G1Joshi Event-Driven Architecture (EDA)
EDA is a software architecture paradigm promoting the production, detection, consumption of, and reaction to events. In 2025, it is the backbone of real-time, scalable, and decoupled systems.
When to Use
- When strict decoupling is required (Producer doesn't know Consumer).
- High-volume, bursty traffic (using buffering queues).
- Asynchronous workflows (e.g., "User Signed Up" -> Send Email, Create Wallet, Analytics).
- Real-time updates (WebSockets/Push).
Quick Start
// Producer (Order Service)
await messageBroker.publish("order.created", {
orderId: "123",
userId: "456",
timestamp: Date.now(),
});
// Consumer (Shipping Service)
// Doesn't need to be online when order is created
messageBroker.subscribe("order.created", async (event) => {
await shippingService.schedulePickup(event.orderId);
console.log("Shipping scheduled");
});
// Consumer (Analytics Service)
// New feature added later? No changes to Order Service!
messageBroker.subscribe("order.created", async (event) => {
await analytics.trackRevenue(event);
});
Core Concepts
Event
A significant change in state (Immutable fact). "OrderCreated" not "CreateOrder".
Broker (Event Bus)
The middleware (Kafka, RabbitMQ, SNS/SQS) that receives, stores, and routes events.
Pub/Sub
Pattern where publishers send messages to a topic, and multiple subscribers receive them independently.
Common Patterns
Event Sourcing
Storing the state of an entity as a sequence of state-changing events rather than the current snapshot.
CQRS (Command Query Responsibility Segregation)
Separating the Read and Write models. Writes publish events; Reads update a denormalized view based on those events.
Transactional Outbox
Ensuring data consistency. Write the event to a DB table in the same transaction as the business logic, then a background worker pushes it to the broker.
Best Practices
Do:
- Use Schemas (Avro, Protobuf, JSON Schema) to govern event structure (Schema Registry).
- Ensure Idempotency in consumers (handling the same message twice safely).
- Monitor Lag (how far behind consumers are).
Don't:
- Don't use events for synchronous queries (Request/Response via queues is painful).
- Don't put huge payloads in events (Pass ID + Metadata, reference Blob Storage if needed).
Tools
- Kafka / Redpanda: High throughput, log-based (replayable).
- RabbitMQ / ActiveMQ: Queue-based, complex routing.
- AWS SNS/SQS / Google PubSub: Cloud native.