Skill v1.0.0
currentAutomated scan100/100version: "1.0.0" 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.
Use this skill when
- Making significant architectural decisions
- Documenting technology choices
- Recording design trade-offs
- Onboarding new team members
- Reviewing historical decisions
- Establishing decision-making processes
Do not use this skill when
- You only need to document small implementation details
- The change is a minor patch or routine maintenance
- There is no architectural decision to capture
Instructions
- Capture the decision context, constraints, and drivers.
- Document considered options with tradeoffs.
- Record the decision, rationale, and consequences.
- Link related ADRs and update status over time.
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Proposed → Accepted → Deprecated → Superseded↓Rejected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)
# ADR-0001: Use PostgreSQL as Primary Database## StatusAccepted## ContextWe need to select a primary database for our new e-commerce platform. The systemwill 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 locatorThe team has experience with MySQL, PostgreSQL, and MongoDB. We need ACIDcompliance 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-textsearch, 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 (needElasticsearch), 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## DecisionWe will use **PostgreSQL 15** as our primary database.## RationalePostgreSQL provides the best balance of:1.**ACID compliance** essential for e-commerce transactions2.**Built-in capabilities** (full-text search, JSONB, PostGIS) reduceinfrastructure complexity3.**Team familiarity** with SQL databases reduces learning curve4.**Mature ecosystem** with excellent tooling and community supportThe slight complexity in replication is outweighed by the reduction inadditional 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
# ADR-0012: Adopt TypeScript for Frontend Development**Status**: Accepted**Date**: 2024-01-15**Deciders**: @alice, @bob, @charlie## ContextOur React codebase has grown to 50+ components with increasing bug reportsrelated to prop type mismatches and undefined errors. PropTypes provideruntime-only checking.## DecisionAdopt TypeScript for all new frontend code. Migrate existing code incrementally.## Consequences**Good**: Catch type errors at compile time, better IDE support, self-documentingcode.**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
# ADR-0015: API Gateway SelectionIn 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
# ADR-0020: Deprecate MongoDB in Favor of PostgreSQL## StatusAccepted (Supersedes ADR-0003)## ContextADR-0003 (2021) chose MongoDB for user profile storage due to schema flexibilityneeds. 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## DecisionDeprecate MongoDB and migrate user profiles to PostgreSQL.## Migration Plan1.**Phase 1** (Week 1-2): Create PostgreSQL schema, dual-write enabled2.**Phase 2** (Week 3-4): Backfill historical data, validate consistency3.**Phase 3** (Week 5): Switch reads to PostgreSQL, monitor4.**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 LearnedDocument 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
# RFC-0025: Adopt Event Sourcing for Order Management## SummaryPropose adopting event sourcing pattern for the order management domain toimprove auditability, enable temporal queries, and support business analytics.## MotivationCurrent challenges:1.Audit requirements need complete order history2."What was the order state at time X?" queries are impossible3.Analytics team needs event stream for real-time dashboards4.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)## Alternatives1. **Audit tables**: Simpler but doesn't enable temporal queries2. **CDC from existing DB**: Complex, doesn't change data model3. **Hybrid**: Event source only for order state changes## Unresolved Questions- [ ] Event schema versioning strategy- [ ] Retention policy for events- [ ] Snapshot frequency for performance## Implementation Plan1. 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)
# Architecture Decision RecordsThis 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 ADR1.Copy `template.md` to `NNNN-title-with-dashes.md`2.Fill in the template3.Submit PR for review4.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)
# Install adr-toolsbrew install adr-tools# Initialize ADR directoryadr init docs/adr# Create new ADRadr new "Use PostgreSQL as Primary Database"# Supersede an ADRadr new -s 3 "Deprecate MongoDB in Favor of PostgreSQL"# Generate table of contentsadr generate toc > docs/adr/README.md# Link related ADRsadr link 2 "Complements" 1 "Is complemented by"
Review Process
## 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