Saga Pattern: Managing Distributed Transactions in Microservices

Saga Pattern: Distributed Transactions in Microservices

When a customer places an order in a microservices system, you need to:

1. Reserve payment
2. Update inventory
3. Schedule shipment
4. Send confirmation

In a monolith, you'd use a database transaction: all-or-nothing.

In microservices, each step is a separate service. The Saga pattern orchestrates these steps, with compensating transactions that undo previous steps if later ones fail.

Two Patterns

Orchestration

A saga orchestrator directs each service in sequence.

• Pros: Centralized control, easy to understand
• Cons: Tight coupling, orchestrator is bottleneck

Choreography

Services communicate through events.

• Pros: Loose coupling, scales well
• Cons: Hard to debug, complex error handling

Key Principles

• ✅ Compensating Transactions: Undo steps in reverse order
• ✅ Idempotency: Same request = same result
• ✅ Eventual Consistency: Not all steps succeed immediately
• ✅ Failure Handling: Plan for compensation failures

Implementation

Orchestration (Java)

@Service
public class OrderSagaOrchestrator {
  public void execute(OrderCommand cmd) {
    try {
      paymentService.reserve(cmd);
      inventoryService.reserve(cmd);
      shipmentService.schedule(cmd);
      emailService.send(cmd);
    } catch (Exception e) {
      // Compensate in reverse
      shipmentService.cancel(cmd);
      inventoryService.release(cmd);
      paymentService.refund(cmd);
    }
  }
}

Choreography (Kafka)

Services listen to events and publish new events:

• Order Service publishes OrderCreated
• Payment Service listens, reserves payment, publishes PaymentReserved
• Inventory Service listens, reserves stock, publishes InventoryReserved
• Shipment Service listens, schedules shipment

If any step fails, compensating events trigger rollbacks.

Tools

• Axon Framework (event sourcing + sagas)
• Apache Camel (choreography)
• Temporal (workflow engine)
• AWS Step Functions (serverless)

Best Practices

1. Define compensations first - Know how to undo each step
2. Ensure idempotency - Retries must be safe
3. Monitor end-to-end - Track saga execution and failures
4. Test failure scenarios - What if step 3 fails?
5. Handle compensation failures - What if compensation fails?

Read the full article for real-world examples (airline bookings), failure scenarios, and distributed tracing patterns.