Architecture Decision Record (ADR) - Technical Overview

An Architecture Decision Record (ADR) is a document that captures an important architectural decision made along with its context, rationale, and consequences. ADRs serve as a historical record of why certain technical decisions were made, helping teams understand the evolution of their system architecture.

High-Level Architecture

ADR Lifecycle Workflow

ADR Document Structure

Key Concepts

What is an ADR?

An ADR captures a single Architecture Decision (AD) and its rationale. Key components include:

• Architecture Decision (AD): A software design choice that addresses a significant requirement
• Architecture Decision Log (ADL): The collection of all ADRs for a project or organization
• Architecturally Significant Requirement (ASR): A requirement with measurable effect on system architecture

When to Create an ADR

Create ADRs when:

• There's no existing basis for a technical decision
• Multiple engineering options exist and you need to document the selection rationale
• Choosing between architectures (microservices vs monolith, cloud providers, etc.)
• Selecting significant technologies (databases, frameworks, protocols)
• Defining security protocols or data encryption standards

ADR Status Lifecycle

Status	Description
Draft	Initial creation, still being refined
Proposed	Ready for team review
Accepted	Approved and active - becomes immutable
Rejected	Not approved, kept for reference
Deprecated	No longer relevant but preserved
Superseded	Replaced by a newer ADR

Popular ADR Templates

Michael Nygard's Template (Original)

The simplest and most widely adopted format:

# ADR-001: Use PostgreSQL for User Data

## Status
Accepted

## Context
We need a database to store user profiles, authentication data,
and transactional records. The system requires ACID compliance,
complex queries, and horizontal scaling capability.

## Decision
We will use PostgreSQL as our primary database.

## Consequences
- Positive: Strong ACID compliance, mature ecosystem
- Positive: Excellent support for complex queries and JSON
- Negative: Requires more operational expertise than SQLite
- Negative: Horizontal scaling requires additional tooling

MADR (Markdown Architectural Decision Records)

Extended format with explicit options and trade-off analysis:

# ADR-002: Authentication Strategy

## Status
Accepted

## Context and Problem Statement
How should we implement user authentication for our API?

## Considered Options
1. Session-based authentication with cookies
2. JWT tokens with refresh mechanism
3. OAuth2 with external identity provider

## Decision Outcome
Chosen option: "JWT tokens with refresh mechanism"

### Consequences
- Good: Stateless, scales horizontally
- Good: Works across domains/services
- Bad: Token revocation is complex
- Bad: Larger request payload

## Pros and Cons of Options

### Session-based
- Good: Simple revocation
- Bad: Requires session store
- Bad: Doesn't work across domains

### OAuth2 External
- Good: Delegates auth complexity
- Bad: External dependency
- Bad: Additional integration work

Y-Statement Format

Ultra-concise single-sentence format:

In the context of building a real-time notification system,
facing the need for low-latency message delivery to thousands of clients,
we decided for WebSockets over HTTP polling
to achieve sub-second message delivery and reduced server load,
accepting the additional complexity of connection management and fallback handling.

ADR Tooling Ecosystem

adr-tools (Original CLI)

# Initialize ADR directory
adr init doc/adr

# Create new ADR
adr new "Use PostgreSQL for user data"
# Creates: doc/adr/0001-use-postgresql-for-user-data.md

# Create ADR that supersedes another
adr new -s 5 "Migrate to MongoDB for user data"
# Updates ADR 5 status to "Superseded by ADR 6"

# Generate table of contents
adr generate toc

# Link related ADRs
adr link 5 "Amends" 3 "Amended by"

Log4brains

Generates browsable static documentation site from ADRs:

# Install
npm install -g log4brains

# Initialize in project
log4brains init

# Preview documentation
log4brains preview

# Build static site
log4brains build

Real-World ADR Examples

Example: Database Selection ADR

# ADR-003: Database Choice for User Management Service

## Status
Accepted (2024-03-15)

## Context
Our user management service needs a database that supports:
- High availability (99.9% uptime requirement)
- Complex queries for user search and filtering
- Horizontal scalability for 10M+ users
- ACID transactions for user profile updates

Current user base: 500K active users, growing 20% monthly.

## Considered Options

### Option 1: PostgreSQL
- Proven ACID compliance
- Excellent query performance
- Strong ecosystem (extensions, tools)
- Team has existing expertise

### Option 2: MongoDB
- Flexible schema for evolving user profiles
- Built-in horizontal scaling
- JSON-native storage
- Steeper learning curve for team

### Option 3: CockroachDB
- Distributed SQL
- Automatic failover
- PostgreSQL wire protocol compatible
- Higher operational complexity

## Decision
We will use **PostgreSQL** as the primary database with **Redis**
as a caching layer for session management.

## Rationale
- PostgreSQL meets all functional requirements
- Team expertise reduces implementation risk
- Redis caching addresses performance needs
- Clear migration path to distributed PostgreSQL (Citus) if needed

## Consequences

### Positive
- Leverage existing team knowledge
- Mature tooling and monitoring
- Strong community support
- Cost-effective (open source)

### Negative
- Manual sharding if we exceed single-node capacity
- Redis adds operational complexity
- Potential data inconsistency between cache and DB

### Risks Accepted
- Will need to implement cache invalidation strategy
- May require Citus or similar for horizontal scaling beyond 50M users

Example: Microservices Migration ADR

# ADR-007: Migrate Order Processing to Microservices

## Status
Accepted (2024-06-01)

## Context
The monolithic e-commerce application is experiencing:
- Database connection pool exhaustion during peak traffic
- 45-minute build times affecting developer productivity
- Full application restarts for any deployment
- Single point of failure for the entire platform

Peak load: 10K orders/hour during sales events.

