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◈ Agents & Manager/2026-03-24Advanced

Antigravity × Event-Driven Architecture: Building Reactive Microservices with AI Agents

Learn how to combine Antigravity AI agents with Event-Driven Architecture to design and implement loosely coupled, scalable reactive microservices using CQRS, Saga, and Event Sourcing patterns.

antigravity⁴⁰² event-driven microservices³ architecture¹⁷ agents¹¹¹ reactive CQRS saga

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Why Event-Driven Architecture Matters Now More Than Ever

As modern applications grow in complexity, synchronous API calls between services create bottlenecks that limit scalability and resilience. Event-Driven Architecture (EDA) addresses this by connecting services through asynchronous events, resulting in loosely coupled systems that can scale independently and recover gracefully from failures.

Antigravity's AI agents are remarkably effective at helping you design and implement these architectural patterns. In this guide, we'll walk through the core concepts of EDA and progressively build out advanced patterns — CQRS, Saga, and Event Sourcing — using Antigravity to accelerate the process.

What you'll learn:

Core concepts and design principles of Event-Driven Architecture
How to build a type-safe event bus with Antigravity agents
Implementing CQRS (Command Query Responsibility Segregation) in practice
Managing distributed transactions with the Saga pattern
Event Sourcing and snapshot techniques for audit trails and time-travel debugging

Target audience: Mid-to-senior engineers with microservices experience who want to master advanced architectural patterns.

The Fundamentals of Event-Driven Architecture

What Exactly Is an Event?

In EDA, an "event" is a record of something that happened — an immutable fact. By convention, events are named in the past tense: OrderPlaced, PaymentProcessed, InventoryUpdated.

There are three fundamental event types:

Domain Events: Business logic state changes (e.g., OrderShipped)
Integration Events: Shared between services for cross-boundary communication (e.g., UserRegistered)
System Events: Infrastructure-level notifications (e.g., ServiceHealthChanged)

Three Core EDA Patterns

Pattern	Purpose	Characteristics
Event Notification	Signal state changes	Lightweight, carries minimal information
Event-Carried State Transfer	Data synchronization	Events carry the complete state
Event Sourcing	State reconstruction	All events are persisted; any point-in-time state can be rebuilt

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WHAT YOU'LL LEARN

✦Event-driven microservices architecture design patterns powered by AI agents

✦Message queuing, event sourcing, and reactive data flow implementation

✦Production patterns for asynchronous coordination and distributed transaction management

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Building a Type-Safe Event Bus with Antigravity

Let's use Antigravity's agent to scaffold a Node.js + TypeScript event bus. Here's a typical implementation the agent generates:

// src/events/event-bus.ts
// Generated by asking the Antigravity agent: "Build a type-safe event bus"
 
import { EventEmitter } from "events";
 
// Event type definitions
interface EventMap {
  "order.placed": { orderId: string; userId: string; items: OrderItem[]; total: number };
  "payment.processed": { orderId: string; transactionId: string; status: "success" | "failed" };
  "inventory.reserved": { orderId: string; items: ReservedItem[] };
  "order.shipped": { orderId: string; trackingNumber: string };
}
 
interface OrderItem {
  productId: string;
  quantity: number;
  price: number;
}
 
interface ReservedItem {
  productId: string;
  quantity: number;
  warehouseId: string;
}
 
// Type-safe event bus class
class TypedEventBus {
  private emitter = new EventEmitter();
  private handlers = new Map<string, Set<Function>>();
 
  // Emit events with full type safety
  emit<K extends keyof EventMap>(event: K, payload: EventMap[K]): void {
    const envelope = {
      type: event,
      payload,
      timestamp: new Date().toISOString(),
      correlationId: crypto.randomUUID(),
    };
 
    console.log(`[EventBus] Emitting: ${event}`, envelope.correlationId);
    this.emitter.emit(event, envelope);
  }
 
  // Subscribe to events with full type safety
  on<K extends keyof EventMap>(
    event: K,
    handler: (payload: EventMap[K], metadata: EventMetadata) => Promise<void>
  ): () => void {
    const wrappedHandler = async (envelope: EventEnvelope<EventMap[K]>) => {
      try {
        await handler(envelope.payload, {
          timestamp: envelope.timestamp,
          correlationId: envelope.correlationId,
        });
      } catch (error) {
        console.error(`[EventBus] Handler error for ${event}:`, error);
      }
    };
 
    this.emitter.on(event, wrappedHandler);
 
