Posts Tagged ‘Quarkus’
[KotlinConf2025] LangChain4j with Quarkus
In a collaboration between Red Hat and Twilio, Max Rydahl Andersen and Konstantin Pavlov presented an illuminating session on the powerful combination of LangChain4j and Quarkus for building AI-driven applications with Kotlin. The talk addressed the burgeoning demand for integrating artificial intelligence into modern software and the common difficulties developers encounter, such as complex setups and performance bottlenecks. By merging Kotlin’s expressive power, Quarkus’s rapid runtime, and LangChain4j’s AI capabilities, the presenters demonstrated a streamlined and effective solution for creating cutting-edge applications.
A Synergistic Approach to AI Integration
The core of the session focused on the seamless synergy between the three technologies. Andersen and Pavlov detailed how Kotlin’s idiomatic features simplify the development of AI workflows. They presented a compelling case for using LangChain4j, a versatile framework for building language model-based applications, within the Quarkus ecosystem. Quarkus, with its fast startup times and low memory footprint, proved to be an ideal runtime for these resource-intensive applications. The presenters walked through practical code samples, illustrating how to set up the environment, manage dependencies, and orchestrate AI tools efficiently. They emphasized that this integrated approach significantly reduces the friction typically associated with AI development, allowing engineers to focus on business logic rather than infrastructural challenges.
Enhancing Performance and Productivity
The talk also addressed the critical aspect of performance. The presenters demonstrated how the combination of LangChain4j and Quarkus enables the creation of high-performing, AI-powered applications. They discussed the importance of leveraging Quarkus’s native compilation capabilities, which can lead to dramatic improvements in startup time and resource utilization. Additionally, they touched on the ongoing work to optimize the Kotlin compiler’s interaction with the Quarkus build system. Andersen noted that while the current process is efficient, there are continuous efforts to further reduce build times and enhance developer productivity. This commitment to performance underscores the value of this tech stack for developers who need to build scalable and responsive AI solutions.
The Path Forward
Looking ahead, Andersen and Pavlov outlined the future roadmap for LangChain4j and its integration with Quarkus. They highlighted upcoming features, such as the native asynchronous API, which will provide enhanced support for Kotlin coroutines. While acknowledging the importance of coroutines for certain use cases, they also reminded the audience that traditional blocking and virtual threads remain perfectly viable and often preferred for a majority of applications. They also extended an open invitation to the community to contribute to the project, emphasizing that the development of these tools is a collaborative effort. The session concluded with a powerful message: this technology stack is not just about building applications; it’s about empowering developers to confidently tackle the next generation of AI-driven projects.
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[DevoxxGR2025] Unmasking Benchmarking Fallacies
Georgios Andrianakis, a Quarkus engineer at Red Hat, presented a 46-minute talk at Devoxx Greece 2025, dissecting benchmarking fallacies, based on a talk by performance expert Francisco Negro.
The Benchmarketing Problem
Andrianakis introduced “benchmarketing,” where benchmarks are manipulated for marketing. Inspired by Negro’s frustration with a claim that Helidon outperformed Quarkus in a TechEmpower benchmark, he explored how data can be misrepresented. Benchmarks should be relevant, representative, equitable, repeatable, cost-effective, scalable, and transparent. A misleading article claimed Helidon’s superiority, but Negro’s investigation revealed unfair comparisons, sparking this talk to expose such fallacies.
Dissecting a Flawed Claim
Focusing on equity, Negro analyzed the TechEmpower benchmark, which tests web frameworks on tasks like JSON serialization and database queries. The claim hinged on a test where Helidon used a raw database driver (Vert.x for PostgreSQL), while Quarkus used a full object-relational mapper (ORM) like Hibernate, incurring performance penalties. Filtering for full ORM tests, Quarkus topped the charts, with Helidon absent. Comparing both without ORMs, Quarkus still outperformed. This exposed the claim’s inequity, as it wasn’t apples-to-apples, misleading readers.
Critical Thinking in Benchmarks
Andrianakis emphasized skepticism, citing Hitchens’ Razor: claims without evidence can be dismissed. Using Brendan Gregg’s USE method, Negro identified CPU saturation, not database I/O, as the bottleneck, debunking assumptions. He urged active benchmarking—monitoring errors and resources—and measuring one level deeper to understand performance. Awareness of biases, like confirmation bias, and avoiding assumptions of malice over incompetence, ensures fair evaluation of benchmark claims.
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[DevoxxUK2024] Productivity is Messing Around and Having Fun by Trisha Gee & Holly Cummins
In their DevoxxUK2024 talk, Trisha Gee (Gradle) and Holly Cummins (Red Hat, Quarkus) explore developer productivity through the lens of joy and play, challenging conventional metrics like lines of code. They argue that developer satisfaction drives business success, drawing on Fred Brooks’ The Mythical Man-Month to highlight why programmers enjoy crafting, solving puzzles, and learning. However, they note that developers spend only ~32% of their time coding, with the rest consumed by toil (e.g., waiting for builds, context-switching).
The speakers critique metrics like lines of code, citing examples where incentivizing code volume led to bloated, unmaintainable codebases (e.g., ASCII art comments). They warn against AI tools like Copilot generating verbose, unnecessary code (e.g., redundant getters/setters in Quarkus), which increases technical debt. Instead, they advocate for frameworks like Quarkus that reduce boilerplate through build-time bytecode inspection, enabling concise, expressive code.
Trisha and Holly introduce the SPACE framework (Satisfaction, Performance, Activity, Communication, Efficiency) as a holistic approach to measuring productivity, emphasizing developer well-being and flow over raw output. They highlight the importance of mental space for creativity, citing the brain’s default mode network, activated during low-stimulation activities like showering, running, or knitting. They encourage embracing “boredom” and play, supported by research showing happier developers are more productive. The talk critiques flawed metrics (e.g., McKinsey’s) and warns against management misconceptions, like assuming developers are replaceable by AI.
