Java

Not all OpenJDK 12 builds include Shenandoah: Here’s why

Not all OpenJDK 12 builds include Shenandoah: Here’s why

OpenJDK 12 is now out, and it has new features. These are:

189: Shenandoah: A Low-Pause-Time Garbage Collector (Experimental)
230: Microbenchmark Suite
325: Switch Expressions (Preview)
334: JVM Constants API
340: One AArch64 Port, Not Two
341: Default CDS Archives
344: Abortable Mixed Collections for G1
346: Promptly Return Unused Committed Memory from G1

When I follow the link from the OpenJDK 12 project page to the open source builds page, I see the downloadable binaries. I download the Linux binary and install it, then see if the first item on the feature list, Shenandoah, works:

$ ./jdk-12/bin/java -XX:+UnlockExperimentalVMOptions -XX:+UseShenandoahGC -cp ~ Hello
Error occurred during initialization of VM
Option -XX:+UseShenandoahGC not supported

Oh! What is going on?

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Migrating Java applications to Quarkus: Lessons learned

Migrating Java applications to Quarkus: Lessons learned

Migrating applications from a well-grounded framework to a completely new framework just a few days after its public release sounds crazy, right? Before doing so, I asked myself several questions, such as: Why should I do that? Is this new framework stable? What would be the gain? To me, the most important of these is: Why?

To help answer that question, I started thinking about my application’s performance—in this case, the bootstrap time—and asked myself whether I was happy with the actual time my application took to start up. The answer was no. And, nowadays, this is one of the most important metrics to be considered when working with microservices, mainly on a serverless architecture.

The goal of this article is to provide a point of reference for a basic migration of an existing Java EE application to Quarkus. For this reason, I’ll save a few lines of the article by not introducing Quarkus and focus mostly on the migration part. If you don’t know what Quarkus is, then I recommend reading this article and visiting the Quarkus homepage.

In this article, I’ll try to illustrate all the changes, or at least the most important changes, that I had to do on my existing application to make it run well with Quarkus.

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From zero to Quarkus and Knative: The easy way

From zero to Quarkus and Knative: The easy way

You’ve probably already read about Quarkus, but you may not know that the superfast startup speed of Quarkus makes it the best candidate for working with Knative and serverless for your Function-as-a-Service (FaaS) projects.

Quarkus, also known as Supersonic, Subatomic Java, is a Kubernetes native Java stack tailored for GraalVM and OpenJDK HotSpot, crafted from the best-of-breed Java libraries and standards. Knative is a Kubernetes-based platform to build, deploy, and manage modern serverless workloads. You can learn more in this article series.

This article does not provide a full deep dive on Knative or Quarkus. Instead, I aim to give you a quick and easy way to start playing with both technologies so you can further explore on your own.

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10 things developers need to know about JShell

10 things developers need to know about JShell

JShell was introduced in JDK 9 as part of Java Enhancement Proposal (JEP) 222 under project Kulla. Many programming languages, such as JavaScript, Python, Ruby, etc., provide easy-to-use, command-line tools for their execution, but Java was still missing such a utility. So, JDK 9 introduced the Java shell (JShell) tool.

I discussed the basics of JShell (which is a Read-Evaluate-Print-Loop; REPL) in a previous article. In this article, I’ll cover advanced concepts in JShell that users should know for rapid development.

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Announcing Red Hat CodeReady Studio, the latest evolution of Red Hat Developer Studio

Announcing Red Hat CodeReady Studio, the latest evolution of Red Hat Developer Studio

Red Hat has been shipping a distribution of Eclipse IDE for years now, including all of the great features of Eclipse along with the add-ons, plugins, and tooling that make working with our products easy and enjoyable. These distributions have gone by different names over the years to indicate how they fit into the Red Hat ecosystem, and to tap into the trust that developers have when they think about Red Hat and what a Red Hat product means for them: it’ll be reliable; it’ll have a published lifecycle; it’s built from source; and if you submit a bug, we’ll fix it (and give the fix to the community). This change is no different.

Red Hat CodeReady Studio is the latest evolution of Red Hat Developer Studio, which itself was an evolution of JBoss Developer Studio. We’re proud to include our distribution of Eclipse IDE in the expanding CodeReady portfolio. Based on the latest Eclipse 4.11, with the latest additions of JBoss Tools and end-to-end testing that ensures everything works as expected, developers can count on the same great experience they’ve grown used to. With tools for working with Fuse and other middleware products and connectors for Red Hat OpenShift that enable super-fast, container-native “inner loop” development cycles, CodeReady Studio is absolutely one of the best desktop IDEs an enterprise JavaTM developer can use.

