I’ve been working with distributed systems for over a decade, and I keep seeing teams struggle with the same challenges. How do you build systems that scale gracefully? How do you maintain data consistency across services? Why do so many architectures become brittle over time? These questions led me to explore event-driven architecture, and today I want to share a practical approach using Node.js, EventStore, and Docker.

Event sourcing fundamentally changed how I think about application state. Instead of storing current state, we persist every change as an immutable event. This creates a complete history of everything that’s happened in your system. Have you ever needed to understand why a particular decision was made months ago? With event sourcing, you can reconstruct the exact state at any point in time.

Let me show you how to set up the foundation. We’ll use Docker to containerize our services and EventStore as our event database. Here’s a basic docker-compose configuration to get started:

services:
  eventstore:
    image: eventstore/eventstore:21.10.0-buster-slim
    environment:
      - EVENTSTORE_INSECURE=true
    ports:
      - "1113:1113"
      - "2113:2113"

  redis:
    image: redis:7-alpine
    ports:
      - "6379:6379"

Now, let’s create our core event infrastructure in Node.js. I’ve found that starting with a solid base event class pays dividends later. Here’s how I typically structure it:

class DomainEvent {
  constructor(aggregateId, eventType, eventData) {
    this.id = uuidv4();
    this.aggregateId = aggregateId;
    this.eventType = eventType;
    this.eventData = eventData;
    this.occurredAt = new Date();
  }
}

But what happens when your business logic evolves and you need to change event structure? This is where event versioning becomes crucial. I’ve learned the hard way that careful planning here prevents major headaches down the road.

Let’s implement a user registration flow to demonstrate the pattern. Notice how we separate commands from queries – this is CQRS in action:

class RegisterUserCommand {
  constructor(email, password) {
    this.email = email;
    this.password = password;
  }
}

class UserRegisteredEvent extends DomainEvent {
  constructor(userId, email) {
    super(userId, 'UserRegistered', { email });
  }
}

When building microservices, how do you ensure they communicate effectively without creating tight coupling? Events provide the answer. Each service publishes events and reacts to events from other services, maintaining loose coupling while enabling complex workflows.

Here’s how I handle projections to build read models:

class UserProjection {
  constructor(eventStore) {
    this.eventStore = eventStore;
    this.users = new Map();
  }

  async projectUserEvents(userId) {
    const events = await this.eventStore.getEvents(userId);
    events.forEach(event => {
      if (event.eventType === 'UserRegistered') {
        this.users.set(userId, { email: event.eventData.email });
      }
    });
  }
}

Monitoring distributed systems requires a different approach. I instrument key points in the event flow to track performance and errors. Have you considered how you’ll trace a request across multiple services? Correlation IDs in events make this manageable.

Testing event-driven systems presents unique challenges. I focus on testing event handlers in isolation and verifying the overall system behavior through integration tests. Mocking the event store helps keep tests fast and reliable.

Deployment strategies matter too. I use Docker to package each service independently, allowing for gradual rollouts and easy scaling. Environment-specific configuration ensures smooth transitions between development, staging, and production.

Building this architecture has transformed how I approach system design. The audit trail alone provides immense value for debugging and compliance. But the real power comes from the flexibility to add new features by simply creating new projections.

What surprised me most was how event sourcing simplifies complex business processes. By breaking down operations into discrete events, you gain clarity and control that’s hard to achieve with traditional approaches.

I’d love to hear about your experiences with event-driven systems. Have you implemented similar patterns? What challenges did you face? If this article helped you understand these concepts better, please share it with your team and leave a comment below – your feedback helps me create more valuable content.