git:20260623.276561b to git:20260721.a6bfd72

+ ---

+ name: architecture-decision-records

+ description: Write and maintain Architecture Decision Records (ADRs) following best practices for technical decision documentation. Use when documenting significant technical decisions, reviewing past architectural choices, or establishing decision processes.

+ ---

+

+ # Architecture Decision Records

+

+ Comprehensive patterns for creating, maintaining, and managing Architecture Decision Records (ADRs) that capture the context and rationale behind significant technical decisions.

+

+ ## When to Use This Skill

+

+ - Making significant architectural decisions

+ - Documenting technology choices

+ - Recording design trade-offs

+ - Onboarding new team members

+ - Reviewing historical decisions

+ - Establishing decision-making processes

+

+ ## Core Concepts

+

+ ### 1. What is an ADR?

+

+ An Architecture Decision Record captures:

+

+ - **Context**: Why we needed to make a decision

+ - **Decision**: What we decided

+ - **Consequences**: What happens as a result

+

+ ### 2. When to Write an ADR

+

+ | Write ADR | Skip ADR |

+ | -------------------------- | ---------------------- |

+ | New framework adoption | Minor version upgrades |

+ | Database technology choice | Bug fixes |

+ | API design patterns | Implementation details |

+ | Security architecture | Routine maintenance |

+ | Integration patterns | Configuration changes |

+

+ ### 3. ADR Lifecycle

+

+ ```

+ Proposed → Accepted → Deprecated → Superseded

+ ↓

+ Rejected

+ ```

+

+ ## Templates

+

+ ### Template 1: Standard ADR (MADR Format)

+

+ ```markdown

+ # 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`

+ ```

+

+ ### Template 2: Lightweight ADR

+

+ ```markdown

+ # 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`.

+ ```

+

+ ### Template 3: Y-Statement Format

+

+ ```markdown

+ # 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**.

+ ```

+

+ ### Template 4: ADR for Deprecation

+

+ ```markdown

+ # 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

+ ```

+

+ ### Template 5: Request for Comments (RFC) Style

+

+ ```markdown

+ # 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 Management

+

+ ### Directory Structure

+

+ ```

+ 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 Index (README.md)

+

+ ```markdown

+ # Architecture Decision Records

+

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

+

+ ## Index

+

+ | ADR | Title | Status | Date |

+ | ------------------------------------- | ---------------------------------- | ---------- | ---------- |

+ | [0001](0001-use-postgresql.md) | Use PostgreSQL as Primary Database | Accepted | 2024-01-10 |

+ | [0002](0002-caching-strategy.md) | Caching Strategy with Redis | Accepted | 2024-01-12 |

+ | [0003](0003-mongodb-user-profiles.md) | MongoDB for User Profiles | Deprecated | 2023-06-15 |

+ | [0020](0020-deprecate-mongodb.md) | 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

+ ```

+

+ ### Automation (adr-tools)

+

+ ```bash

+ # 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"

+ ```

+

+ ## Review Process

+

+ ```markdown

+ ## 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

+ ```

+

+ ## Best Practices

+

+ ### Do's

+

+ - **Write ADRs early** - Before implementation starts

+ - **Keep them short** - 1-2 pages maximum

+ - **Be honest about trade-offs** - Include real cons

+ - **Link related decisions** - Build decision graph

+ - **Update status** - Deprecate when superseded

+

+ ### Don'ts

+

+ - **Don't change accepted ADRs** - Write new ones to supersede

+ - **Don't skip context** - Future readers need background

+ - **Don't hide failures** - Rejected decisions are valuable

+ - **Don't be vague** - Specific decisions, specific consequences

+ - **Don't forget implementation** - ADR without action is waste