Event Sourcing in Go: From Zero to Production
5 days ago
- #cqrs
- #go
- #event-sourcing
- Event sourcing provides a complete audit trail and time-travel debugging capabilities.
- CQRS enables independent scaling of reads and writes.
- Snapshots are essential for performance with large event streams.
- Proper event versioning and migration strategies prevent production disasters.
- Event streaming with Kafka enables real-time projections and system integration.
- Event sourcing stores state changes as immutable events, providing natural audit logging.
- Production event stores need to handle millions of events efficiently with proper indexing and partitioning.
- Aggregate Root Pattern ensures consistency by managing events within a boundary.
- CQRS introduces eventual consistency between write and read models.
- Snapshots optimize performance by reducing the need to replay all events.
- Event streaming with Kafka supports real-time system integration.
- Temporal queries allow retrieving state at specific points in time.
- Saga Pattern manages distributed transactions across services.
- Security considerations include event encryption and access control.
- Comprehensive testing strategy covers event store, aggregates, projections, and integration.
- Production monitoring includes metrics, health checks, and lag monitoring.
- Performance optimizations include batch writes, parallel projections, and caching.
- Migration from traditional systems involves generating events from existing state.
- Event sourcing increases storage costs but provides transformative benefits for audit-heavy domains.