event-driven-patterns

The event-driven outbox pattern solves this by writing events to an outbox table within the same database transaction as your domain state changes. A separate process then reliably publishes those events to Kafka, ensuring atomic state transitions and reliable messaging.

The best way to handle a dead-letter queue is to define DLQ policies for poison pills and establish compensating transactions for failed state transitions. This operational guidance ensures observable behavior and prevents message processing bottlenecks.

The outbox pattern works by storing domain events in a dedicated database table alongside state transitions before asynchronously publishing them to Kafka. This guarantees reliable event delivery without dual-write consistency issues in event-driven systems.

Yes, you can use event-driven patterns to achieve eventual consistency across microservices by leveraging asynchronous messaging, idempotent consumers, and versioned event schemas. These strategies coordinate state transitions and ensure reliable system integration.

You need compensating transactions in event-driven systems when a downstream service fails to process a domain event, requiring a rollback of previous state transitions. They maintain eventual consistency by reversing completed operations within asynchronous messaging flows.