Architecture Decision Record Template
A standardized template for documenting architectural decisions, their context, and consequences.
What is an ADR?
An Architecture Decision Record (ADR) is a document that captures an important architectural decision along with its context and consequences. ADRs help teams:
- Remember why decisions were made
- Onboard new team members faster
- Avoid relitigating settled decisions
- Understand trade-offs that were considered
The Template
Copy and use this template for each significant architectural decision:
# ADR-[NUMBER]: [TITLE]
## Status
[Proposed | Accepted | Deprecated | Superseded by ADR-XXX]
## Date
[YYYY-MM-DD]
## Context
[Describe the issue motivating this decision. What is the problem or opportunity?
Include relevant background, constraints, and forces at play.]
## Decision Drivers
* [Driver 1: e.g., "Need to support 10x current traffic"]
* [Driver 2: e.g., "Team has limited experience with technology X"]
* [Driver 3: e.g., "Must integrate with existing system Y"]
* [Driver 4: e.g., "Budget constraints limit options"]
## Considered Options
### Option 1: [Name]
[Brief description]
**Pros:**
* [Pro 1]
* [Pro 2]
**Cons:**
* [Con 1]
* [Con 2]
### Option 2: [Name]
[Brief description]
**Pros:**
* [Pro 1]
* [Pro 2]
**Cons:**
* [Con 1]
* [Con 2]
### Option 3: [Name]
[Brief description]
**Pros:**
* [Pro 1]
* [Pro 2]
**Cons:**
* [Con 1]
* [Con 2]
## Decision
[State the decision that was made. Be clear and specific.
Example: "We will use PostgreSQL as our primary database."]
## Rationale
[Explain why this option was chosen over the alternatives.
Reference the decision drivers and how this option addresses them.]
## Consequences
### Positive
* [Positive consequence 1]
* [Positive consequence 2]
### Negative
* [Negative consequence 1]
* [Negative consequence 2]
### Neutral
* [Neutral consequence or follow-up action required]
## Related Decisions
* [ADR-XXX: Related decision]
* [ADR-YYY: Another related decision]
## References
* [Link to relevant documentation]
* [Link to relevant discussion]
* [Link to relevant RFC or proposal]Example ADR
# ADR-001: Use Event Sourcing for Order Management
## Status
Accepted
## Date
2024-03-15
## Context
Our current order management system stores only the current state of orders
in a relational database. This creates several problems:
- We cannot audit the history of order changes
- Investigating customer complaints requires searching through logs
- Calculating historical reports requires complex queries
- Data inconsistencies between services are difficult to debug
The business requires complete audit trails for compliance and has requested
the ability to "replay" order history for analysis.
## Decision Drivers
* Must maintain complete audit trail of all order changes
* Need to support temporal queries ("What was the order state at time T?")
* System must handle 50,000 orders per day
* Team has moderate experience with event-driven architectures
* Must integrate with existing inventory and shipping systems
## Considered Options
### Option 1: Event Sourcing with Apache Kafka
Use event sourcing pattern with Kafka as the event store.
**Pros:**
* Complete audit trail built in
* Natural fit for temporal queries
* Kafka provides high throughput and durability
* Enables CQRS pattern for read optimization
**Cons:**
* Significant learning curve for team
* Requires new infrastructure (Kafka cluster)
* Event schema evolution requires careful management
* Eventually consistent reads
### Option 2: Database Audit Tables
Add audit tables that log all changes to order records.
**Pros:**
* Simpler to implement
* Uses existing database infrastructure
* Team already familiar with pattern
* Immediate consistency
**Cons:**
* Audit tables can grow very large
* Historical queries still complex
* Not designed for replay scenarios
* Audit logic scattered across codebase
### Option 3: Change Data Capture (CDC)
Use CDC tools to capture database changes to a separate store.
**Pros:**
* No application code changes for capture
* Works with existing database
* Can stream to various destinations
**Cons:**
* Physical vs logical changes (internal DB changes captured)
* Limited semantic meaning of events
* Additional infrastructure (Debezium, etc.)
* Doesn't enable true event sourcing benefits
## Decision
We will implement event sourcing with Apache Kafka for the order
management domain.
## Rationale
Event sourcing with Kafka best addresses our core requirements:
1. **Audit trail**: Events are the source of truth, providing complete history
2. **Temporal queries**: Can rebuild state at any point in time
3. **Scale**: Kafka can easily handle our throughput requirements
4. **Integration**: Event-driven architecture simplifies integration with
inventory and shipping systems
While the learning curve is higher, the long-term benefits outweigh the
short-term investment. We will mitigate risks through:
- Training for the team before implementation
- Starting with order management only (bounded scope)
- Maintaining a read model for common queries
## Consequences
### Positive
* Complete audit trail for all order changes
* Can answer "what was the state at time X" queries
* Simplified integration with downstream systems via events
* Foundation for future event-driven capabilities
### Negative
* Team needs training on event sourcing patterns
* Need to manage Kafka infrastructure
* Must design and evolve event schemas carefully
* Read-after-write consistency requires careful handling
### Neutral
* Will need to build projections for common query patterns
* Existing systems will continue as-is; new pattern for orders only
## Related Decisions
* ADR-002: Event Schema Versioning Strategy
* ADR-003: CQRS Read Model Implementation
## References
* [Event Sourcing Pattern - Microsoft](https://docs.microsoft.com/en-us/azure/architecture/patterns/event-sourcing)
* [Kafka Architecture](https://kafka.apache.org/documentation/#design)
* Internal RFC: Order Management ModernizationBest Practices
When to Write an ADR
Write an ADR when:
- The decision affects system structure significantly
- The decision is difficult to reverse
- Multiple valid options exist
- Team members have differing opinions
- Future team members would ask “why did we do this?”
Keeping ADRs Useful
Do:
- Keep them short and focused
- Write them at decision time (not after)
- Include the options you rejected
- Update status when decisions change
- Store them with the code they describe
Don’t:
- Write ADRs for trivial decisions
- Use them as detailed design documents
- Let them become stale
- Skip the consequences section
Organizing ADRs
File Naming:
docs/decisions/
0001-use-postgresql-for-primary-database.md
0002-implement-event-sourcing-for-orders.md
0003-adopt-kubernetes-for-deployment.mdIndex Document:
# Architecture Decision Records
| ADR | Title | Status | Date |
|-----|-------|--------|------|
| 001 | Use PostgreSQL | Accepted | 2024-01-15 |
| 002 | Event Sourcing for Orders | Accepted | 2024-03-15 |
| 003 | Kubernetes Deployment | Proposed | 2024-04-01 |Tools
- adr-tools: Command-line tools for managing ADRs
- Log4brains: ADR management with web UI
- Markdown in Git: Simple, version-controlled ADRs
For architecture review or decision-making support, contact our team.
