Spring AI 2.0 advances the Java framework for generative AI apps with a Spring Boot 4 baseline, cleaner agentic tooling, Model Context Protocol support and vendor-backed integrations including Azure ...

Open-source Java projects advance Jakarta EE compatibility, persistence capabilities, and developer tooling as enterprise teams prepare for the next generation of Java applications.

The release includes an embedded MCP server that exposes Spring project analytics to AI coding assistants, along with first-class support for Spring AI and automated property refactoring.

Aseon Labs, which came out of Y Combinator's 2026 spring cohort, has raised $10 million from Crane Venture Partners and ...

Building web services and documenting RESTful endpoints is no easy task, but testing RESTful APIs has always been a particularly sore point with Spring Boot and Java. Sure, you can test a GET ...

This crash course on how to build a RESTful API with Spring Boot teaches everything you need to know to immediately develop enterprise-grade microservices in Java. In just 90 minutes you'll learn how ...

Java 17 or higher Maven 3.6 or higher PostgreSQL 12 or higher Redis 6 or higher IDE (IntelliJ IDEA, Eclipse, or VS Code) src/main/java/com/rskworld ...

Cloud-native and microservices architectures are becoming even more central to modern applications, with Java and Spring Boot powering scalable backend systems. Lightweight frameworks and cutting-edge ...

The goal of the project is to make it easy to have proper and consistent error responses for REST APIs build with Spring Boot. See https://wimdeblauwe.github.io/error ...

There are plenty of ways to integrate an AI model in your code. But sometimes, when you start, it is really hard to pick one. That’s why, I decided to share my experience in going through this path.