I’ve been building web applications for over a decade, and recently I hit a wall with traditional request-response architectures. My systems were becoming tangled webs of dependencies where changing one part risked breaking three others. That’s when I rediscovered event-driven architecture and decided to build something truly scalable using NestJS, Redis, and MongoDB. Today, I want to show you how to create systems that can handle massive scale while remaining maintainable and resilient.

Event-driven architecture fundamentally changes how components communicate. Instead of services directly calling each other, they emit events that other services can react to. This creates loose coupling, making your system more flexible and easier to scale. Think of it like a busy restaurant kitchen - chefs don’t constantly check with waiters; they just ring a bell when orders are ready, and waiters respond accordingly.

Why did I choose this specific stack? NestJS provides a solid foundation with excellent dependency injection and modular structure. Redis offers blazing-fast pub/sub capabilities perfect for event distribution. MongoDB’s flexible document model works beautifully with event sourcing patterns. Together, they create a powerful trio for building modern applications.

Let me show you how to set up the basic infrastructure. First, we’ll create our NestJS project and dependencies:

npm i -g @nestjs/cli
nest new event-driven-app
cd event-driven-app
npm install @nestjs/mongoose mongoose @nestjs/microservices redis

Now, here’s a docker-compose.yml to run Redis and MongoDB locally:

services:
  redis:
    image: redis:7-alpine
    ports: ["6379:6379"]
  
  mongodb:
    image: mongo:6
    ports: ["27017:27017"]
    environment:
      MONGO_INITDB_DATABASE: eventstore

Have you ever wondered how to ensure events maintain their structure across different services? That’s where strong typing comes in. Let me share a base event class I’ve refined through several projects:

export abstract class BaseDomainEvent {
  public readonly eventId: string;
  public readonly occurredAt: Date;

  constructor(
    public readonly aggregateId: string,
    public readonly aggregateType: string,
    public readonly payload: Record<string, any>
  ) {
    this.eventId = uuidv4();
    this.occurredAt = new Date();
  }

  abstract get eventType(): string;
}

This base class ensures every event has essential metadata while allowing specific event types to define their own structure. Notice how we’re using UUIDs for event IDs and timestamps for ordering - these small decisions prevent big headaches later.

Now, let’s implement our Redis event bus. This is where the magic happens for distributing events across your system:

@Injectable()
export class RedisEventBus implements EventPublisher {
  private publisher: Redis.RedisClientType;
  
  async publish<T extends DomainEvent>(event: T): Promise<void> {
    const channel = `events:${event.eventType}`;
    const message = JSON.stringify(event);
    await this.publisher.publish(channel, message);
  }
}

What happens when you need to handle the same event differently across multiple services? That’s where event handlers shine. Here’s a simple order creation handler:

@Injectable()
export class OrderCreatedHandler implements EventHandler<OrderCreatedEvent> {
  constructor(private readonly emailService: EmailService) {}

  async handle(event: OrderCreatedEvent): Promise<void> {
    await this.emailService.sendOrderConfirmation(event.payload.orderId);
    await this.inventoryService.updateStock(event.payload.items);
  }
}

MongoDB integration for event sourcing is where things get really interesting. Instead of storing just current state, we store every event that changed the state. This gives us an audit trail and the ability to reconstruct state at any point in time. Here’s how I model event storage:

@Schema()
export class StoredEvent {
  @Prop({ required: true })
  eventId: string;

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

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

  @Prop({ type: Object })
  payload: Record<string, any>;
}

But what about error handling and retries? In event-driven systems, you need to plan for failures. I always implement dead letter queues for events that repeatedly fail processing. This prevents one problematic event from blocking your entire system.

Another common question: how do you test event-driven components? I’ve found that testing events in isolation then testing integration separately works best. Here’s a simple unit test for an event handler:

describe('OrderCreatedHandler', () => {
  it('should send email and update inventory', async () => {
    const handler = new OrderCreatedHandler(emailService, inventoryService);
    const event = new OrderCreatedEvent('order-123', { orderId: 'order-123' });
    
    await handler.handle(event);
    
    expect(emailService.sendOrderConfirmation).toHaveBeenCalledWith('order-123');
  });
});

As your system grows, you might encounter performance bottlenecks. One technique I’ve used successfully is event batching - grouping multiple events for more efficient processing. Also, consider using Redis clusters for higher availability and MongoDB sharding for distributing event storage load.

In production, monitoring becomes crucial. I always set up detailed logging for event flows and use metrics to track event processing times and error rates. This helps identify issues before they affect users.

Remember that event-driven architecture isn’t a silver bullet. It introduces complexity in exchange for scalability and decoupling. Start simple, understand the patterns, and gradually implement more advanced features as needed.

I’ve seen teams transform their systems using these approaches, moving from fragile monoliths to resilient, scalable architectures. The journey requires careful planning but pays dividends in maintainability and performance.

If you’re working on systems that need to handle growth while staying responsive, event-driven architecture with this stack might be your solution. What challenges are you facing with your current architecture? Share your experiences in the comments below - I’d love to hear how you’re approaching these problems. If this guide helped you, please like and share it with others who might benefit from these patterns.