ddd-event-driven

Domain events model business occurrences to integrate bounded contexts. They decouple microservices by capturing state changes as standalone events, allowing independent services to react asynchronously and maintain loose coupling across distributed systems.

Event sourcing persists state changes as an immutable event log, while CQRS separates read and write operations. Together they improve traceability and scalability by reconstructing state from historical events and optimizing queries against tailored read models.

Eventual consistency in event-driven systems requires reliable event delivery and error handling. You must implement retry mechanisms, idempotent processing, and compensating actions to manage distributed state while accepting temporary data divergence.

Use event-driven architecture when you need scalable, loosely coupled services across microservices. It fits scenarios requiring asynchronous processing and high throughput, rather than synchronous request-response flows demanding immediate consistency.

Event modeling best practices include defining clear event schemas, ensuring reliable delivery, and handling errors. Production environments must satisfy requirements for event versioning, idempotency, and monitoring to maintain eventual consistency.

Start implementing event sourcing by identifying a single bounded context and defining its initial domain events. Apply these events to update write models and project them into read models to establish a minimal CQRS workflow.