Microservices architecture decomposes applications into small, independent services communicating through APIs. This approach contrasts with monolithic architecture where applications consist of single units. Microservices enable scaling components independently, deploying changes independently, and using diverse technologies.
Service boundaries define what functionality belongs in each service. Bounded contexts from domain-driven design help identify appropriate boundaries. Well-designed boundaries enable independent development and deployment.
Communication patterns between services include synchronous REST/HTTP, asynchronous messaging, and gRPC for high-performance communication. Service discovery enables services finding other services dynamically. API gateways provide single entry points for client access.
Data consistency in microservices involves eventual consistency rather than immediate consistency. Distributed transactions are complex and should be avoided. Saga pattern enables coordinating multi-service transactions through compensation logic.
Service deployment involves containerization for consistency and isolation. Container orchestration platforms manage deployment and scaling. Blue-green deployment and canary releases enable safe updates.
Resilience patterns like circuit breakers prevent cascading failures. Timeouts prevent indefinite waiting for responses. Retry logic with exponential backoff handles transient failures. Bulkheads isolate failures to prevent spreading.
Monitoring and observability are critical with multiple services. Distributed tracing follows requests through multiple services. Centralized logging aggregates logs from multiple services. Metrics track service health and performance.
API versioning enables evolving services independently. Backward compatibility enables removing old API versions gracefully. Contract testing ensures service dependencies remain compatible.
Microservices complexity includes managing distributed state, debugging across services, and coordinating deployments. Tools and practices help manage this complexity. Standardized patterns and frameworks reduce implementation variation.
Database per service pattern enables services owning data. This pattern provides independence but complicates consistency. Data synchronization between service databases requires careful coordination.
Security in microservices involves service-to-service authentication and authorization. API keys, OAuth, or mTLS enable service authentication. Network policies restrict communication to necessary paths.
Microservices suit large, rapidly evolving applications with multiple teams. Smaller, simpler applications may not benefit from added complexity. Organizational structure should align with service boundaries (Conway's Law).