    // Return a cleanup function
    return () => this.emitter.off(event, wrappedHandler);
  }
}
 
interface EventMetadata {
  timestamp: string;
  correlationId: string;
}
 
interface EventEnvelope<T> {
  type: string;
  payload: T;
  timestamp: string;
  correlationId: string;
}
 
export const eventBus = new TypedEventBus();

Here's an example prompt to generate this with the agent:

Build a type-safe event bus in TypeScript.
Requirements:
- EventEmitter-based, lightweight
- Use generics for type safety
- Track event chains with correlationId
- Built-in error handling
- Return cleanup functions from subscriptions

Implementing the CQRS Pattern

CQRS (Command Query Responsibility Segregation) separates your data model into a write side (Commands) and a read side (Queries). It pairs beautifully with EDA — the write side emits events that project into optimized read views.

The Command Side

// src/commands/place-order.command.ts
// Order command handler — the write model
 
import { eventBus } from "../events/event-bus";
 
interface PlaceOrderCommand {
  userId: string;
  items: Array<{ productId: string; quantity: number; price: number }>;
}
 
class OrderCommandHandler {
  async execute(command: PlaceOrderCommand): Promise<string> {
    // 1. Validation
    if (command.items.length === 0) {
      throw new Error("An order must contain at least one item");
    }
 
    // 2. Create the aggregate
    const orderId = crypto.randomUUID();
    const total = command.items.reduce(
      (sum, item) => sum + item.price * item.quantity,
      0
    );
 
    // 3. Persist to the write model
    await this.saveOrder({
      id: orderId,
      userId: command.userId,
      items: command.items,
      total,
      status: "pending",
      createdAt: new Date(),
    });
 
    // 4. Emit the domain event
    eventBus.emit("order.placed", {
      orderId,
      userId: command.userId,
      items: command.items,
      total,
    });
 
    return orderId;
  }
 
  private async saveOrder(order: Record<string, unknown>): Promise<void> {
    // Database persistence logic
    console.log(`[OrderCommand] Order saved: ${order.id}`);
  }
}
 
export const orderCommandHandler = new OrderCommandHandler();

The Query Side

// src/queries/order-view.query.ts
// Order query handler — the read model (denormalized views)
 
import { eventBus } from "../events/event-bus";
 
interface OrderView {
  orderId: string;
  userId: string;
  itemCount: number;
  total: number;
  status: string;
  lastUpdated: string;
}
 
class OrderQueryHandler {
  // Denormalized view store (Redis/DynamoDB in production)
  private views = new Map<string, OrderView>();
 
  constructor() {
    // Subscribe to events and update views
    eventBus.on("order.placed", async (payload) => {
      this.views.set(payload.orderId, {
        orderId: payload.orderId,
        userId: payload.userId,
        itemCount: payload.items.length,
        total: payload.total,
        status: "pending",
        lastUpdated: new Date().toISOString(),
      });
    });
 
    eventBus.on("payment.processed", async (payload) => {
      const view = this.views.get(payload.orderId);
      if (view) {
        view.status = payload.status === "success" ? "paid" : "payment_failed";
        view.lastUpdated = new Date().toISOString();
      }
    });
 
    eventBus.on("order.shipped", async (payload) => {
      const view = this.views.get(payload.orderId);
      if (view) {
        view.status = "shipped";
        view.lastUpdated = new Date().toISOString();
      }
    });
  }
 
  // Fast read queries
  getOrder(orderId: string): OrderView | undefined {
    return this.views.get(orderId);
  }
 
  getOrdersByUser(userId: string): OrderView[] {
    return Array.from(this.views.values()).filter(
      (v) => v.userId === userId
    );
  }
}
 
export const orderQueryHandler = new OrderQueryHandler();

Expected behavior:

[OrderCommand] Order saved: abc-123
[EventBus] Emitting: order.placed abc-123
[QueryHandler] View updated: abc-123 → status: pending
[EventBus] Emitting: payment.processed abc-123
[QueryHandler] View updated: abc-123 → status: paid

The power of CQRS lies in optimizing your read models for each use case. You can build separate views for dashboards, search indexes, and analytics — all from the same event stream.

Distributed Transaction Management with the Saga Pattern

In a microservices world, you can't rely on database-level ACID transactions across service boundaries. The Saga pattern solves this by defining a sequence of local transactions paired with compensating (rollback) actions, guaranteeing eventual consistency.

