Event-Driven Architecture Patterns
Designing loosely coupled systems using event-driven patterns for scalability and resilience.
Event-driven architecture enables building systems where components communicate through events, leading to loose coupling, scalability, and resilience.
Event sourcing stores state as a sequence of events rather than current state. This provides a complete audit trail and enables temporal queries and debugging.
CQRS (Command Query Responsibility Segregation) separates read and write models. This optimises each for its specific purpose and pairs well with event sourcing.
Message brokers like Kafka, RabbitMQ, and AWS SQS provide the infrastructure for event distribution. Choose based on your requirements for ordering, durability, and throughput.
Eventual consistency is inherent in event-driven systems. Design for this reality with idempotent consumers, compensation logic, and appropriate user experience patterns.
Schema management is critical as systems evolve. Use schema registries and backward-compatible changes to prevent breaking consumers.
Observability in event-driven systems requires tracing events through the system. Correlation IDs and distributed tracing help maintain visibility.
Start with simple patterns and add complexity as needed. Many benefits of event-driven architecture come from basic pub/sub patterns without full event sourcing.
