microservices-patterns

Service decomposition organizes services by business capability or DDD bounded context, enabling independent deployability and single responsibility. Start by identifying domain boundaries, then split functionality—for example, separating user, order, and inventory services with their own data stores and APIs.

Microservices support both synchronous (REST, gRPC) and asynchronous (event-driven) communication. Choose synchronous for request-response flows and asynchronous for loose coupling and resilience. API gateways route client requests; service meshes handle inter-service networking and observability.

Decentralized data management assigns each service its own data store, preventing shared databases. Polyglot persistence allows different databases per service based on their needs. Services exchange data through APIs or events, not direct database access.

A service mesh handles cross-cutting concerns like load balancing, circuit breaking, and observability without code changes. Use it for resilience at scale, when managing many inter-service connections, or when you need centralized traffic control and failure handling.

No. Microservices work with synchronous APIs alone, but event-driven patterns enable better resilience and loose coupling. Events suit use cases like order processing pipelines or multi-service workflows where asynchronous updates improve fault tolerance.