#java

#java

The Java Virtual Machine (JVM) is a marvel of engineering, optimized for long-running, high-performance applications. Its just-in-time (JIT) compiler analyzes code as it runs, making sophisticated optimizations to deliver incredible peak performance. But this strength becomes a weakness in a serverless model. When a Lambda function starts cold, the JVM must go through its entire initialization process: loading classes, verifying bytecode and beginning the slow warm-up of the JIT compiler. This can take several seconds - an eternity for a latency-sensitive workflow.

In the first article we looked at the Java developer's dilemma: the gap between flashy prototypes and the reality of enterprise production systems. In the second article we explored why new types of applications are needed, and how AI changes the shape of enterprise software. This article focuses on what those changes mean for architecture. If applications look different, the way we structure them has to change as well.

Records in Java are a newer kind of class for holding data. Instead of writing boilerplate code for constructors, accessors, equals(), hashCode(), and toString(), you just declare the fields and let the Java compiler handle the rest. This article introduces you to Java records, including examples of basic and advanced use cases and a few programming scenarios where you should not use them.

First things first, you're going to select your LLM. You can go with OpenAI. It's a pretty standard choice for your Hello World. You're going to go to the documentation and you'll see how to actually do a Hello World using OpenAI. Of course, you'll see Python over there. Python is always there. I'm going to count as a win because we're starting to see examples in Java as well.

Perforce Software has introduced JRebel Enterprise, software that promises to accelerate the configuration of cloud-based Java development environments, and that enables incremental code changes to Java applications, eliminating the need to redeploy entire applications for every change, the company said. Announced August 19, JRebel Enterprise skips Java application redeploys for minor code changes and automatically configures Java environments to support changing Java development environments at enterprise scale, Perforce said.

The release of EclipseStore 3.0.0 delivers bug fixes and new features that introduce: GigaMap, a specialized collection aimed at optimizing performance and memory usage in EclipseStore; and Storage Graph Analysis, APIs that export a storage graph structure without user data.

The transition from local development to production is crucial in creating a seamless developer experience, which is a focus for tools and frameworks today.

JobRunr 8.0 has been released, incorporating various new features following two beta releases and one release candidate since its initial announcement.

The release of Spring gRPC 0.9.0 delivers notable changes such as: the removal of the GrpcClientFactoryCustomizer in favor of the GrpcChannelBuilderCustomizer interface and the ability to filter global interceptors.

The TornadoVM programming guide demonstrates how developers can utilize hardware-agnostic APIs, enabling the same Java source code to run identically on various hardware accelerators.

JDK 25 Build 28 and JDK 26 Build 3 were released recently, addressing various issues and furthering the development of upcoming Java versions.

The enhancement addresses a long-standing inefficiency in Java's memory model where object headers can consume over 20% of heap space in applications with many small objects.

To join friends in Minecraft, players must be mutual friends online. Bedrock offers direct world joining, while Java uses Realms or dedicated servers.

JUnit 5 is the de facto standard for developing unit tests in Java, and using a robust test suite ensures confidence in application behavior and future changes.

The release of the Python ADK 1.0.0 and Java ADK 0.1.0 by Google aims to provide developers with flexible tools for building and deploying AI agents.

"This talk is all about ultra-fast in-memory database processing with Java, showcasing how to build the fastest database applications using proven methods utilized by leading industries for over 20 years."

The API aims to simplify parallel task management through clearer frameworks, particularly with virtual threads, enabling developers to achieve safer execution of concurrency.

In Java, the try-with-resources statement automates resource management, closing resources after use, while in Scala, similar functionality is provided by the scala.util.Using utility.

The Vector API enables Java developers to utilize CPU-level performance enhancements, essential for optimizing numerically intensive operations and improving application efficiency.