spring-boot-saga-pattern

What this skill does

# Spring Boot Saga Pattern

## Overview

Implements distributed transactions across microservices using the Saga Pattern. Replaces two-phase commit with a sequence of local transactions and compensating actions. Supports choreography (event-driven) and orchestration (centralized coordinator) approaches with Kafka, RabbitMQ, or Axon Framework.

## When to Use

- Building distributed transactions across multiple microservices
- Replacing two-phase commit (2PC) with a more scalable solution
- Handling transaction rollback when a service fails
- Ensuring eventual consistency in microservices architecture
- Implementing compensating transactions for failed operations
- Coordinating complex business processes spanning multiple services

**Trigger phrases**: distributed transactions, saga pattern, compensating transactions, microservices transaction, eventual consistency, rollback across services, orchestration pattern, choreography pattern

## Instructions

### 1. Design Transaction Flow

Map the sequence of operations and their compensating transactions:

```
Order → Payment → Inventory → Shipment
  ↓        ↓        ↓          ↓
Cancel  Refund   Release    Cancel
```

**Validation**: Verify every forward step has a corresponding compensation.

### 2. Choose Implementation Approach

| Approach | Use Case | Stack |
|----------|----------|-------|
| Choreography | Greenfield, few participants | Spring Cloud Stream + Kafka/RabbitMQ |
| Orchestration | Complex workflows, brownfield | Axon Framework, Eventuate Tram, Camunda |

**Validation**: Review team expertise and system complexity before choosing.

### 3. Implement Services with Local Transactions

Each service completes its local ACID transaction atomically:

```java
@Service
@RequiredArgsConstructor
public class OrderService {
    private final OrderRepository orderRepository;
    private final KafkaTemplate<String, Object> kafka;

    @Transactional
    public Order createOrder(CreateOrderCommand cmd) {
        Order order = orderRepository.save(new Order(cmd.orderId(), cmd.items()));
        kafka.send("order.created", new OrderCreatedEvent(order.getId(), order.getItems()));
        return order;
    }
}
```

**Validation**: Test that local transaction commits before event is published.

### 4. Implement Compensating Transactions

Every forward operation requires an idempotent compensation:

```java
@Service
@RequiredArgsConstructor
public class PaymentService {
    private final PaymentRepository paymentRepository;
    private final KafkaTemplate<String, Object> kafka;

    public void processPayment(PaymentRequest request) {
        Payment payment = paymentRepository.save(new Payment(request.orderId(), request.amount()));
        kafka.send("payment.processed", new PaymentProcessedEvent(payment.getId(), request.orderId()));
    }

    @Transactional
    public void refundPayment(String paymentId) {
        paymentRepository.findById(paymentId)
            .ifPresent(p -> {
                p.setStatus(REFUNDED);
                paymentRepository.save(p);
                kafka.send("payment.refunded", new PaymentRefundedEvent(paymentId));
            });
    }
}
```

**Validation**: Confirm compensation can execute safely multiple times (idempotency).

### 5. Set Up Message Broker

Configure Kafka with idempotent consumers:

```java
@Configuration
@EnableKafka
public class KafkaConfig {
    @Bean
    public ConcurrentKafkaListenerContainerFactory<String, Object> kafkaListenerContainerFactory(
            ConsumerFactory<String, Object> consumerFactory) {
        ConcurrentKafkaListenerContainerFactory<String, Object> factory =
            new ConcurrentKafkaListenerContainerFactory<>();
        factory.setConsumerFactory(consumerFactory);
        factory.setCommonErrorHandler(new DefaultErrorHandler());
        return factory;
    }
}
```

**Validation**: Enable transactional ID and verify exactly-once semantics.

### 6. Implement Saga Orchestrator (Orchestration Only)

```java
@Service
@RequiredArgsConstructor
public class OrderSagaOrchestrator {
    private final KafkaTemplate<String, Object> kafka;
    private final SagaStateRepository sagaStateRepo;

    public void startSaga(OrderRequest request) {
        String sagaId = UUID.randomUUID().toString();
        sagaStateRepo.save(new SagaState(sagaId, STARTED, LocalDateTime.now()));
        kafka.send("saga.order.start", new StartOrderSagaCommand(sagaId, request));
    }

    @KafkaListener(topics = "payment.failed")
    public void handlePaymentFailed(PaymentFailedEvent event) {
        kafka.send("order.compensate", new CompensateOrderCommand(event.getSagaId()));
        kafka.send("inventory.compensate", new ReleaseInventoryCommand(event.getSagaId()));
        sagaStateRepo.updateStatus(event.getSagaId(), FAILED);
    }
}
```

**Validation**: Verify saga state persists before sending commands. Check compensation triggers on each failure path.

### 7. Implement Event Handlers (Choreography Only)

```java
@Service
public class OrderEventHandler {
    private final OrderService orderService;
    private final KafkaTemplate<String, Object> kafka;

    @KafkaListener(topics = "payment.processed", groupId = "order-service")
    public void onPaymentProcessed(PaymentProcessedEvent event) {
        try {
            InventoryReservedEvent result = orderService.reserveInventory(event.toInventoryRequest());
            kafka.send("inventory.reserved", result);
        } catch (InsufficientInventoryException e) {
            kafka.send("inventory.insufficient", new InsufficientInventoryEvent(event.getOrderId(), event.getPaymentId()));
        }
    }
}
```

**Validation**: Test that each event handler correctly triggers the next step or compensation.

### 8. Add Monitoring and Observability

```java
@Configuration
public class SagaMetricsConfig {
    @Bean
    public MeterRegistry meterRegistry() {
        return new PrometheusMeterRegistry(PrometheusConfig.DEFAULT);
    }
}
```

Track: saga execution duration, compensation count, failure rate, stuck sagas.

**Validation**: Set up alerts for sagas exceeding expected duration.

## Best Practices

**Design**:
- Make compensating transactions **idempotent** using database constraints or deduplication tables
- Use **immutable events** (Java records) to prevent accidental mutation
- Store saga state in persistent storage for recovery

**Error Handling**:
- Implement **circuit breakers** for inter-service calls
- Use **dead-letter queues** for messages exceeding retry limits
- Set appropriate **timeouts** per saga step (30s default, configurable)

**Monitoring**:
- Track saga status: PENDING, COMPLETED, COMPENSATING, FAILED
- Monitor compensation execution time
- Alert when sagas exceed SLA duration

## Constraints and Warnings

- Every forward transaction MUST have a corresponding compensating transaction
- Compensating transactions MUST be idempotent to handle retry scenarios
- Saga state MUST be persisted to handle failures and recovery
- Never use synchronous communication between saga participants
- Sagas provide eventual consistency, not strong consistency
- Test all failure scenarios including partial failures
- Consider Axon Framework or Eventuate for complex orchestrations
- Ensure message brokers are highly available

## Examples

### Choreography-Based Saga

```java
// Application.java
@SpringBootApplication
@EnableKafka
@EnableKafkaListeners
public class OrderApplication {
    public static void main(String[] args) {
        SpringApplication.run(OrderApplication.class, args);
    }
}

// Event Classes (immutable)
public record OrderCreatedEvent(String orderId, List<OrderItem> items) {}
public record PaymentProcessedEvent(String paymentId, String orderId) {}
public record InventoryReservedEvent(String reservationId, String orderId) {}
public record PaymentFailedEvent(String orderId, String reason) {}
public record InsufficientInventoryEvent(String orderId, String paymentId) {}

// OrderService wi