Bernie Pruss

Architecture Decision Records

Posted on August 17, 2025 by Bernie Pruss

Every software project faces countless technical decisions: which database to use, how to structure the API, what authentication method to implement, or whether to adopt microservices. These decisions shape the project’s future, yet they’re often made in isolation and quickly forgotten. Architecture Decision Records (ADRs) provide a structured way to capture these decisions, preserving the context and reasoning for future teams.

This guide will show you how to implement ADRs effectively, providing templates, tools, and real-world examples to help your team document decisions that matter.

What Are Architecture Decision Records?

Architecture Decision Records are short text documents that capture important architectural decisions made during a project. They answer three fundamental questions:

  1. What decision was made?
  2. Why was this decision made?
  3. What are the consequences?

ADRs differ from other documentation by focusing on decisions rather than descriptions. They capture the reasoning behind choices, not just the final outcome.

The Anatomy of an ADR

A well-structured ADR typically contains:

  • Status: Proposed, Accepted, Deprecated, Superseded
  • Context: The situation that prompted the decision
  • Decision: What was decided
  • Consequences: Both positive and negative outcomes

Why ADRs Matter

Knowledge Preservation

Teams change, but decisions persist. ADRs ensure that future developers understand not just what was built, but why it was built that way.

Decision Quality

The act of writing an ADR forces deeper thinking about trade-offs and alternatives, leading to better decisions.

Accountability

ADRs create a paper trail for architectural decisions, helping teams learn from both successes and failures.

Onboarding Acceleration

New team members can quickly understand the architectural landscape by reading through ADRs chronologically.

ADR Structure and Templates

Basic ADR Template

# ADR-001: [Title of Decision]

## Status
[Proposed | Accepted | Deprecated | Superseded]

## Context
What is the issue that we're seeing that is motivating this decision or change?

## Decision
What is the change that we're proposing and/or doing?

## Consequences
What becomes easier or more difficult to do because of this change?

---
Date: YYYY-MM-DD
Authors: [List of decision makers]

Enhanced ADR Template

For more complex decisions, consider this expanded template:

# ADR-XXX: [Decision Title]

## Metadata
- **Status**: [Proposed/Accepted/Deprecated/Superseded]
- **Date**: YYYY-MM-DD
- **Authors**: [Decision makers]
- **Reviewers**: [Stakeholders who reviewed]
- **Supersedes**: [Previous ADR numbers if applicable]

## Context and Problem Statement
Describe the context and problem statement that led to this decision.
What is the architectural problem we're trying to solve?

## Decision Drivers
What factors influenced this decision?
- Performance requirements
- Security constraints  
- Team expertise
- Budget limitations
- Timeline constraints

## Considered Options
What alternatives were considered?
1. Option 1: [Brief description]
2. Option 2: [Brief description]
3. Option 3: [Brief description]

## Decision Outcome
Chosen option: "[Option X]"

### Positive Consequences
- [Positive outcome 1]
- [Positive outcome 2]

### Negative Consequences
- [Negative outcome 1]
- [Negative outcome 2]

## Implementation Notes
Any specific implementation details or migration steps.

## Related Decisions
- Links to related ADRs
- Dependencies on other architectural decisions

Real-World ADR Examples

Example 1: Database Selection

# ADR-003: Use PostgreSQL for Primary Database

## Status
Accepted (2024-01-15)

## Context
Our application needs a reliable, ACID-compliant database that can handle:
- Complex queries with joins across multiple tables
- JSON document storage for flexible schemas
- Full-text search capabilities
- Concurrent read/write operations from multiple services
- Data integrity constraints

The team has experience with both relational and NoSQL databases.
We need to make a decision that will serve us for the next 2-3 years.

## Decision Drivers
- **Performance**: Sub-100ms query response times required
- **Scalability**: Must handle 10k+ concurrent users
- **Developer Experience**: Team has strong SQL experience
- **Operational Complexity**: Prefer battle-tested, well-documented solutions
- **Cost**: Open-source preferred to control licensing costs
- **Feature Requirements**: Need both relational and document storage

## Considered Options

### Option 1: PostgreSQL
**Pros:**
- Excellent SQL compliance and performance
- Native JSON support with indexing
- Strong consistency guarantees
- Extensive ecosystem and tooling
- Team expertise exists

**Cons:**
- Single-node bottleneck (though clustering available)
- More complex backup/recovery procedures
- Learning curve for advanced JSON features

### Option 2: MongoDB
**Pros:**
- Schema flexibility
- Horizontal scaling built-in
- Strong document query capabilities
- Good performance for document operations

**Cons:**
- Team lacks MongoDB expertise
- Complex transactions across collections
- Higher operational overhead
- Licensing considerations for advanced features

### Option 3: MySQL
**Pros:**
- Wide adoption and community
- Team familiarity
- Good performance for simple queries

**Cons:**
- Limited JSON support compared to PostgreSQL
- Less advanced indexing options
- Weaker constraint enforcement

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

## Consequences

### Positive
- Leverages existing team SQL expertise
- Single technology for both relational and document needs
- Strong data integrity guarantees
- Excellent tooling ecosystem (pgAdmin, monitoring tools)
- Cost-effective (open source)