[DevoxxBE 2023] The Great Divergence: Bridging the Gap Between Industry and University Java
At Devoxx Belgium 2023, Felipe Yanaga, a teaching assistant at the University of North Carolina at Chapel Hill and a Robertson Scholar, delivered a compelling presentation addressing the growing disconnect between the vibrant use of Java in industry and its outdated perception in academia. As a student with internships at Amazon and Google, and a fellow at UNC’s Computer Science Experience Lab, Felipe draws on his unique perspective to highlight how universities lag in teaching modern Java practices. His talk explores the reasons behind this divergence, the negative perceptions students hold about Java, and actionable steps to revitalize its presence in academic settings.
Java’s Strength in Industry
Felipe begins by emphasizing Java’s enduring relevance in the professional world. Far from the “Java is dead” narrative that periodically surfaces online, the language thrives in industry, powered by innovations like Quarkus, GraalVM, and a rapid six-month release cycle. Companies sponsoring Devoxx, such as Red Hat and Oracle, exemplify Java’s robust ecosystem, leveraging frameworks and tools that enhance developer productivity. For instance, Felipe references the keynote by Brian Goetz, which outlined Java’s roadmap, showcasing its adaptability to modern development needs by drawing inspiration from other languages. This continuous evolution ensures Java remains a cornerstone for enterprise applications, from microservices to large-scale systems.
However, Felipe points out a troubling trend: despite its industry strength, Java’s popularity is declining in metrics like GitHub’s language rankings and the TIOBE Index. While JavaScript and Python have surged, Java’s share of relevant Google searches has dropped from 26% in 2002 to under 10% by 2023. Felipe attributes this partly to a shift in academic settings, where the foundation for programming passion is often laid. The disconnect between industry innovation and university curricula is a critical issue that needs addressing to sustain Java’s future.
The Academic Lag: Java’s Outdated Image
In universities, Java’s reputation suffers from outdated teaching practices. Felipe notes that many institutions, including top U.S. universities, have shifted introductory courses from Java to Python, citing Java’s perceived complexity and age. A 2017 quote from a Stanford professor illustrates this sentiment, claiming Java “shows its age” and prompting a move to Python for introductory courses. Surveys of 70 leading U.S. universities confirm this trend, with Python now dominating as the primary teaching language, while Java is relegated to data structures or object-oriented programming courses.
Felipe’s own experience at UNC-Chapel Hill reflects this shift. A decade ago, Java dominated the curriculum, but by 2023, Python had overtaken introductory and database courses. This transition reinforces a perception among students that Java is verbose, bloated, and outdated. Felipe conducted a survey among 181 students in a software engineering course, revealing stark insights: 42% believed Python was in highest industry demand, 67% preferred Python for building REST APIs, and terms like “tedious,” “boring,” and “outdated” dominated a word cloud describing Java. One student even remarked that Java is suitable only for maintaining legacy code, a sentiment that underscores the stigma Felipe aims to dismantle.
The On-Ramp Challenge: Simplifying Java’s Introduction
A significant barrier to Java’s adoption in academia is its steep learning curve for beginners. Felipe contrasts Python’s straightforward “hello world” with Java’s intimidating boilerplate code, such as public static void main. This complexity overwhelms novices, who grapple with concepts like classes and static methods without clear explanations. Instructors often dismiss these as “magic,” which disengages students and fosters a negative perception. Felipe highlights Java’s JEP 445, which introduces unnamed classes and instance main methods to reduce boilerplate, as a promising step to make Java more accessible. By simplifying the initial experience, such innovations could align Java’s on-ramp with Python’s ease, engaging students early and encouraging exploration.
Beyond the language itself, the Java ecosystem poses additional challenges. Installing Java is daunting for beginners, with multiple Oracle websites offering conflicting instructions. Felipe recounts his own struggle as a student, only navigating this thanks to his father’s guidance. Tools like SDKMan and JBang simplify installation and scripting, but these are often unknown to students outside the Java community. Similarly, choosing an IDE—IntelliJ, Eclipse, or VS Code—adds another layer of complexity. Felipe advocates for clear, standardized guidance, such as recommending SDKMan and IntelliJ, to streamline the learning process and make Java’s ecosystem more approachable.
Bridging the Divide: Community and Mentorship
To reverse the declining trend in academia, Felipe proposes actionable steps centered on community engagement. He emphasizes the need for industry professionals to connect with universities, citing examples like Tom from Info Support, who collaborates with local schools to demonstrate Java’s real-world applications. By mentoring students and updating professors on modern tools like Maven, Gradle, and Quarkus, industry can reshape Java’s image. Felipe also encourages inviting students to Java User Groups (JUGs), where they can interact with professionals and discover tools that enhance Java development. These initiatives, he argues, plant seeds of enthusiasm that students will share with peers, amplifying Java’s appeal.
Felipe stresses that small actions, like a 10-minute conversation with a student, can make a significant impact. By demystifying stereotypes—such as Java being slow or bloated—and showcasing frameworks like Quarkus with hot reload capabilities, professionals can counter misconceptions. He also addresses the lack of Java-focused workshops compared to Python and JavaScript, urging the community to actively reach out to students. This collective effort, Felipe believes, is crucial to ensuring the next generation of developers sees Java as a vibrant, modern language, not a relic of the past.
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University of North Carolina at Chapel Hill
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Duke University
Hashtags: #Java #SoftwareDevelopment #Education #Quarkus #GraalVM #UNCChapelHill #DukeUniversity #FelipeYanaga