I’ve been working with distributed systems for years, and one question keeps coming up: how do we build applications that not only scale but also maintain a complete, trustworthy history of every change? This curiosity led me to event sourcing, and specifically to combining Axon Framework with Spring Boot. Traditional approaches often bury the story behind data changes, making debugging and auditing painful. Event sourcing changes this by storing every state change as an immutable event. If you’re tired of losing context in your data, stick with me as we build a high-performance system from the ground up.

Event sourcing flips traditional data persistence on its head. Instead of storing only the current state, we capture every change as an event. Think about a bank account: we don’t just store the balance; we record every deposit, withdrawal, and account creation. This gives us a perfect audit trail and the ability to reconstruct any past state. Have you ever wished you could see exactly how your data looked last Tuesday at 3 PM? With event sourcing, you can.

Let’s start by setting up our project. We’ll use Spring Boot for its simplicity and Axon for its robust event sourcing capabilities. Here’s a basic Maven setup:

<dependency>
    <groupId>org.axonframework</groupId>
    <artifactId>axon-spring-boot-starter</artifactId>
    <version>4.8.4</version>
</dependency>
<dependency>
    <groupId>org.springframework.boot</groupId>
    <artifactId>spring-boot-starter-data-jpa</artifactId>
</dependency>

Commands in Axon represent intentions to change state. For our bank account example, a command might be “CreateAccount” or “DepositMoney.” Events are the factual records of what happened, like “AccountCreated” or “MoneyDeposited.” Here’s how you might define a command:

public class CreateAccountCommand {
    @TargetAggregateIdentifier
    private String accountId;
    private String ownerName;
    // Constructor and getters
}

When this command is handled, it produces an event:

public class AccountCreatedEvent {
    private String accountId;
    private String ownerName;
    private BigDecimal initialBalance;
    // Constructor and getters
}

Aggregates are the heart of our domain model. They process commands and emit events. In Axon, an aggregate is a class annotated with @Aggregate. It maintains its state by applying events. For instance, when an AccountCreatedEvent is applied, the aggregate sets its initial balance. What happens if multiple commands try to modify the same aggregate concurrently? Axon handles this with optimistic locking, ensuring consistency.

Projections build query models from events. If you need a view of all accounts with their current balances, a projection listens to events and updates a database table. This separates read and write concerns, a key part of CQRS. Here’s a simple projection:

@EventHandler
public void on(AccountCreatedEvent event) {
    accountViewRepository.save(new AccountView(event.getAccountId(), event.getInitialBalance()));
}

Performance can suffer when aggregates have thousands of events. Snapshots help by periodically saving the current state, so we don’t need to replay all events every time. Axon can automatically create snapshots when certain conditions are met. How do you decide when to snapshot? It often depends on the number of events or time intervals.

Event schemas evolve over time. Upcasting allows older event versions to be transformed into the current format. Imagine if we added a new field to an event; upcasting ensures we can still read old events. Axon provides tools for this, making schema changes manageable.

Testing event-sourced systems requires a different approach. We need to verify that commands produce the correct events and that aggregates handle events properly. Axon’s test fixtures make this straightforward. You can set up a test scenario, send commands, and assert on the resulting events.

Common pitfalls include not designing events carefully. Events should represent business facts, not database operations. Another issue is overcomplicating projections. Keep them simple and focused on specific read needs. Have you considered how to handle event ordering in distributed systems? Axon’s event store ensures events are stored in the order they occurred.

While Axon and Spring Boot are powerful, alternatives like EventStoreDB or custom solutions exist. The choice depends on your team’s expertise and system requirements. I prefer Axon for its integration with Spring and comprehensive feature set.

Building with event sourcing requires a mindset shift, but the benefits in traceability and flexibility are immense. I’ve seen teams transform their ability to debug and scale by adopting this pattern. If this resonates with you, I’d love to hear your thoughts—feel free to like, share, or comment below. Let’s keep the discussion going and help each other build better systems.