Jonathan Lalou's Blog

Posts Tagged ‘KotlinConf2025’

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.

Links:

• Max Rydahl Andersen on about.me
• Red Hat company website
• Twilio company website

The concluding panel of KotlinConf2025 offered a vibrant and candid discussion, serving as the capstone to the conference. The diverse group of experts from JetBrains, Netflix, and Google engaged in a wide-ranging dialogue, reflecting on the state of Kotlin, its evolution, and the path forward. They provided a unique blend of perspectives, from language design and backend development to mobile application architecture and developer experience. The conversation was an unfiltered look into the challenges and opportunities facing the Kotlin community, touching on everything from compiler performance to the future of multiplatform development.

The Language and its Future

A central theme of the discussion was the ongoing development of the Kotlin language itself. The panel members, including Simon from the K2 compiler team and Michael from language design, shared insights into the rigorous process of evolving Kotlin. They addressed questions about new language features and the careful balance between adding functionality and maintaining simplicity. A notable point of contention and discussion was the topic of coroutines and the broader asynchronous programming landscape. The experts debated the best practices for managing concurrency and how Kotlin’s native features are designed to simplify these complex tasks. There was a consensus that while new features are exciting, the primary focus remains on stability, performance, and enhancing the developer experience.

The State of Multiplatform Development

The conversation naturally shifted to Kotlin Multiplatform (KMP), which has become a cornerstone of the Kotlin ecosystem. The panelists explored the challenges and successes of building applications that run seamlessly across different platforms. Representatives from companies like Netflix and AWS, who are using KMP for large-scale projects, shared their experiences. They discussed the complexities of managing shared codebases, ensuring consistent performance, and maintaining a robust build system. The experts emphasized that while KMP offers immense benefits in terms of code reuse, it also requires a thoughtful approach to architecture and toolchain management. The panel concluded that KMP is a powerful tool, but its success depends on careful planning and a deep understanding of the underlying platforms.

Community and Ecosystem

Beyond the technical discussions, the panel also reflected on the health and vibrancy of the Kotlin community. A developer advocate, SA, and others spoke about the importance of fostering an inclusive environment and the role of the community in shaping the language. They highlighted the value of feedback from developers and the critical role it plays in guiding the direction of the language and its tooling. The discussion also touched upon the broader ecosystem, including the various libraries and frameworks that have emerged to support Kotlin development. The panel’s enthusiasm for the community was palpable, and they expressed optimism about Kotlin’s continued growth and adoption in the years to come.

Links:

• Google company website
• JetBrains company website
• Netflix company website

The journey of an object within a computer’s memory is a topic that is often obscured from the everyday developer. In a highly insightful session, Troels Lund, a leader on the Kotlin/Native team at Google, delves into the intricacies of what transpires behind the scenes when an object is instantiated and subsequently discarded within the Kotlin/Native runtime. This detailed examination provides a compelling look at a subject that is usually managed automatically, demonstrating the sophisticated mechanisms at play to ensure efficient memory management and robust application performance.

The Inner Workings of the Runtime

Lund begins by exploring the foundational elements of the Kotlin/Native runtime, highlighting its role in bridging the gap between high-level Kotlin code and the native environment. The runtime is responsible for a variety of critical tasks, including memory layout, garbage collection, and managing object lifecycles. One of the central tenets of this system is its ability to handle memory allocation and deallocation with minimal developer intervention. The talk illustrates how an object’s structure is precisely defined in memory, a crucial step for both performance and predictability. This low-level perspective offered a new appreciation for the seamless operation that developers have come to expect.

A Deep Dive into Garbage Collection

The talk then progresses to the sophisticated mechanisms of garbage collection. A deep dive into the Kotlin/Native memory model reveals a system designed for both performance and concurrency. Lund describes the dual approach of a parallel mark and concurrent sweep and a concurrent mark and sweep. The parallel mark and concurrent sweep is designed to maximize throughput by parallelizing the marking phase, while the concurrent mark and sweep aims to minimize pause times by allowing the sweeping phase to happen alongside application execution. The session details how these processes identify and reclaim memory from objects that are no longer in use, preventing memory leaks and maintaining system stability. The discussion also touches upon weak references and their role in memory management. Lund explains how these references are cleared out in a timely manner, ensuring that objects that should be garbage-collected are not resurrected.