### Negative
- Need to invest in PostgreSQL-specific optimization knowledge
- Scaling strategy will require careful planning
- JSON query optimization may require learning curve
- Backup/recovery procedures more complex than managed solutions

## Implementation Notes
- Start with single PostgreSQL 14+ instance
- Use connection pooling (PgBouncer)
- Implement read replicas when scaling needs arise
- Consider PostgreSQL extensions (pg_stat_statements, pg_trgm for search)

## Related Decisions
- ADR-004: Connection pooling strategy
- ADR-007: Backup and disaster recovery approach

ADR Management and Tooling

File Organization

docs/
├── adr/
│   ├── 0001-record-architecture-decisions.md
│   ├── 0002-use-postgresql-database.md
│   ├── 0003-adopt-microservices-architecture.md
│   ├── 0004-implement-api-gateway.md
│   └── README.md
├── architecture/
│   └── diagrams/
└── runbooks/

Numbering Convention

  • Sequential: ADR-0001, ADR-0002, ADR-0003
  • Date-based: ADR-2024-001, ADR-2024-002
  • Category-based: ADR-DB-001, ADR-API-001, ADR-SEC-001

ADR Lifecycle Management

#!/bin/bash
# ADR management helper script

create_adr() {
    local title="$1"
    local number=$(printf "%04d" $(($(ls docs/adr/*.md | wc -l) + 1)))
    local filename="docs/adr/${number}-$(echo "$title" | tr '[:upper:]' '[:lower:]' | tr ' ' '-').md"
    
    cat > "$filename" << EOF
# ADR-${number}: ${title}

## Status
Proposed

## Context
[Describe the context and problem statement]

## Decision
[Describe the decision]

## Consequences
[Describe the consequences, both positive and negative]

---
Date: $(date +%Y-%m-%d)  
Authors: [Your name]
EOF
    
    echo "Created: $filename"
}

# Usage: ./adr-helper.sh "Use Redis for Caching"
create_adr "$1"

Best Practices and Common Pitfalls

Writing Effective ADRs

Do:

  • Write ADRs when the decision impacts multiple people or future development
  • Include the decision-making process, not just the outcome
  • Update status when decisions change
  • Use clear, jargon-free language
  • Include concrete examples and code snippets when helpful

Don’t:

  • Document every minor technical decision
  • Write ADRs after implementation is complete
  • Make decisions in isolation—involve stakeholders
  • Use ADRs to justify poor decisions post-hoc
  • Delete superseded ADRs—mark them as superseded instead

Common Pitfalls

1. Too Much Detail

<!-- Too detailed -->
## Context
The application currently uses a custom JSON parser implementation 
that was written in 2019 by John Doe (employee ID 12345) during 
sprint 47 of the Q3 roadmap initiative...

<!-- Better -->
## Context  
Our custom JSON parser has performance issues and lacks features
compared to standard libraries. Maintenance overhead is high.

2. Missing Alternatives

<!-- Missing alternatives -->
## Decision
We will use Redis for caching.

<!-- Better -->
## Considered Options
1. Redis - In-memory, fast, good tooling
2. Memcached - Simpler, slightly faster for basic use cases  
3. In-process cache - No network overhead, but limited to single instance

## Decision
We chose Redis because...

3. Vague Consequences

<!-- Vague -->
## Consequences
This will make things better and improve performance.

<!-- Better -->
## Consequences
Positive:
- 40% reduction in API response times for cached data
- Simplified cache invalidation with Redis pub/sub

Negative:  
- Additional infrastructure to maintain and monitor
- Increased memory costs (~$200/month)
- Network dependency introduces potential failure point

Measuring ADR Success

Quantitative Metrics

  • Decision Velocity: Time from problem identification to decision
  • Decision Quality: Percentage of decisions that don’t require reversal
  • Knowledge Transfer: Time for new team members to understand architecture
  • Documentation Coverage: Percentage of significant decisions documented

Qualitative Indicators

  • Team members reference ADRs in discussions
  • Fewer “why did we build it this way?” questions
  • More structured decision-making conversations
  • Better alignment between team members on architectural direction

Conclusion

Architecture Decision Records are a lightweight yet powerful tool for improving team communication and preserving architectural knowledge. They work best when:

  1. Integrated into workflow: Make ADR creation part of your standard process
  2. Kept current: Update status as decisions evolve
  3. Focused on decisions: Document choices, not just descriptions
  4. Shared widely: Use ADRs as communication tools, not just documentation

Start small—document your next significant architectural decision using the basic template. As your team gets comfortable with the process, evolve your ADR practice to match your needs.

Remember: the goal isn’t perfect documentation, but better decision-making and knowledge sharing. ADRs are successful when they help your team make better decisions and onboard new members more effectively.

The best ADR is the one that gets written and used. Start with simple templates and evolve your practice based on what works for your team and organization.