Spring Boot development for APIs and microservices

What Spring Boot gives a backend team

Spring Boot's value is less about any single feature and more about convention: a consistent way to configure, secure, test, observe and deploy services. When every service in a system follows the same structure, engineers can move between them easily and operational tooling works the same everywhere.

Spring Boot 3 requires Java 17 or later and is built on Jakarta EE 9+, which brings first-class support for observability through Micrometer, better support for GraalVM native images and a cleaner baseline for the coming years. On Java 21, enabling virtual threads lets traditional blocking Spring MVC code handle high concurrency without moving to WebFlux.

How we build Spring Boot services

We design APIs contract-first with OpenAPI, so clients and servers can be developed in parallel and breaking changes are caught in review. Persistence uses Spring Data JPA where a relational model fits, with Flyway or Liquibase migrations versioned alongside the code, and we keep a close eye on generated SQL to avoid the classic JPA performance traps.

Security is configured explicitly with Spring Security: OAuth 2.0 and OpenID Connect resource servers, method-level authorization where business rules require it, and secure defaults for headers and CORS. Every service exposes health, metrics and traces through Spring Boot Actuator and Micrometer, exported to tools such as Prometheus, Grafana and OpenTelemetry collectors.

• Contract-first REST APIs with OpenAPI and consistent error responses (RFC 9457 problem details)
• Event-driven integration with Spring for Apache Kafka or Spring AMQP, with idempotent consumers
• Integration tests with @SpringBootTest slices and Testcontainers instead of in-memory fakes
• Configuration externalized per environment, secrets kept out of the repository

Spring Boot microservices without unnecessary complexity

Microservices solve organizational and scaling problems, but they also introduce network failures, distributed data and operational overhead. As part of our backend and API engineering work, we help teams decide where service boundaries should be, and we are comfortable recommending a modular monolith when that fits better.

When a distributed architecture is justified, we use the parts of Spring Cloud that earn their place: Spring Cloud Gateway for routing, resilience patterns such as timeouts, retries and circuit breakers with Resilience4j, and configuration management. On Kubernetes we generally rely on the platform for service discovery and configuration rather than duplicating it in the application. Our cloud and DevOps engineering covers the infrastructure side.

Migrating from Spring Boot 2 to Spring Boot 3

Spring Boot 2.7 is no longer covered by open-source support, so many teams need to migrate. The main changes are the move to Java 17+, the javax to jakarta package rename, Spring Security 6 configuration changes, and updated observability and Hibernate 6 behavior.

We migrate in controlled steps: first upgrade to the latest 2.7 release and fix deprecations, then upgrade the Java runtime, then apply automated refactoring with OpenRewrite recipes and resolve the remaining issues by hand. A strong integration test suite is what makes this safe, so if one is missing we add coverage around critical flows before changing versions.

Taking over an existing Spring codebase

Inherited Spring applications often share the same symptoms: slow startup, heavy use of field injection, business logic spread across controllers, and tests that need the full application context to run. We start with a short review covering architecture, dependencies, security configuration and test strategy, and we share the findings as a prioritized list.

From there we improve the codebase while continuing to deliver features, which is usually more realistic than a separate cleanup phase. Larger reviews of this kind are also available as part of our software architecture consulting.