Architecture Decision Records: A Practical Template for Better Software Decisions
Architecture Decision Records: A Practical Template for Better Software Decisions
In software development, we make countless architectural decisions that shape our applications. From choosing frameworks and databases to deciding on deployment strategies, these decisions have long-lasting impacts on our projects. Yet we rarely document why we made those choices.
Architecture Decision Records (ADRs) provide a structured way to capture the context, reasoning, and consequences of important architectural decisions. This guide presents a practical template and instructions for implementing ADRs in your projects.
Table of Contents
- What Are Architecture Decision Records?
- The ADR Template Structure
- Best Practices for ADRs
- Real-World Example: Database Selection
- Common Pitfalls to Avoid
- Conclusion
What Are Architecture Decision Records?
Architecture Decision Records are short documents that capture an important architectural decision together with its context and consequences. They serve as a historical record of why certain decisions were made, which is invaluable for:
- Future team members who need to understand existing decisions
- Current team members who may forget the reasoning behind past choices
- Decision reviews when circumstances change
- Learning from outcomes -- both successful and unsuccessful decisions
The ADR Template Structure
The following template structure balances thoroughness with practicality:
Metadata Table
Every ADR starts with a metadata table that provides quick reference information:
| Field | Value |
| -------- | -------------------------------------------------- |
| title | Use React with TypeScript for Frontend Development |
| status | accepted |
| impact | high |
| Driver | Sarah Johnson (Tech Lead) |
| Approver | Mike Chen (Engineering Manager) |
| created | 2025-01-15 |
| Outcome | Accepted - Implementation started Q1 2025 |
Key Fields Explained:
- Title: Clear, descriptive name for the decision
- Status:
proposedthenaccepted/rejected/deferred, and eventuallysupersededif the decision is later revisited - Impact:
low/medium/high- helps prioritize and track important decisions - Driver: Person leading the decision-making process
- Approver: Person with authority to approve the decision
- Created: Date when the ADR was created
- Outcome: Final result and any implementation notes
Core Sections
1. Context and Problem Statement
This section sets the stage. Explain:
- What situation led to the need for a decision
- What problem the team is trying to solve
- Why this decision is necessary now
- Any relevant background information
Example:
## Context and Problem Statement
Our current frontend is built with jQuery and has become difficult to maintain
as the application has grown to over 50 interactive components. The codebase
lacks proper state management, testing is challenging, and new developer
onboarding takes weeks. We need to modernize our frontend architecture to
support continued growth and improve developer productivity.
User complaints about slow page loads and inconsistent UI behavior have
increased 40% over the past quarter, indicating our current approach isn't
scaling effectively.
2. Decision Drivers
List the key factors that will influence the decision:
Example:
## Decision Drivers
- **Developer Experience**: Need faster development cycles and easier debugging
- **Performance**: Must improve page load times and user interactions
- **Maintainability**: Code should be easier to test, refactor, and extend
- **Team Skills**: Must align with current team capabilities or reasonable learning curve
- **Long-term Support**: Technology should have strong community and corporate backing
- **Integration**: Must work well with existing backend APIs and deployment pipeline
3. Considered Options
Document every serious alternative that was evaluated:
Example:
## Considered Options
### Option 1: React with TypeScript
- **Pros**: Strong typing, excellent tooling, large community, team has some experience
- **Cons**: Learning curve for TypeScript, build complexity increases
- **Estimated effort**: 3-4 months for full migration
### Option 2: Vue.js with JavaScript
- **Pros**: Gentler learning curve, good documentation, progressive adoption possible
- **Cons**: Smaller community than React, team has no experience
- **Estimated effort**: 2-3 months for full migration
### Option 3: Continue with jQuery + incremental improvements
- **Pros**: No learning curve, immediate improvements possible
- **Cons**: Doesn't address core architectural issues, technical debt continues growing
- **Estimated effort**: 1-2 months for improvements
4. Decision Outcome
State clearly what was decided and list any immediate actions:
Example:
## Decision Outcome
**Chosen Option: React with TypeScript**
We will migrate our frontend to React with TypeScript over the next 4 months,
starting with new features and gradually converting existing components.
**Immediate Actions:**
- Set up React/TypeScript development environment by January 30th
- Create component library and style guide by February 15th
- Begin migration with user dashboard (highest impact area) by March 1st
- Train team through weekly workshops starting February 1st
5. Consequences
Document the positive and negative consequences alike:
Example:
## Consequences
### Positive Consequences
- **Improved Developer Productivity**: Type safety will catch errors earlier
- **Better Testing**: React's component model enables easier unit testing
- **Performance Gains**: Modern build tools and component optimization
- **Future-Proofing**: React's ecosystem provides growth path for advanced features
### Negative Consequences
- **Short-term Productivity Loss**: 2-3 week learning curve for team members
- **Increased Build Complexity**: More sophisticated toolchain required
- **Migration Risk**: Potential for bugs during transition period
- **Dependency on NPM Ecosystem**: More third-party dependencies to manage
6. Links
Include references to relevant resources:
Example:
## Links
- [Performance Analysis Report](./performance-analysis-2024.md)
- [Team Skills Assessment](./team-skills-react-2024.md)
- [React vs Vue Comparison Study](https://example.com/react-vue-comparison)
- [TypeScript Migration Guide](./typescript-migration-plan.md)
- [Original RFC Discussion](https://github.com/company/engineering-rfcs/pull/42)
Best Practices for ADRs
1. Write ADRs for Significant Decisions
Not every decision needs an ADR. Focus on decisions that:
- Have long-term impact on the system
- Are difficult or expensive to reverse
- Affect multiple teams or components
- Involve trade-offs between important factors
2. Write ADRs When the Decision is Made
Don't wait until later to document decisions. Write the ADR:
- During the decision-making process
- Before implementation begins
- While the reasoning is fresh in everyone's mind
3. Keep ADRs Concise but Complete
Aim for one to two pages at most. Include enough detail for someone to understand the decision without additional context, but do not over-elaborate.
