Event-driven architecture (EDA) enables loosely coupled, scalable systems. This guide covers core patterns, implementation strategies, and best practices.
Core Concepts#
Events vs Commands vs Queries#
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Event Flow#
┌─────────┐ Command ┌──────────┐ Event ┌──────────┐
│ Client │ ─────────────> │ Service │ ────────────> │ Queue │
└─────────┘ └──────────┘ └──────────┘
│
┌──────────────────────────────────┤
│ │ │
▼ ▼ ▼
┌──────────┐ ┌──────────┐ ┌──────────┐
│ Service │ │ Service │ │ Service │
│ A │ │ B │ │ C │
└──────────┘ └──────────┘ └──────────┘
Event Sourcing#
Store events as the source of truth:
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CQRS (Command Query Responsibility Segregation)#
Separate read and write models:
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Message Brokers#
Implementing with Redis Streams#
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Implementing with RabbitMQ#
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Saga Pattern#
Coordinate distributed transactions:
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Best Practices#
- Idempotent handlers: Events may be delivered multiple times
- Event versioning: Plan for schema evolution
- Dead letter queues: Handle poison messages
- Monitoring: Track event processing latency and failures
- Event ordering: Use partitioning for ordered processing
Conclusion#
Event-driven architecture enables scalable, loosely coupled systems. Start with simple pub/sub patterns and evolve to event sourcing and CQRS as complexity grows.