Java Development

Built for software with a long life ahead of it

Java’s strongest argument is boring and it is the right argument: code written against it keeps compiling and keeps running. Systems that must still be maintainable in a decade, by people who have not met the original authors, are exactly what the language, the JVM and its tooling were shaped around. That is why banking, insurance, telecoms, logistics and public sector systems still run on it, and why replacing them rarely pays.

The platform has also moved a long way from its verbose reputation. Records, sealed types, pattern matching, virtual threads and a much shorter path from source to running service have removed most of the ceremony that people remember from older Java.

Spring Boot as the default

Most new Java work we do is Spring Boot, for the unexciting reason that almost every problem a service will hit has a well-trodden answer in that ecosystem — data access, security, validation, messaging, observability, configuration. The result is less bespoke infrastructure code, and fewer decisions that only the person who made them understands.

Where a lighter footprint or faster startup matters, Quarkus and native compilation are on the table, particularly for services that scale to zero or run at the edge.

What we build

• Domain-heavy backend services — where the rules are intricate, wrong answers are expensive, and a strong type system pays for itself.
• Event-driven pipelines — Kafka consumers and producers, outbox patterns, and the idempotency work that keeps a redelivery from double-charging someone.
• Integration and API layers in front of systems that cannot be changed, including SOAP and fixed-width formats that are still very much alive.
• Batch processing — the overnight jobs that reconcile, settle and report, and that quietly matter more than the web tier.

Moving off an older JVM

Plenty of production Java is still on Java 8 or 11, often held there by a framework version or a single unmaintained dependency. Upgrading is usually less painful than teams fear, and the payoff is concrete: current security patches, faster garbage collection, virtual threads for I/O-heavy services, and a hiring pool that has not moved on. We normally do it in steps — get the build onto a current toolchain, upgrade the framework, then the language level — with tests and a rollback path at every stage.

The stack we work in

Java on a current LTS release, Spring Boot, Maven and Gradle, JPA and Hibernate with jOOQ where SQL should stay visible, PostgreSQL and Oracle, Kafka and RabbitMQ, JUnit 5 with Testcontainers, JaCoCo, Docker, and Kubernetes for deployment. Kotlin where a team wants it, since it shares the ecosystem without a rewrite.

We staff Java engineers into existing teams via outstaffing and take on complete services through outsourcing. Our backend development page covers how these services get designed, and agile delivery covers how the work is run.