4. Make ADRs Immutable
Once an ADR is approved:
- Do not edit the content (typo corrections are the only exception).
- If circumstances change, create a new ADR that supersedes the old one.
- This preserves the historical record of what was known at the time of the decision.
5. Store ADRs with Your Code
Keep ADRs in your project repository, typically in:
docs/
architecture/
decisions/
001-use-react-typescript.md
002-adopt-microservices.md
003-choose-postgresql.md
Real-World Example: Database Selection
The following example shows how this template might look for a database decision:
# Use PostgreSQL for Primary Database
| Field | Value |
| -------- | ----------------------------------- |
| title | Use PostgreSQL for Primary Database |
| status | accepted |
| impact | high |
| Driver | Alex Kumar (Backend Lead) |
| Approver | Sarah Johnson (CTO) |
| created | 2025-01-10 |
| Outcome | Accepted - Migration planned for Q2 |
## Context and Problem Statement
Our application currently uses MySQL but we're hitting performance limitations
with complex queries and JSON data handling. We need a database that can:
- Handle complex analytical queries efficiently
- Provide better JSON/NoSQL hybrid capabilities
- Support our growing data science requirements
- Maintain ACID compliance for financial transactions
## Decision Drivers
- **Performance**: Complex reporting queries taking 30+ seconds
- **JSON Support**: Increasing need for flexible document storage
- **Analytics**: Data team needs better SQL analytics capabilities
- **Compliance**: Must maintain strict consistency for financial data
- **Operational Complexity**: Prefer single database over polyglot persistence
## Considered Options
### Option 1: PostgreSQL
- **Pros**: Excellent JSON support, powerful analytics, strong consistency
- **Cons**: Team learning curve, migration complexity
- **Cost**: Similar hosting costs, 2-month migration effort
### Option 2: MongoDB + MySQL
- **Pros**: JSON-native, familiar MySQL for transactions
- **Cons**: Operational complexity, data synchronization challenges
- **Cost**: Higher operational overhead, 3-month implementation
### Option 3: Stay with MySQL + optimization
- **Pros**: No migration risk, team expertise
- **Cons**: Doesn't solve core JSON/analytics limitations
- **Cost**: 1 month optimization, ongoing performance issues
## Decision Outcome
**Chosen Option: PostgreSQL**
We will migrate to PostgreSQL in Q2 2025, starting with read replicas for
analytics workloads, then gradually migrating write workloads.
## Consequences
### Positive Consequences
- **Query Performance**: 60-80% improvement in complex queries
- **Feature Velocity**: JSON capabilities enable faster feature development
- **Analytics**: Data team can work directly with production data
- **Future Growth**: Better foundation for machine learning features
### Negative Consequences
- **Migration Risk**: 2-month period with dual database complexity
- **Learning Curve**: Team needs training on PostgreSQL-specific features
- **Tooling Changes**: Some MySQL-specific tools need replacement
## Links
- [Database Performance Analysis](./db-performance-2024.md)
- [PostgreSQL Migration Plan](./postgresql-migration-plan.md)
- [Cost Analysis Spreadsheet](./db-cost-analysis.xlsx)
Common Pitfalls to Avoid
1. Being Too Vague
❌ "Use microservices for better scalability" ✅ "Split user management into separate service to handle 10x user growth expected in Q3"
2. Omitting Alternatives
Always document the options that were considered, even if some were quickly dismissed.
3. Forgetting to Update Status
Keep the status field current as decisions move through the approval process.
4. Writing ADRs After Implementation
The value lies in capturing the decision-making process itself, not just documenting what was built.
Conclusion
Architecture Decision Records provide a structured way to capture the reasoning behind important technical decisions. By documenting context, alternatives, and consequences, ADRs help teams to:
- Make better-informed decisions
- Avoid repeating past mistakes
- Onboard new team members faster
- Review and learn from outcomes
The template provided here balances thoroughness with practicality, making it straightforward to adopt ADRs without creating excessive documentation overhead.
Start small. Pick one significant upcoming decision and use this template to document it. As your team sees the benefits, ADRs will naturally become part of your architectural decision-making process.
The goal is not perfect documentation. It is better decision-making through structured thinking and shared understanding.