

模板 4：弃用类 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

模板 5：征求意见（RFC）风格

# 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 (event retention and privacy/deletion requirements need an explicit policy)

## Alternatives

1. **Audit tables**: Simpler; temporal queries depend on which history and ordering are captured
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 管理

目录结构

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 索引（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

自动化（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"

审查流程

## 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

最佳实践

应做事项

• 尽早编写 ADR - 在开始实现之前
• 保持简短 - 最多 1-2 页
• 如实说明权衡 - 列出实际缺点
• 链接相关决策 - 构建决策关系图
• 更新状态 - 被取代时标记为弃用

不应做事项

• 不要修改已接受的 ADR - 编写新的 ADR 来取代它
• 不要省略背景 - 后续读者需要了解背景
• 不要隐瞒失败 - 被否决的决策也很有价值
• 不要含糊其辞 - 决策要具体，后果也要具体
• 不要忘记实施 - 没有行动的 ADR 毫无价值

资源

• 架构决策文档（Michael Nygard）
• MADR 模板
• ADR GitHub 组织
• adr-tools

限制

• 仅当任务明确符合上述范围时，才使用此技能。
• 不要将输出视为环境特定验证、测试或专家审查的替代品。
• 如果缺少必要输入、权限、安全边界或成功标准，请停止并请求澄清。

这些模板中的所有决策、基准、日期以及人员配置／时间安排均为虚构示例，并非关于用户项目的证据。新提案在获得授权决策者接受之前，应标记为 Proposed。比较选项前，应审查部署环境中供应商的具体能力，记录不确定性，并要求为双重写入设计回滚／协调方案。替换人工维护的 README 前，应先审查 ADR 索引输出。