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Quarkus: Why compile to native?

Quarkus: Why compile to native?

Quarkus is Kubernetes native, and to accomplish that we’ve spent a lot of time working across a number of different areas, such as the Java Virtual Machine (JVM) and various framework optimizations. And, there’s much more work still to be done. One area that has piqued the interest of the developer community is Quarkus’s comprehensive and seamless approach to generating an operating system specific (aka native) executable from your Java code, as you do with languages like C and C++, which we believe will typically be used at the end of the build-test-deploy cycle.

Although the native compilation is important, as we’ll discuss later, Quarkus works really well with vanilla OpenJDK Hotspot, thanks to the significant performance improvements we’ve made to the entire stack. The native executable aspect Quarkus offers is optional and, if you don’t want it or your applications don’t need it, then you can ignore it. In fact, even when you are using native images, Quarkus still relies heavily on OpenJDK. The well-received dev mode is able to deliver near-instantaneous change-test cycles all due to Hotspot’s rich dynamic code execution capabilities. Additionally, GraalVM internally uses OpenJDK’s class library and HotSpot to produce a native image.

Still, there’s the question: Why have native compilation at all if the other optimizations are so good? That’s the question we’ll look at more closely here.

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Set up JDK Mission Control with Red Hat Build of OpenJDK

Set up JDK Mission Control with Red Hat Build of OpenJDK

JDK Mission Control is now the newest member of the Red Hat Software Collections (RHSCL). JDK Mission Control is a powerful profiler for HotSpot Java virtual machines (JVMs) and has an advanced set of tools that enable efficient and detailed analysis of the extensive data collected by JDK Flight Recorder. The toolchain enables developers and administrators to collect and analyze data from Java applications running locally or deployed in production environments using OpenJDK 11.

In this article, I will go through a primary example of setting up JDK Mission Control. For Linux, JDK Mission Control is part of the RHSCL and, for Windows, it is available as part of the OpenJDK zip distribution on the Red Hat Customer Portal.  For Linux, these instructions assume that Red Hat Build of OpenJDK 11 is already installed. I will show how to set up the system to install software from RHSCL, which provides the latest development technologies for Red Hat Enterprise Linux. Then, I will install the JDK Mission Control and run a simple sample application. The whole tutorial should take fewer than 10 minutes to complete.

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Quarking Drools: How we turned a 13-year-old Java project into a first-class serverless component

Quarking Drools: How we turned a 13-year-old Java project into a first-class serverless component

“The question of whether a computer can think is no more interesting than the question of whether a submarine can swim.” (Edsger W. Dijkstra)

Rule-based artificial intelligence (AI) is often overlooked, possibly because people think it’s only useful in heavyweight enterprise software products. However, that’s not necessarily true. Simply put, a rule engine is just a piece of software that allows you to separate domain and business-specific constraint from the main application flow. We are part of the team developing and maintaining Drools—the world’s most popular open source rule engine and part of Red Hat—and, in this article, we will describe how we are changing Drools to make it part of the cloud and serverless revolution.

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Introducing Quarkus: a next-generation Kubernetes native Java framework

Introducing Quarkus: a next-generation Kubernetes native Java framework

Java was introduced to the open-source community more than 20 years ago and it still remains popular among developers. In fact, Java has never ranked lower than #2 on the TIOBE Index. Java was born in the mid-1990s and has nearly 20 years of optimizations for running highly dynamic monolithic applications that assumed sole ownership of (virtualized) host CPU and memory. However, we now live in a world dominated by the cloud, mobile, IoT, and open source, where containers, Kubernetes, microservices, reactive, Function-as-a-Service (FaaS), 12-factor, and cloud-native application development can deliver higher levels of productivity and efficiency. As an industry, we need to rethink how Java can be best utilized to address these new deployment environments and application architectures.

We’d like to introduce you to Quarkus and Supersonic Subatomic Java!

Quarkus is a Kubernetes Native Java framework tailored for GraalVM and HotSpot, crafted from best-of-breed Java libraries and standards. The goal of Quarkus is to make Java a leading platform in Kubernetes and serverless environments while offering developers a unified reactive and imperative programming model to optimally address a wider range of distributed application architectures.

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