Final Thoughts on the Runtime

In his concluding remarks, Lund offers a final summary of the Kotlin/Native runtime. He reiterates that this is a snapshot of what is happening now, and that the details are subject to change over time as new features are added and existing ones are optimized. He emphasizes that the goal of the team is to ensure that the developer experience is as smooth and effortless as possible, with the intricate details of memory management handled transparently by the runtime. The session serves as a powerful reminder of the complex engineering that underpins the simplicity and elegance of the Kotlin language, particularly in its native context.

Links:

• Google company website

Managing a large, multi-team codebase is a monumental task, especially when it has evolved over many years. Introducing architectural changes and maintaining consistency across autonomous teams adds another layer of complexity. In a comprehensive discussion, Tristan Hamilton, a distinguished member of the HubSpot team, presented a strategic approach to future-proofing Android codebases by leveraging static analysis tools like KtLint and Detekt.

Tristan began by framing the challenges inherent in a codebase that has grown and changed for over eight years. He emphasized that without robust systems, technical debt can accumulate, and architectural principles can erode as different teams introduce their own patterns. The solution, he proposed, lies in integrating automated guardrails directly into the continuous integration (CI) pipeline. This proactive approach ensures a consistent level of code quality and helps prevent the introduction of new technical debt.

He then delved into the specifics of two powerful static analysis tools: KtLint and Detekt. KtLint, as a code linter, focuses on enforcing consistent formatting and style, ensuring that the codebase adheres to a single, readable standard. Detekt, on the other hand, is a more powerful static analysis tool that goes beyond simple style checks. Tristan highlighted its ability to perform advanced analysis, including type resolution, which allows it to enforce architectural patterns and detect complex code smells that a simple linter might miss. He shared practical examples of how Detekt can be used to identify and refactor anti-patterns, such as excessive class size or complex methods, thereby improving the overall health of the codebase.

A significant part of the talk was dedicated to a specific, and crucial, application of these tools: safely enabling R8, the code shrinker and optimizer, in a multi-module Android application. The process is notoriously difficult and can often lead to runtime crashes if not handled correctly. Tristan showcased how custom Detekt rules could be created to enforce specific architectural principles at build time. For instance, a custom rule could ensure that certain classes are not obfuscated or that specific dependencies are correctly handled, effectively creating automated safety nets. This approach allowed the HubSpot team to gain confidence in their R8 configuration and ship with greater speed and reliability.

Tristan concluded by offering a set of key takeaways for developers and teams. He underscored the importance of moving beyond traditional static analysis and embracing tools that can codify architectural patterns. By automating the enforcement of these patterns, teams can ensure the integrity of their codebase, even as it grows and evolves. This strategy not only reduces technical debt but also prepares the codebase for future changes, including the integration of new technologies and methodologies, such as Large Language Model (LLM) generated code. It is a powerful method for building robust, maintainable, and future-ready software.

Links:

• HubSpot website
• Code Quality at Scale: Future Proof Your Android Codebase with KtLint and Detekt | Tristan Hamilton

The journey to unified mobile applications is a complex one, fraught with technical and organizational challenges. Rodrigo Sicarelli, a staff software engineer at StoneCo, a leading Latin American fintech company, shared a compelling real-world account of his company’s two-year transition to Kotlin Multiplatform (KMP). This exploration revealed the strategic decisions, hurdles, and impressive achievements that led to a remarkable 55% code sharing across two large-scale mobile applications.

The initial challenge for StoneCo was to evaluate various cross-platform frameworks to find one that could balance the efficiency of code sharing with the critical need for a seamless user experience in the financial sector. Rodrigo detailed the exhaustive process of assessment and the ultimate decision to adopt KMP, a choice that promised to unify their mobile development efforts. A key part of the journey was the organizational shift, which involved training 130 mobile engineers to embrace a new paradigm. Rodrigo emphasized that this was not merely a technical migration but a cultural and educational one, fostering a collaborative spirit and promoting knowledge sharing across teams.

