Best of Spring Boot — March 2026

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    Article
    Avatar of foojayioFoojay.io·9w

    foojay – a place for friends of OpenJDK

    BoxLang Spring Boot Starter lets Spring Boot 3 developers use BoxLang — a modern dynamic JVM language — as a view/templating engine with zero configuration. Add one dependency and write .bxm templates that have full access to HTTP scopes (url, form, cookie, request), auto-inject Spring Model attributes, and support hot-reload during development. BoxLangViewResolver integrates cleanly into Spring MVC's resolver chain alongside Thymeleaf or FreeMarker. Additional features include scheduled tasks, enterprise caching, and enhanced concurrency utilities. Requires Java 21+ and Spring Boot 3.4+.

  2. 2
    Video
    Avatar of dan-vegaDan Vega·10w

    Building a Terminal UI for Spring Initializr with Java

    A developer built a terminal UI (TUI) for Spring Initializr using Java and the newly announced Tamboo UI framework. The tool replicates the Spring Initializr web experience in the terminal, with features like fuzzy dependency search, favorites, project exploration, and post-generation hooks that can automatically open an IDE (like IntelliJ) and launch Claude Code in the new project directory. The native executable is built with GraalVM for fast startup and low memory usage, and binaries for macOS, Windows, and Linux are distributed via GitHub releases.

  3. 3
    Article
    Avatar of quarkusQuarkus·12w

    Quarkus has great performance – and we have new evidence

    The Quarkus team published a new transparent, reproducible benchmark comparing Quarkus and Spring Boot performance. Results show Quarkus handles 2.7x more transactions per second (19,255 vs 7,238 tps), starts 2.3x faster, and uses half the memory. The benchmark addresses past shortcomings: outdated data, missing throughput metrics, and lack of reproducibility. The team open-sourced the benchmark code, invited Spring Boot community input to ensure fairness, and explored questions like virtual threads impact (+6k tps for all frameworks) and Spring Boot 3 vs 4 differences. The post also clarifies that while Quarkus JVM mode outperforms alternatives across all metrics, native compilation does cut throughput in half (though startup and memory improve dramatically), making native mode best suited for frequently restarted or low-workload applications.

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    Article
    Avatar of piotr-minkowskiPiotr Minkowski TechBlog·9w

    Speed up Java Startup with Spring Boot and Project Leyden

    Project Leyden is an experimental OpenJDK initiative that uses Ahead-of-Time (AOT) compilation caching to speed up Java application startup. Using the early access build (EA2, based on JDK 26), you can generate an AOT cache with the -XX:AOTCacheOutput flag on first run, then reuse it with -XX:AOTCache on subsequent runs. Tests with two Spring Boot apps (one using H2+Liquibase, another using Redis) show roughly 40% faster startup times. While promising, the gains are comparable to CRaC and still fall short of GraalVM native image. The key advantage is that Leyden is intended to eventually ship as part of the standard OpenJDK distribution.

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    Article
    Avatar of baeldungBaeldung·8w

    Distributed Transaction Management Using Apache Seata

    Apache Seata is an open source distributed transaction manager originally from Alibaba, now part of the Apache Incubator. It solves the problem of maintaining atomicity across multiple microservices that each have their own database. The setup involves running a Seata Server as a transaction coordinator (via Docker), adding the seata-spring-boot-starter dependency, configuring seata.conf and application.properties, and creating an undo_log table for AT mode. The @GlobalTransactional annotation marks the start of a distributed transaction. For Spring Boot, XID propagation between services requires a custom ClientHttpRequestInterceptor for outbound calls and a servlet filter for inbound calls. Spring Cloud simplifies this by handling most propagation automatically, though RestClient and WebClient still need manual configuration.

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    Article
    Avatar of jetbrainsJetBrains·10w

    Koog Comes to Java: The Enterprise AI Agent Framework From JetBrains

    JetBrains has launched Koog for Java, bringing its AI agent framework to the JVM with a fully idiomatic Java API. The framework lets Java teams build AI agents directly in existing backends without Python microservices. Key features include multiple workflow strategies (functional, graph-based, and GOAP planning), Spring Boot integration, support for major LLM providers (OpenAI, Anthropic, Google, DeepSeek, Ollama), fault-tolerant persistence (Postgres, S3, disk) that resumes from the exact failure point, OpenTelemetry observability with Langfuse and W&B Weave support, history compression to manage token costs, and fine-grained Java thread pool control via ExecutorService configuration.

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