// src/sagas/order-saga.ts
// Order processing saga — orchestration approach
 
import { eventBus } from "../events/event-bus";
 
interface SagaStep {
  name: string;
  execute: () => Promise<void>;
  compensate: () => Promise<void>;
}
 
class OrderSaga {
  private completedSteps: SagaStep[] = [];
 
  async execute(orderId: string, userId: string): Promise<void> {
    const steps: SagaStep[] = [
      {
        name: "Reserve Inventory",
        execute: async () => {
          await this.reserveInventory(orderId);
          console.log(`[Saga] ✅ Inventory reserved: ${orderId}`);
        },
        compensate: async () => {
          await this.releaseInventory(orderId);
          console.log(`[Saga] ↩️ Inventory released: ${orderId}`);
        },
      },
      {
        name: "Process Payment",
        execute: async () => {
          await this.processPayment(orderId, userId);
          console.log(`[Saga] ✅ Payment processed: ${orderId}`);
        },
        compensate: async () => {
          await this.refundPayment(orderId);
          console.log(`[Saga] ↩️ Payment refunded: ${orderId}`);
        },
      },
      {
        name: "Arrange Shipping",
        execute: async () => {
          await this.arrangeShipping(orderId);
          console.log(`[Saga] ✅ Shipping arranged: ${orderId}`);
        },
        compensate: async () => {
          await this.cancelShipping(orderId);
          console.log(`[Saga] ↩️ Shipping cancelled: ${orderId}`);
        },
      },
    ];
 
    // Execute steps in order; on failure, compensate in reverse
    for (const step of steps) {
      try {
        await step.execute();
        this.completedSteps.push(step);
      } catch (error) {
        console.error(`[Saga] ❌ ${step.name} failed:`, error);
        await this.rollback();
        throw new Error(`Saga failed at step: ${step.name}`);
      }
    }
 
    console.log(`[Saga] 🎉 Order processing complete: ${orderId}`);
  }
 
  private async rollback(): Promise<void> {
    console.log("[Saga] Starting rollback...");
    for (const step of [...this.completedSteps].reverse()) {
      try {
        await step.compensate();
      } catch (compensateError) {
        // Log compensation failures and continue (requires manual intervention)
        console.error(
          `[Saga] Compensation failed (${step.name}):`,
          compensateError
        );
      }
    }
  }
 
  private async reserveInventory(orderId: string): Promise<void> {
    eventBus.emit("inventory.reserved", {
      orderId,
      items: [{ productId: "prod-1", quantity: 1, warehouseId: "wh-tokyo" }],
    });
  }
 
  private async releaseInventory(orderId: string): Promise<void> {
    // Release inventory API call
  }
 
  private async processPayment(orderId: string, userId: string): Promise<void> {
    eventBus.emit("payment.processed", {
      orderId,
      transactionId: crypto.randomUUID(),
      status: "success",
    });
  }
 
  private async refundPayment(orderId: string): Promise<void> {
    // Refund processing
  }
 
  private async arrangeShipping(orderId: string): Promise<void> {
    eventBus.emit("order.shipped", {
      orderId,
      trackingNumber: `TRK-${Date.now()}`,
    });
  }
 
  private async cancelShipping(orderId: string): Promise<void> {
    // Cancel shipping
  }
}
 
export { OrderSaga };

Expected output (happy path):

[Saga] ✅ Inventory reserved: order-789
[Saga] ✅ Payment processed: order-789
[Saga] ✅ Shipping arranged: order-789
[Saga] 🎉 Order processing complete: order-789

Expected output (payment failure with rollback):

[Saga] ✅ Inventory reserved: order-789
[Saga] ❌ Process Payment failed: PaymentDeclinedError
[Saga] Starting rollback...
[Saga] ↩️ Inventory released: order-789

Event Sourcing and Snapshots

Event Sourcing flips the traditional persistence model on its head. Instead of storing the current state of an entity, you store every state change as an immutable event. This gives you a complete audit trail and the ability to reconstruct state at any point in time.

