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Proposed → Accepted → Deprecated → Superseded ↓ Rejected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)

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
• PostgreSQL Full Text Search
• 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

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

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

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

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
• EventStoreDB Documentation

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 Records

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

Index

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)

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

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