## Considered Options

1. **Vertical scaling** - Bigger servers, optimized queries
2. **Modular monolith** - Internal boundaries, separate deployments
3. **Microservices** - Independent services per domain

## Decision
Extract order processing into independent microservices:
- Order Service (order lifecycle management)
- Inventory Service (stock management)
- Payment Service (payment processing)
- Notification Service (customer communications)

Communication via event-driven architecture using Apache Kafka.

## Consequences

### Positive
- Independent scaling per service
- Faster build times (2-5 min vs 45 min)
- Fault isolation (payment issues don't affect browsing)
- Technology flexibility per service
- Smaller, focused teams

### Negative
- Operational complexity (multiple deployments)
- Network latency between services
- Distributed debugging challenges
- Eventual consistency (vs immediate consistency)
- Need for service mesh and observability tooling

### Migration Plan
1. Phase 1: Extract Notification Service (lowest risk)
2. Phase 2: Extract Inventory Service
3. Phase 3: Extract Payment Service
4. Phase 4: Extract Order Service (core domain)

## Related ADRs
- ADR-008: Event Sourcing for Order State
- ADR-009: Saga Pattern for Distributed Transactions

Team Adoption Workflow

Best Practices

Writing Effective ADRs

1. Keep it focused - One decision per ADR, avoid combining multiple decisions
2. Be specific - Include concrete details, not vague statements
3. Document trade-offs - Explain what you're accepting by choosing this option
4. Provide context - Future readers need to understand the situation
5. Keep it concise - Avoid turning ADRs into design documents

Storage and Organization

project/
├── docs/
│   └── adr/
│       ├── 0001-use-postgresql-for-user-data.md
│       ├── 0002-adopt-event-driven-architecture.md
│       ├── 0003-authentication-with-jwt.md
│       └── README.md (index/table of contents)

Review Meeting Structure

Phase	Duration	Activity
Reading	10-15 min	Silent reading of ADR document
Comments	5 min	Write inline comments on specific sections
Discussion	15-20 min	Address comments and questions
Decision	5 min	Accept, reject, or request revision

ADR Governance Rules

1. ADRs are immutable once accepted - create new ADR to change decisions
2. Never delete ADRs - mark as superseded or deprecated
3. Anyone can propose - but follow the review process
4. Keep meetings to < 45 minutes with < 10 participants
5. Review ADRs monthly against actual implementation

Key Facts (2025)

• Origin: Coined by Michael Nygard in 2011
• ThoughtWorks Radar: Listed as "Adopt" since 2018
• Major Adopters: AWS, Microsoft Azure, Google Cloud include ADR guidance in architecture frameworks
• UK Government: Published ADR Framework in December 2024 for public sector
• IBM Watson: Used 80+ ADRs to document microservices architecture evolution
• Storage: Most commonly stored as Markdown files in /docs/adr/ directory
• Popular Templates: MADR, Nygard, Y-Statement
• Key Tools: adr-tools, Log4brains, ADR Manager (VS Code), pyadr, dotnet-adr

Use Cases

1. Onboarding New Team Members

New developers can read the ADL to understand why the system is built the way it is, reducing knowledge transfer time.

2. Preventing Decision Reversal

Documented rationale prevents future architects from unknowingly reversing decisions without understanding the original context.

3. Audit and Compliance

ADRs provide evidence of thoughtful decision-making for security audits, compliance reviews, and due diligence.

4. Distributed Teams

Asynchronous ADR review enables decision-making across time zones without requiring synchronous meetings.

5. Technical Debt Tracking

Accepted trade-offs documented in consequences section become trackable technical debt items.

6. Architecture Evolution

Superseding ADRs create a clear timeline of how the architecture evolved and why.

Anti-Patterns to Avoid

Anti-Pattern	Problem	Solution
Too vague	"We chose X because it's better"	Include specific criteria and measurements
Too long	10-page design documents	Keep to 1-2 pages, link to detailed docs
No options	Only documenting chosen solution	Always list 2-3 alternatives considered
No consequences	Missing trade-off analysis	Explicitly state positive AND negative impacts
Abandoned	Initial enthusiasm, then forgotten	Monthly reviews, integrate into workflow
Decision by committee	20-person review meetings	Limit to < 10 cross-functional representatives

Sources

• ADR GitHub Organization - Official templates and guidance
• Joel Parker Henderson's ADR Repository - Comprehensive examples and templates
• AWS Prescriptive Guidance on ADRs
• AWS Architecture Blog - Master ADRs
• Microsoft Azure Well-Architected Framework - ADR
• Google Cloud Architecture Center - ADRs
• UK Government ADR Framework
• TechTarget - 8 Best Practices for Creating ADRs
• MADR Template Documentation
• adr-tools GitHub
• Agile Alliance - Distribute Design Authority with ADRs
• Olaf Zimmermann - MADR Template Explained