distributed-events-advanced

Distributed events enable loosely coupled microservices to communicate reliably. Design event publishers and consumers using a message broker like RabbitMQ, define Event Transfer Objects for payloads, implement IDistributedEventHandler patterns, and enforce idempotency through a processed-event store to prevent duplicate processing across services.

Saga pattern orchestrates long-running transactions across services with explicit compensating actions for rollback, ensuring eventual consistency. Choreography uses events to trigger service actions without central orchestration. The Saga pattern suits complex workflows; choreography works better for simple event chains.

The Outbox pattern writes domain events and business data in a single database transaction, then publishes events from the outbox to the message broker. This guarantees events are never lost due to publishing failures and maintains consistency between your database and message flow.

Event versioning and schema evolution patterns allow you to modify event structures over time. Include version fields in Event Transfer Objects, support backward compatibility in consumers, and communicate breaking changes to dependent services to avoid system-wide failures.

Implement correlation IDs in your event metadata to track requests across service boundaries and enable cross-tenant data isolation. Log and propagate correlation IDs through each event handler to create an audit trail for debugging and monitoring multi-tenant, event-driven systems.

A message broker is essential for reliable inter-service event delivery and decoupling. RabbitMQ and Kafka both work with distributed event patterns; choose based on throughput, persistence, and replay requirements for your microservices architecture.