// src/event-sourcing/event-store.ts
// The Event Store — the heart of Event Sourcing
 
interface StoredEvent {
  id: string;
  aggregateId: string;
  type: string;
  payload: Record<string, unknown>;
  version: number;
  timestamp: string;
}
 
class EventStore {
  private events: StoredEvent[] = [];
  private snapshots = new Map<string, { state: unknown; version: number }>();
 
  // Append-only event storage
  async append(
    aggregateId: string,
    type: string,
    payload: Record<string, unknown>,
    expectedVersion: number
  ): Promise<void> {
    const currentVersion = this.getLatestVersion(aggregateId);
 
    // Optimistic concurrency control
    if (currentVersion !== expectedVersion) {
      throw new Error(
        `Concurrency conflict: expected v${expectedVersion}, got v${currentVersion}`
      );
    }
 
    this.events.push({
      id: crypto.randomUUID(),
      aggregateId,
      type,
      payload,
      version: expectedVersion + 1,
      timestamp: new Date().toISOString(),
    });
  }
 
  // Retrieve event history for an aggregate
  getEvents(aggregateId: string, fromVersion = 0): StoredEvent[] {
    return this.events.filter(
      (e) => e.aggregateId === aggregateId && e.version > fromVersion
    );
  }
 
  // Save snapshots for performance optimization
  saveSnapshot(aggregateId: string, state: unknown, version: number): void {
    this.snapshots.set(aggregateId, { state, version });
    console.log(
      `[EventStore] Snapshot saved: ${aggregateId} at v${version}`
    );
  }
 
  // Restore from snapshot + replay subsequent events
  getSnapshot(
    aggregateId: string
  ): { state: unknown; version: number } | undefined {
    return this.snapshots.get(aggregateId);
  }
 
  private getLatestVersion(aggregateId: string): number {
    const events = this.events.filter(
      (e) => e.aggregateId === aggregateId
    );
    return events.length > 0
      ? Math.max(...events.map((e) => e.version))
      : 0;
  }
}
 
// Rebuilding aggregate state from events
class OrderAggregate {
  private state = { status: "created", items: [] as string[], total: 0 };
  private version = 0;
 
  // Apply an event to update state
  apply(event: StoredEvent): void {
    switch (event.type) {
      case "OrderCreated":
        this.state.status = "created";
        break;
      case "ItemAdded":
        this.state.items.push(event.payload.productId as string);
        this.state.total += event.payload.price as number;
        break;
      case "OrderConfirmed":
        this.state.status = "confirmed";
        break;
      case "OrderCancelled":
        this.state.status = "cancelled";
        break;
    }
    this.version = event.version;
  }
 
  // Fast restore from snapshot + remaining events
  static restore(
    snapshot: { state: unknown; version: number } | undefined,
    events: StoredEvent[]
  ): OrderAggregate {
    const aggregate = new OrderAggregate();
 
    if (snapshot) {
      aggregate.state = snapshot.state as typeof aggregate.state;
      aggregate.version = snapshot.version;
    }
 
    for (const event of events) {
      aggregate.apply(event);
    }
 
    return aggregate;
  }
 
  getState() {
    return { ...this.state, version: this.version };
  }
}
 
export { EventStore, OrderAggregate };

Common Pitfalls and How to Handle Them

Guaranteeing Event Order

In distributed systems, events may arrive out of order. Use partition keys (such as order IDs) to ensure events for the same aggregate are processed sequentially. Most message brokers like Kafka and AWS SQS FIFO support this natively.

Ensuring Idempotency

Network failures can cause duplicate event delivery. Design every handler to be idempotent:

// Example of an idempotent event handler
const processedEvents = new Set<string>();
 
async function idempotentHandler(eventId: string, handler: () => Promise<void>) {
  if (processedEvents.has(eventId)) {
    console.log(`[Idempotent] Skipping duplicate: ${eventId}`);
    return; // Skip duplicate events
  }
  await handler();
  processedEvents.add(eventId);
}

Dealing with Schema Evolution

Event schemas evolve as your system grows. Use versioning strategies — either suffix events with v1, v2, or implement upcasters (functions that transform older event versions into newer ones) to maintain backward compatibility.

Wrapping Up and Next Steps

Event-Driven Architecture provides a powerful foundation for building loosely coupled, scalable, and resilient microservices. By separating reads from writes with CQRS, managing distributed transactions with Sagas, and maintaining complete history through Event Sourcing, you can architect production-grade systems that handle real-world complexity.

Antigravity's AI agents dramatically accelerate this work by generating boilerplate code for these patterns, letting you focus on the business logic that matters. Start small with a basic event bus, then progressively introduce CQRS and Saga patterns as your system's needs grow.

To continue your deep dive, check out advanced multi-agent orchestration and building WebSocket real-time apps.

Thank You for Reading

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