microservices

Define microservice boundaries by establishing bounded contexts so each service owns its specific domain and database, reducing coupling. This domain decomposition ensures distributed components remain loosely coupled and independently scalable.

Use event-driven architecture with message buses when you need asynchronous throughput and eventual consistency, and choose synchronous REST or gRPC when immediate consistency is required. Matching communication patterns to interaction needs prevents fragile distributed systems.

Implement distributed tracing by propagating correlation IDs and applying OpenTelemetry to visualize end-to-end request flow. This trace-based monitoring tracks latency SLOs and reveals hidden bottlenecks across service boundaries.

Common microservices anti-patterns include unclear service boundaries, tightly coupled databases, and missing observability. Avoiding these prevents hard-to-debug distributed systems by enforcing bounded contexts and consistent data handling strategies.

You can plan data consistency strategies for evolving event-driven backends by defining service boundaries, selecting communication patterns, and mapping required tracing. This approach handles domain decomposition and read/write separation safely.