As the adoption matured, the teams faced a number of technical hurdles. One of the primary challenges was ensuring consistent data models and a unified network layer. Rodrigo outlined how they tackled this by consolidating data sources and creating a shared codebase for networking logic, which streamlined development and reduced errors. Another significant obstacle was the integration of KMP into their iOS CI/CD pipeline. He provided a clear explanation of how they overcame this by creating custom Gradle tasks and optimizing their build process, which dramatically improved build times. He also touched upon the importance of addressing the specific needs of iOS developers, particularly concerning the generation of idiomatic Swift APIs from the shared Kotlin code.

A major win for the team was the development of a custom Gradle plugin to manage Kotlin Multiplatform dependencies. This innovation was designed to solve a problem with exposing external libraries to Swift, where the linker would sometimes struggle with duplicate symbols. By adding annotations, the team was able to improve the linking process and reduce build times. This solution not only streamlined their internal workflow but is also planned for open-sourcing, showcasing StoneCo’s commitment to giving back to the community.

Rodrigo concluded by looking to the future, outlining a vision for a single, unified application repository that is user-segment-aware and built with Compose Multiplatform. This forward-looking approach demonstrates a long-term commitment to KMP and a desire to continue pushing the boundaries of shared code. His talk provided invaluable, actionable insights for any organization considering or already in the process of scaling Kotlin Multiplatform.

Links:

• StoneCo website
• Two Years with Kotlin Multiplatform: From Zero to 55% Shared Code | Rodrigo Sicarelli

The world of dependency management is often taken for granted in the JVM ecosystem. However, when venturing into the realm of Kotlin Native, the familiar comforts of JAR files and class loaders fade, giving way to a more intricate and challenging landscape. In his insightful talk, Tadeas Kriz, a senior Kotlin developer at Touchlab, demystified this complex topic, offering a detailed comparison between JVM and native dependency handling and providing practical solutions for common issues.

Tadeas began by drawing a clear distinction between the two worlds. The JVM handles the heavy lifting of linking and loading dependencies at runtime, a process that is largely transparent to the developer. In contrast, Kotlin Native produces a standalone binary, which means the developer must contend with the nuances of native linking and compilation. This fundamental difference introduces a new set of challenges, particularly for those accustomed to the JVM’s seamless “it just works” experience.

He delved into the specifics of native platforms, examining dependency management tools like CocoaPods and Swift Package Manager used on Apple platforms. By comparing their strengths and weaknesses, Tadeas provided valuable context for how Kotlin Multiplatform fits into this ecosystem. He underscored the importance of understanding the native build process, a step that is often abstracted away but is crucial for troubleshooting the cryptic errors that can arise when integrating dependencies. He emphasized that static linking is often the most reliable approach in Kotlin Native, offering a more predictable and robust solution.

A significant portion of the talk was dedicated to practical workarounds and tools to overcome these challenges. Tadeas introduced a key concept: cinterop bindings, which are used to interact with C libraries from Kotlin Native code. He explained how to handle dynamic and static libraries and provided guidance on navigating the complexities of header file inclusion and symbol visibility. He also highlighted the utility of specific tools and practices, such as meticulously heeding build warnings, as they often contain clues to underlying issues.

Tadeas also brought attention to Skie, an open-source tool he co-authored, which addresses a key pain point for developers: the quality of the Kotlin Multiplatform API exposed to Swift. He explained that Skie enhances the generated Swift API, making it more idiomatic and easier for iOS developers to work with. He positioned it as a valuable solution for teams looking to improve their development workflow and collaboration while waiting for future features like Swift export. His talk provided a comprehensive guide, arming developers with the knowledge and tools needed to navigate the complexities of dependencies in the Kotlin Native world with greater confidence and efficiency.

Links:

• Touchlab website
• Dependencies and Kotlin Native | Tadeas Kriz

A captivating tale of a developer’s obsession and a journey into the less-trodden paths of Kotlin development was shared by Márton Braun, a Developer Advocate at JetBrains. It all began with a simple, yet compelling, observation at a previous KotlinConf: a screen saver featuring the bouncing Kotlin logos, reminiscent of old DVD players. Upon discovering it was merely a pre-rendered video and not a true screen saver, a challenge was born. Márton set out to build his own, a native macOS application powered by Kotlin/Native.

The project became a masterclass in interoperability and a candid exploration of the quirks of native application development. Márton detailed how Kotlin/Native’s powerful interop capabilities made it surprisingly easy to call native macOS APIs. However, this ease was often contrasted with the complexities and frustrations of working with the macOS platform itself. The development process was a constant battle, with macOS often proving to be an uncooperative partner in this creative endeavor.

