What are the pitfalls about running Java or JVM based applications in containers? In this article, Jörg Schad goes over the challenges and how to solve them.
What did we read as the year drew to a close? We pop a bottle of champagne and pour some bubbly as we take a look at some of our top stories from the whole of 2017, from Java to Eclipse, Angular to ML, and more!
How can you make design more recognizable? In this series, Denis Kuniß explains one approach developers can take to move beyond object-oriented design and improve the flow of their code.
Eclipse Oxygen.2 includes a number of improvements in functionality and performance. If you want to find out more about some of the impressive new upgrades for the Java IDE, Git and C/C++, check out this video.
In this article, Mark Vollmary talks about native multi-model databases and introduces ArangoDB. If you want to know how ArangoDB integrates with Java, look no further.
The Z Garbage Collector (ZGC) was designed with the aim to remove obstacles that have previously hindered Java developers from getting access to innovations and new features. Now that the project is open source, anyone can try it out on their workloads. Let’s allow Per Liden, ZGC Lead, to tell us what’s under the hood of this new project and what’s next for ZGC.
As 2017 draws to a close, it’s good to stop and take a look at how things have gone over the past twelve months. Today, we’re looking at Java: what happened this year and what’s next for our favorite programming language.
Machine learning can do all sorts of things: it can discover new exoplanets and apparently, it will help machines (in the not so distant future) write most of their own code by 2040.
It’s official. The next Java version will be called JDK 10. It’s time to say goodbye to the scheme introduced by JEP 223 since it’s no longer “well-suited to the [six-month cadence] future”.
The Kotlin Team AMA is over now but it’s been quite the ride. There were over 600 comments and the list of people from the Kotlin team grew bigger and bigger until there were 12 persons answering users’ questions. Let us know what your highlights are in the comments section.
Python and R have long been the two languages said to have a hold on the data science world, but that’s not to say they’re the only languages worth using for data science. Java is, in fact, a great language for doing data science — in this article, Aaron Lazar offers 10 reasons why Java should be included in your next data science project.
Do you need a bootstrap project to help you with your next microservice architecture? Trust me, if you’re interested in implementing microservices, this project is for you. In this article, Alexsandro Souza addresses some common challenges that everyone faces when starting with microservices.
Leaves are crunching underfoot as we move towards the end of the year. As we polish off the last of the turkey leftovers, let’s take a look at what everyone was reading in November. Last month, we read all about Angular old and new, React.js, the top freelance skills of 2017, and more!
What are your plans for moving to JDK 9? Are you already in production or are we all just “thinking” about it? Simon Ritter believes that there are a few key reasons why JDK 9 will have little adoption in production.