Event-Driven Architecture in Production: Patterns, Pitfalls, and Best Practices

Why Event-Driven Architecture?

EDA enables loose coupling, temporal decoupling, and audit trails by default. But it also introduces complexity around ordering, consistency, and error handling.

Core Patterns

1. Event Notification

The simplest pattern: emit an event when something happens, let other services react.

await eventBus.emit("order.created", {
  orderId: order.id,
  customerId: order.customerId,
  items: order.items,
  total: order.total
});

2. Event Sourcing

Store every state change as an immutable event. The current state is derived by replaying events.

const events = [
  { type: "OrderCreated", data: { items: [...] }, timestamp: "2025-01-15T10:00:00Z" },
  { type: "PaymentReceived", data: { amount: 100 }, timestamp: "2025-01-15T10:05:00Z" },
  { type: "OrderShipped", data: { carrier: "FedEx", tracking: "123" }, timestamp: "2025-01-16T09:00:00Z" }
];

3. CQRS (Command Query Responsibility Segregation)

Separate read and write models for different performance needs. Write model optimizes for consistency, read model optimizes for query performance.

Message Broker Selection

Handling Failures

• Dead Letter Queues for messages that can't be processed
• Idempotency keys for duplicate processing
• Circuit breakers for downstream service failures
• Saga pattern for distributed transactions