Márton’s perseverance paid off, resulting in a fully functional screen saver. He even managed to create two distinct implementations: one using the traditional AppKit framework and another built with Compose Multiplatform. This dual approach not only demonstrated the capabilities of both technologies but also provided a unique learning experience. He highlighted how the Compose version allowed him to focus on the core UI logic, abstracting away the intricacies of packaging the screen saver. This is a powerful testament to Compose Multiplatform’s potential for simplifying development and improving productivity.

The screen saver project serves as an excellent case study, showcasing Kotlin’s ability to venture into unconventional domains beyond mobile and backend development. Márton successfully demonstrated that with Kotlin and the right tools, developers can create truly native applications for platforms like macOS, leveraging their existing skills and knowledge. The flexibility of Kotlin Multiplatform allows developers to share code across platforms while still delivering a native user experience.

Ultimately, this project is a celebration of the unique possibilities that Kotlin offers. It encourages developers to think creatively about how they can apply the language to solve a wide range of problems and build applications for a diverse set of platforms. Márton’s story is an inspiring reminder that sometimes the most interesting and valuable projects are born from a simple desire to see something that doesn’t exist yet come to life.

Links:

• Márton Braun on GitHub
• Márton Braun’s Blog
• JetBrains website
• Building a macOS Screen Saver with Kotlin | Márton Braun

In the high-stakes world of competitive sailing, where every decision can mean the difference between victory and defeat, an extraordinary tool has emerged: Kotlin Notebook. Roman Belov, a distinguished member of the JetBrains team, shared a captivating account of leveraging this innovative technology to triumph in a 24-hour regatta. The narrative transcends a simple code demonstration, illustrating how interactive programming becomes a critical asset in a dynamic, unpredictable environment like the open sea.

This journey highlights the power of Kotlin Notebook as more than just a development tool; it’s a platform for real-time problem-solving. While a seasoned developer, Roman’s most cherished hat is that of a yachtsman. He uses the notebook to translate complex nautical challenges into actionable, data-driven decisions. The essence of the task is to navigate a course, which is essentially a graph with nodes representing different locations and edges representing the path between them. However, unlike a typical graph problem, the rules of sailing introduce complex variables. The boat cannot sail directly into the wind, and its speed is heavily dependent on the angle of the wind. This means the graph is constantly changing, making traditional route-planning algorithms obsolete.

The solution required a tool that could rapidly process data, visualize outcomes, and allow for on-the-fly adjustments. This is where Kotlin Notebook excelled, providing a live, interactive environment. Roman outlined how he could use the notebook to perform crucial tasks in the middle of the race: visualizing the race course on a map, calculating the fastest path based on current wind conditions, and dynamically adjusting the route as the wind shifted. This is achieved by creating a “sailable roads” model, which evaluates every potential path on the graph at regular intervals and discards any that are impossible given the wind direction. For the remaining paths, the notebook computes the optimal boat speed and time to complete that segment, effectively modeling the race in real time.

Roman then showcased the brute-force search algorithm that was used to find the optimal path. The code, written in Kotlin, was surprisingly straightforward and demonstrated the language’s elegance and readability. The algorithm, running within the notebook, would constantly iterate through the potential paths, calculating the time to finish for each one and discarding any that were slower than the best time found so far. The visual output of the notebook, which could render the different routes directly on the map, was a game-changer. It transformed abstract data and calculations into a clear, visual representation that allowed the sailors to make quick, informed decisions.

The application of Kotlin Notebook in this unconventional scenario proves its versatility beyond traditional data science or development tasks. It demonstrated how a tool designed for rapid experimentation can be applied to complex, real-world problems. The interactive nature of the notebook allowed Roman to combine data analysis, algorithm execution, and visual feedback into a single, cohesive workflow, enabling him and his crew to stay ahead of the competition and ultimately, win the race. This story is a testament to the power of a modern programming language and an adaptable toolchain, turning a challenging maritime endeavor into an exciting display of computational prowess.

Links:

• Roman Belov on JetBrains Blog
• JetBrains website
• Charts, Code, and Sails: Winning a Regatta with Kotlin Notebook | Roman Belov