Why We Chose Spring Boot for Microservices

When the Monolith Becomes a Problem

Anyone who has developed enterprise software in recent years knows the pattern: an application starts as a manageable project, grows over months and years, and eventually you end up with a monolith that nobody fully understands anymore. Deployments become risky, build times explode, and teams block each other because everyone is working on the same artifact.

This is exactly what we experienced across multiple client projects. The classic Java EE approach with WAR deployments on an application server works -- until it doesn't. At the latest, when a team consists of more than five developers and the application covers multiple business domains, the monolith becomes a bottleneck.

Microservices are no silver bullet here, but they solve some of these problems very elegantly: independent deployments, clear responsibilities, technological freedom per service. For us, the question was not whether, but how.

Why Spring Boot?

After evaluating various frameworks -- including Dropwizard, Vert.x, and pure Java EE approaches with WildFly Swarm -- we settled on Spring Boot. The reasons are multifaceted.

Auto-Configuration: Less Boilerplate, More Productivity

Spring Boot analyzes the classpath and configures beans automatically. If you have an H2 database on the classpath, you get a DataSource. If you include Spring MVC, you get an embedded Tomcat. This sounds trivial, but in practice it saves an enormous amount of time that would otherwise be spent on XML configuration or manual bean definitions.

A working application can be set up in just a few minutes:

@SpringBootApplication
public class OrderServiceApplication {

    public static void main(String[] args) {
        SpringApplication.run(OrderServiceApplication.class, args);
    }
}

That's all the code you need to start a service. No web.xml, no application server setup, no deployment descriptor.

Embedded Server: One JAR, One Process

In the microservice world, the deployment unit is crucial. Spring Boot builds a so-called fat JAR -- a single JAR file that already contains the embedded Tomcat (or Jetty, or Undertow). This means: java -jar order-service.jar and the service is running.

This simplifies not only the deployment but also the container strategy. A Dockerfile for a Spring Boot service is remarkably simple:

FROM openjdk:8-jre-alpine
COPY target/order-service.jar /app.jar
ENTRYPOINT ["java", "-jar", "/app.jar"]

Combined with Docker, each service becomes a standalone container that can be independently scaled and deployed.

Opinionated Defaults: Convention Over Configuration

Spring Boot makes deliberate choices. Jackson for JSON serialization, Logback for logging, Tomcat as the embedded server. You can override everything, but you don't have to. For teams developing multiple services in parallel, this is invaluable: every service behaves the same way without having to assemble a custom framework stack.

The application.properties or application.yml files provide a central place for all configuration. Environment-specific settings can be cleanly separated via profiles (spring.profiles.active) -- a pattern that fits a microservice architecture perfectly.

Spring Cloud: The Ecosystem for Distributed Systems

Microservices bring their own challenges: service discovery, load balancing, centralized configuration, circuit breakers. This is where Spring Cloud comes in, building closely on Spring Boot and addressing many of these concerns.

We were particularly impressed by the integration with Netflix OSS:

• Eureka for service discovery -- each service registers automatically and can find other services by name.
• Ribbon for client-side load balancing -- requests are intelligently distributed across available instances.
• Hystrix as a circuit breaker -- when a downstream service fails, a fallback kicks in instead of blocking the entire call chain.
• Zuul as an API gateway -- a central entry point that handles routing, filtering, and authentication.

All of these components can be integrated into a Spring Boot service with just a few annotations and minimal configuration. This significantly lowers the barrier to entry.

REST APIs with Spring Boot: A Practical Example

A typical microservice at our company exposes a REST API. With Spring Boot, a simple controller looks like this:

@RestController
@RequestMapping("/api/orders")
public class OrderController {

    private final OrderService orderService;

    @Autowired
    public OrderController(OrderService orderService) {
        this.orderService = orderService;
    }

    @GetMapping("/{id}")
    public ResponseEntity<Order> getOrder(@PathVariable Long id) {
        return orderService.findById(id)
                .map(ResponseEntity::ok)
                .orElse(ResponseEntity.notFound().build());
    }

    @PostMapping
    public ResponseEntity<Order> createOrder(@RequestBody @Valid Order order) {
        Order created = orderService.create(order);
        URI location = ServletUriComponentsBuilder.fromCurrentRequest()
                .path("/{id}")
                .buildAndExpand(created.getId())
                .toUri();
        return ResponseEntity.created(location).body(created);
    }
}

Content negotiation, error handling, and JSON serialization all work out of the box. If you include Spring Data JPA, you also get a repository pattern that reduces database access to just a few lines. This allows us to have new services production-ready within hours -- not days.

Starter POMs as a Toolkit

An often underrated advantage is the Spring Boot starter POMs. Instead of fighting through dependency conflicts, you pull in a starter and get a coordinated set of libraries:

• spring-boot-starter-web for REST services
• spring-boot-starter-data-jpa for database access
• spring-boot-starter-security for authentication and authorization
• spring-boot-starter-actuator for health checks and metrics

The Actuator in particular is indispensable for microservices. It provides endpoints for health checks that an orchestrator like Docker Swarm or Kubernetes can use to monitor the state of a service.

Things to Keep in Mind

Microservices with Spring Boot are not a set-and-forget solution. The complexity shifts from the code to the infrastructure. You need a solid CI/CD pipeline, a well-thought-out logging strategy (we use the ELK stack), and monitoring that goes beyond individual services.

Communication between services also needs careful planning. Synchronous REST calls create dependencies; asynchronous communication via a message broker like RabbitMQ can help, but increases complexity.

If you're getting started with microservices, start small. Don't set up 20 services right away -- begin with two or three, build out the infrastructure, and gain experience.

Outlook

Spring Boot has established itself as the most productive framework for microservices in the Java ecosystem for us. The combination of a quick start, well-thought-out defaults, and the powerful Spring Cloud ecosystem makes it the first choice for new projects.

With the increasing adoption of Docker and container orchestration platforms, this approach will become even more relevant in the coming years. We are closely watching developments in the area of container orchestration and are convinced that Spring Boot will continue to gain importance here.

In future articles, we will dive deeper into specific aspects: service discovery with Eureka, configuration management with Spring Cloud Config, and the topic of monitoring in a distributed architecture.