I’ve been thinking about building resilient systems lately. What happens when you need more than just the current state of your application? When you require a complete history of changes for auditing, debugging, or rebuilding state? That’s when I turned to event sourcing with Axon Framework and Spring Boot. Let’s explore how this powerful combination solves real-world challenges.

Traditional persistence stores only the latest state. But what if we kept every change as immutable events? Imagine having a complete timeline of your business data. That’s the core idea behind event sourcing. Axon Framework provides the tools to implement this pattern effectively, while Spring Boot simplifies configuration and deployment. Together, they create robust systems that stand the test of time.

Consider an e-commerce order system. When an order is placed, we record the “OrderPlaced” event. When items are added, we store “ItemAdded”. This sequence becomes our source of truth. Why guess about past states when you can replay actual events? Let’s build this step by step.

First, set up a Spring Boot project with Axon dependencies:

<dependency>
    <groupId>org.axonframework</groupId>
    <artifactId>axon-spring-boot-starter</artifactId>
    <version>4.8.5</version>
</dependency>
<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-data-jpa</artifactId>
</dependency>

Our domain model starts with aggregates - clusters of objects treated as single units. The Order aggregate handles commands and emits events:

@Aggregate
public class OrderAggregate {
    @AggregateIdentifier
    private String orderId;
    
    @CommandHandler
    public OrderAggregate(PlaceOrderCommand command) {
        apply(new OrderPlacedEvent(command.getOrderId(), command.getItems()));
    }
    
    @EventSourcingHandler
    public void on(OrderPlacedEvent event) {
        this.orderId = event.getOrderId();
    }
}

Notice how commands trigger events, while event sourcing handlers rebuild state. How do we ensure consistency across distributed components? That’s where Axon’s command gateway helps:

@Autowired
private CommandGateway commandGateway;

public void placeOrder(String orderId, List<OrderItem> items) {
    commandGateway.send(new PlaceOrderCommand(orderId, items));
}

For querying, we build projections from events. This JPA entity represents our read model:

@Entity
public class OrderSummary {
    @Id
    private String orderId;
    private OrderStatus status;
    
    @EventHandler
    public void on(OrderPlacedEvent event) {
        this.orderId = event.getOrderId();
        this.status = OrderStatus.PLACED;
    }
}

Testing is crucial. Axon provides TestFixtures for aggregate testing:

@Test
void testOrderPlacement() {
    fixture.givenNoPriorActivity()
           .when(new PlaceOrderCommand("order1", items))
           .expectSuccessfulHandlerExecution()
           .expectEvents(new OrderPlacedEvent("order1", items));
}

What about performance? Event sourcing introduces unique considerations. Snapshots help optimize aggregates with long event histories:

@Bean
public SnapshotTriggerDefinition snapshotTrigger(Snapshotter snapshotter) {
    return new EventCountSnapshotTriggerDefinition(snapshotter, 50);
}

Common pitfalls include overcomplicating event design and neglecting idempotency. Remember: events are facts, not commands. Keep them focused on what happened, not what should happen. How would you handle duplicate events in your system?

For advanced scenarios, Axon’s Saga implementation manages distributed transactions:

@Saga
public class OrderManagementSaga {
    @StartSaga
    @SagaEventHandler(associationProperty = "orderId")
    public void handle(OrderPlacedEvent event) {
        // Initiate payment process
    }
}

Alternatives exist, but Axon’s tight integration with Spring Boot and comprehensive tooling makes it stand out. The framework handles event storage, message routing, and infrastructure concerns so you focus on business logic.

I’ve found event sourcing particularly valuable for financial systems and audit-heavy domains. The ability to reconstruct state at any point provides unparalleled insight. Have you considered how temporal queries could benefit your applications?

Building with Axon requires mindset shifts. Commands may fail, but events never change. Projections might lag. These trade-offs bring significant advantages in traceability and flexibility. What problems could you solve with a complete change history?

The journey from traditional CRUD to event sourcing pays dividends in system resilience and business insight. Start small with a single bounded context, apply the patterns we’ve covered, and expand as you gain confidence. Your future self will thank you when debugging production issues or implementing new features.

Found this helpful? Share your thoughts in the comments below - I’d love to hear about your event sourcing experiences. If this guide solved a problem for you, consider sharing it with colleagues who might benefit.