I’ve been thinking about microservices a lot lately, especially how we can build systems that scale gracefully while remaining maintainable. The shift from monolithic architectures to distributed systems brings both opportunities and challenges. What happens when one service needs to communicate with another without creating tight coupling? How do we ensure data consistency across service boundaries?

Event-driven architecture with NestJS provides an elegant solution to these questions. By combining NestJS’s structured approach with RabbitMQ’s messaging capabilities and MongoDB’s flexibility, we can create systems that are both resilient and scalable.

Let me show you how to build a complete e-commerce platform using these technologies. We’ll start with the foundational concepts and work our way to a fully functional system.

What makes event-driven architecture so powerful in distributed systems? It’s the way services communicate through events rather than direct API calls. When a user registers, for example, the user service publishes a UserRegisteredEvent. Other services that care about new users can react accordingly without being tightly coupled to the user service.

Here’s how we define a base event class:

export abstract class BaseEvent {
  public readonly eventId: string;
  public readonly eventType: string;
  public readonly timestamp: Date;

  constructor(eventType: string) {
    this.eventId = uuidv4();
    this.eventType = eventType;
    this.timestamp = new Date();
  }
}

Each service in our architecture has a specific responsibility. The order service handles order creation and management, while the inventory service tracks stock levels. But how do these services coordinate when a customer places an order?

Instead of the order service calling the inventory service directly, it publishes an OrderCreatedEvent. The inventory service listens for this event and reserves the necessary items. This asynchronous communication prevents cascading failures and allows each service to operate independently.

Let me share a practical example of event handling:

@Controller()
export class OrderController {
  constructor(private readonly eventBus: EventBus) {}

  @Post('orders')
  async createOrder(@Body() createOrderDto: CreateOrderDto) {
    const order = await this.ordersService.create(createOrderDto);
    
    // Publish event instead of direct service calls
    await this.eventBus.publish(
      new OrderCreatedEvent(order.id, order.items)
    );
    
    return order;
  }
}

RabbitMQ acts as our message broker, ensuring reliable delivery between services. But what happens if a service goes offline temporarily? RabbitMQ’s persistence mechanisms ensure messages aren’t lost, and services can process them when they come back online.

Here’s how we set up a RabbitMQ connection in NestJS:

@Module({
  imports: [
    ClientsModule.register([
      {
        name: 'RABBITMQ_CLIENT',
        transport: Transport.RMQ,
        options: {
          urls: ['amqp://localhost:5672'],
          queue: 'orders_queue',
        },
      },
    ]),
  ],
})
export class AppModule {}

MongoDB plays a crucial role in our event sourcing pattern. Instead of storing just the current state, we store the complete history of events. This gives us an audit trail and allows us to reconstruct state at any point in time.

Consider this event store implementation:

@Entity()
export class EventStore {
  @Prop({ required: true })
  eventId: string;

  @Prop({ required: true })
  eventType: string;

  @Prop({ type: Object, required: true })
  eventData: any;

  @Prop({ required: true })
  aggregateId: string;

  @Prop({ default: Date.now })
  timestamp: Date;
}

Error handling in distributed systems requires careful consideration. What happens if the inventory service can’t reserve items after an order is created? We implement compensating actions - like publishing an OrderCancelledEvent - to maintain system consistency.

Monitoring becomes essential when working with multiple services. I’ve found that implementing structured logging and metrics collection helps tremendously when debugging issues across service boundaries:

@Injectable()
export class LoggingInterceptor implements NestInterceptor {
  intercept(context: ExecutionContext, next: CallHandler) {
    const request = context.switchToHttp().getRequest();
    console.log(`Incoming request: ${request.method} ${request.url}`);
    
    return next.handle().pipe(
      tap(() => console.log('Request completed successfully'))
    );
  }
}

Testing event-driven systems requires a different approach. We need to verify that services publish the correct events and handle incoming events properly. I typically use a combination of unit tests for business logic and integration tests for event flow.

Deployment with Docker simplifies managing our multi-service architecture. Each service runs in its own container, and docker-compose orchestrates the entire system:

version: '3.8'
services:
  order-service:
    build: ./apps/order-service
    environment:
      - RABBITMQ_URL=amqp://rabbitmq:5672
    depends_on:
      - rabbitmq

  rabbitmq:
    image: rabbitmq:3-management
    ports:
      - "5672:5672"

Building event-driven microservices requires shifting our mindset from synchronous to asynchronous communication. The initial complexity pays dividends in scalability and resilience. Services can be developed, deployed, and scaled independently, and the system as a whole becomes more robust.

Have you considered how event-driven patterns could improve your current systems? What challenges have you faced with microservice communication?

I’d love to hear about your experiences with distributed systems. If you found this article helpful, please share it with your colleagues and leave a comment below with your thoughts or questions. Your feedback helps me create better content for our developer community.