microservices-patterns

Microservices decomposition can be achieved using business capability and subdomain-based strategies to define service boundaries. This approach breaks down monolithic applications into smaller, independent services aligned with specific business functions.

The Saga pattern is a sequence of local transactions where each transaction updates data within a single microservice. It ensures data consistency across distributed services by automatically rolling back previous operations if a step fails.

Resilience in distributed systems is built by applying patterns like Circuit Breakers, Retries, and Bulkheads. These strategies prevent cascading failures and ensure the system remains partially operational during partial outages.

Event-driven microservices rely on asynchronous communication patterns, alongside synchronous options like REST and gRPC. Choosing the right pattern depends on whether services need immediate responses or can react to domain events independently.

A database per service is a common data management pattern in microservices to ensure loose coupling. It allows each service to manage its own data independently, though it introduces challenges requiring distributed transaction solutions like the Saga pattern.

Microservices architectures introduce significant complexity in distributed data management and communication. You should avoid this approach if your application domain is too small to justify the operational overhead of service decomposition and fault tolerance strategies.