REL03-BP02: Build services focused on specific business domains and functionality

Overview

Design services around specific business domains and functionality using domain-driven design principles to create well-bounded, cohesive services that align with business capabilities. This approach ensures services have clear ownership, single responsibility, and minimal coupling while maximizing cohesion within business domain boundaries, leading to more maintainable, scalable, and reliable architectures.

Implementation Steps

1. Conduct Domain-Driven Design Analysis

Identify core business domains and subdomains within your organization
Map business capabilities and processes to potential service boundaries
Engage domain experts and stakeholders to understand business context
Define ubiquitous language for each domain to ensure clear communication

2. Define Bounded Contexts and Service Boundaries

Establish clear boundaries between different business domains
Identify entities, value objects, and aggregates within each domain
Define domain services and their responsibilities
Ensure each service owns its data and business logic

3. Design Domain-Specific APIs and Interfaces

Create APIs that reflect business operations and workflows
Design interfaces using domain-specific terminology and concepts
Implement proper abstraction layers to hide implementation details
Establish clear input/output contracts for each service

4. Implement Service Ownership and Governance

Assign clear ownership of each service to specific teams
Establish service-level objectives (SLOs) and key performance indicators
Implement governance processes for service evolution and changes
Create documentation and knowledge sharing practices

5. Establish Inter-Service Communication Patterns

Design communication patterns that respect domain boundaries
Implement event-driven architectures for loose coupling
Use domain events to communicate business state changes
Avoid chatty interfaces and minimize cross-domain dependencies

6. Implement Domain-Specific Data Management

Design data models that reflect business domain concepts
Implement appropriate data consistency patterns for each domain
Establish data ownership and access patterns
Consider event sourcing and CQRS patterns where appropriate
Implementation Examples

Example 1: Domain-Driven Service Design and Implementation Engine

Example 2: Domain-Driven Service Implementation Script

AWS Services Used

AWS Lambda: Serverless functions for implementing domain services with clear business boundaries
Amazon DynamoDB: NoSQL database for domain entity storage with single-table design per domain
Amazon EventBridge: Event-driven communication for publishing domain events across bounded contexts
Amazon API Gateway: RESTful APIs that reflect business operations and domain terminology
AWS Step Functions: Workflow orchestration for complex business processes within domains
Amazon SQS: Message queuing for asynchronous communication between domain services
Amazon SNS: Publish-subscribe messaging for domain event distribution
AWS CloudFormation: Infrastructure as code for consistent domain service deployment
Amazon CloudWatch: Monitoring and logging for domain service observability
AWS X-Ray: Distributed tracing for understanding cross-domain service interactions
AWS CodePipeline: CI/CD pipelines for independent domain service deployments
AWS Systems Manager: Parameter store for domain-specific configuration management
Amazon Cognito: Authentication and authorization aligned with business domain access patterns
AWS AppSync: GraphQL APIs for complex domain queries and real-time subscriptions
Amazon ElastiCache: Caching layer for domain-specific data access patterns
AWS Secrets Manager: Secure storage of domain service credentials and API keys

Benefits

Clear Business Alignment: Services directly map to business capabilities and domain expertise
Improved Maintainability: Well-defined boundaries reduce complexity and improve code organization
Enhanced Team Ownership: Clear service ownership aligned with business domain expertise
Better Scalability: Independent scaling based on domain-specific load patterns
Reduced Coupling: Loose coupling between domains through well-defined interfaces
Faster Development: Domain experts can work independently within their bounded contexts
Improved Testing: Domain-focused testing strategies with clear business scenarios
Better Communication: Ubiquitous language improves communication between technical and business teams
Easier Evolution: Services can evolve independently based on business domain changes
Enhanced Reliability: Fault isolation prevents failures from cascading across business domains