Spring Boot Development Services

Why Spring Boot

Spring Boot is the most widely used framework for building Java applications. It removes much of the configuration traditionally associated with Spring, provides sensible defaults and includes embedded servers, so a service can be built, tested and containerised quickly.

With Spring Security, Spring Data, Spring Cloud and a huge ecosystem of integrations, Spring Boot covers most enterprise needs — authentication, data access, messaging, observability — with well-documented, battle-tested components.

When Spring Boot is the right choice

What we build with Spring Boot

Our Spring Boot toolkit

Upgrading to Spring Boot 3

Spring Boot 3 requires Java 17 or later and moved from javax to jakarta packages, which affects many applications and libraries. We plan upgrades by first moving to the latest Spring Boot 2.7, fixing deprecations, upgrading Java, then switching to Spring Boot 3 with automated refactoring tools and a full test run. The result is a supported platform with better performance and native-image options.

Monolith or microservices with Spring Boot?

Spring Boot is often associated with microservices, but a well-structured modular monolith is the better starting point for most teams. Spring Modulith helps enforce boundaries between modules inside one deployable application, so code stays organised and individual modules can be extracted later if scaling or team structure demands it. When microservices are justified, Spring Cloud provides configuration, service discovery, circuit breakers and gateways — though on Kubernetes many of these concerns are better handled by the platform itself.

Production-ready from the first release

• Spring Security with OAuth 2.0 and OpenID Connect integration to Okta, Microsoft Entra ID, Keycloak or Auth0.
• Actuator health and metrics exported to Prometheus, Grafana or your existing monitoring tools.
• Flyway or Liquibase database migrations versioned with the code.
• Testcontainers integration tests against real PostgreSQL, Kafka or Redis instead of mocks.
• Resilience4j timeouts, retries and circuit breakers around external calls.
• Virtual threads on Java 21+ for high-concurrency workloads without reactive complexity.

How we run a Spring Boot 3 upgrade

Spring Boot 3 requires Java 17 or later and moves from the javax to the jakarta namespace, which touches many imports and some third-party libraries. Applications still on Spring Boot 2.x no longer receive open-source support. We handle these upgrades methodically: dependency audit, automated refactoring with OpenRewrite recipes, focused fixes for security configuration changes and full regression testing before release.

Messaging and event-driven integration

Many Spring Boot systems exchange data through events rather than direct calls, which decouples services and absorbs traffic spikes. Spring for Apache Kafka, Spring AMQP for RabbitMQ and Spring Cloud Stream provide consistent programming models across brokers. We design events with versioned schemas, idempotent consumers that can safely process a message twice, dead-letter queues for failures and the transactional outbox pattern so database changes and published events never drift apart. Combined with distributed tracing, this makes asynchronous flows as debuggable as synchronous ones — a common weak point in event-driven systems.

Testing Spring Boot applications

Spring Boot has excellent testing support, and using it well is what lets large Java teams release often without breaking things:

• Unit tests with JUnit 5 and Mockito for business logic
• Slice tests such as @WebMvcTest and @DataJpaTest for focused, fast checks
• Testcontainers for integration tests against real PostgreSQL, Kafka or Redis
• Contract tests between services with Spring Cloud Contract or Pact
• Architecture rules enforced with ArchUnit so module boundaries stay intact

Security with Spring Security

• OAuth 2.0 and OpenID Connect login through Entra ID, Okta, Keycloak or Auth0
• JWT validation for APIs with scopes and roles mapped to method-level checks
• CSRF protection, secure headers and CORS rules configured explicitly
• Secrets loaded from a vault or cloud secret manager, never from source code
• Dependency scanning to catch vulnerable libraries early

For a deeper review, see application security.

Performance and runtime choices

We measure with realistic load before changing runtimes, since connection pools, queries and caching usually matter more.

Observability built in

Spring Boot Actuator and Micrometer make it straightforward to expose health checks, metrics and traces. We wire these into your monitoring stack, whether Prometheus and Grafana, Datadog, New Relic or a cloud provider, so every service reports latency, errors and saturation from its first deployment.

Related: Java development, microservices and Kubernetes consulting.

Questions to settle before starting

• Which Java LTS version and Spring Boot line will we standardise on?
• One deployable application or several services, and why?
• Which identity provider and message broker are already in place?
• How will configuration differ between environments?
• Who owns the build pipeline and production support?

Data access patterns

Spring Data JPA makes simple persistence quick, but large applications need care to avoid performance surprises. We watch for lazy-loading problems that cause many small queries, use projections and explicit fetch joins for read-heavy screens, and manage schema changes with Flyway or Liquibase so every environment matches. For reporting or complex queries, jOOQ or plain SQL through JdbcClient is often clearer than forcing everything through an ORM.

Connection pools are sized against real load, and slow-query logging is enabled from the start so database issues show up in monitoring before users notice them.

Typical Spring Boot engagement

1. Architecture review1–2 weeks

   Agree module boundaries, integrations, security and deployment target.

2. Platform setup1–2 weeks

   Build pipeline, environments, observability and a reference service.

3. Feature deliveryongoing

   Two-week sprints with automated tests and regular releases.

Durations are typical starting points.

Common Spring Boot pitfalls

• Relying on auto-configuration without understanding what it enables in production
• Very large application contexts that slow start-up and tests
• Splitting into microservices before module boundaries are clear
• Exposing Actuator endpoints publicly without authentication
• Letting Spring Boot and Java versions fall behind supported releases
• Distributed transactions across services instead of events and idempotent handlers

Each is easy to avoid with clear conventions agreed at the start of the project and checked in code review. We document these conventions in the repository so new developers follow them from their first pull request.

Build tooling and dependency management

We standardise on Gradle or Maven with the Spring Boot dependency management plugin, so library versions stay compatible with each other. Shared conventions such as code style, test configuration and security scanning live in a common build setup used by every service, which keeps a growing estate of applications consistent and makes upgrades a single coordinated change rather than dozens of separate ones.

Work with us

Part of our backend technologies. See also Java development and microservices.

This page is part of Backend Development Services — see the full overview for related services, approach and pricing.