🔄 Distributed Transactions Deep Dive

Welcome back to The Code Hut Distributed Systems series! In this post, we’ll dive deeper into distributed transactions, advanced Saga patterns, and techniques to maintain consistency across microservices.

Why Distributed Transactions Are Tricky

In a distributed system, each service typically manages its own database. Coordinating multiple services to commit or roll back changes atomically is challenging because:

• Network failures can occur
• Partial failures can leave inconsistent state
• Global locking is expensive and reduces availability

1. Saga Pattern Deep Dive

The Saga pattern breaks a transaction into a series of smaller, independent steps with compensating actions if something fails.

• Choreography: Services emit events that trigger the next step.
• Orchestration: A central coordinator tells each service what action to take next.

2. Example: Orchestrated Saga in Java

// Orchestrator triggers a series of service calls
public class OrderSagaOrchestrator {
    public void processOrder(Order order) {
        try {
            paymentService.charge(order);
            shippingService.reserveStock(order);
            notificationService.sendConfirmation(order);
        } catch (Exception e) {
            compensate(order);
        }
    }

    private void compensate(Order order) {
        paymentService.refund(order);
        shippingService.releaseStock(order);
    }
}

3. Event-Driven Sagas (Choreography)

Using messaging (Kafka, RabbitMQ) to trigger compensations:

// Pseudocode for event-driven saga
@KafkaListener(topics = "order-events")
public void handleOrderEvent(OrderEvent event) {
    if (event.getType() == EventType.PAYMENT_FAILED) {
        stockService.releaseStock(event.getOrderId());
    }
}

4. Best Practices

• Keep sagas small and simple
• Idempotent operations are crucial
• Monitor sagas with observability tools
• Consider compensation complexity before implementation

Next in the Series

In the next post, we’ll explore Advanced Fault Tolerance strategies including retries, circuit breakers, and recovery techniques in distributed systems.

Label for this post: Distributed Systems