Java has been a staple in the software development world for decades, renowned for its robustness and vast ecosystem. However, some seasoned Java developers have encountered limitations within its collections framework, particularly when dealing with ordered elements. Enter JEP 431. JEP 431, part of the Java Enhancement Proposal system, represents a significant advancement in Java's ongoing evolution. The Java Enhancement Proposal system is a process for proposing, reviewing, and implementing new features in the Java programming language. JEP 431, in particular, introduces necessary enhancements to the Java Collections Framework, addressing longstanding limitations and expanding its capabilities for us Java developers.

In the journey through our Jakarta Batch blog series (see Part 1 here and Part 2 here) , we've taken a deep dive into the architecture of batch jobs, the inner workings of chunks, and the best practices for optimising their processing. Now, it's time to shed light on the less-discussed but equally vital aspect of batch processing: the task-oriented approach, specifically the role of batchlets in Jakarta Batch jobs. We'll also explore how to effectively monitor and manage batch job lifecycles to maintain efficiency and reliability.

Java’s Ahead-of-Time (AOT) native compilation, as seen in frameworks like GraalVM, boasts rapid startup times and lower memory usage. However, for Jakarta EE application developers, the practical benefits of these advantages often don’t translate into substantial economic or technical gains. This leads to questioning the viability of investing resources into adapting existing Jakarta EE applications for GraalVM compatibility.

Download the Guide - Reassessing Native Compilation for Jakarta EE Applications: A Pragmatic Perspective

Cloud deployment refers to the process of hosting applications on a remote server infrastructure, accessible over the internet. This paradigm has revolutionised software development, offering immense scalability, flexibility, and efficiency. Traditional deployment methods have evolved to embrace modern cloud environments, ranging from Infrastructure-as-a-Service (IaaS), where you manage servers but not physical hardware, to Platform-as-a-Service (PaaS) and Software-as-a Service (SaaS) solutions, which abstract much of the server management and maintenance tasks.

Download the Guide - Automated Jakarta EE Cloud Deployments With GitHub Actions And Payara Cloud

Continuing from where thelast blog post left off, let's delve deeper into the intricacies of configuring the chunk in Jakarta Batch. As we've seen, a chunk represents a set of items to be processed as a batch. Now we will explore how to control this process, manage potential errors, and ensure efficient execution.

In a world where technology never sleeps, staying ahead is not just an advantage; it's a necessity.  This is especially true for organisations running enterprise-level applications on Java EE 8 through  Payara Enterprise 5. While this platform has undoubtedly served you well, the release of Jakarta  EE 10 and Payara Enterprise 6 marks the beginning of a new era in Enterprise Java development. 

In the dynamic world of software development, efficiency and speed are key. This is where Payara Starter, our new code scaffolding tool, comes in. Designed to streamline and simplify the initial setup process, Payara Starter helps developers like you kickstart your Jakarta EE projects with ease, whether you prefer Maven or Gradle build systems.

Splashing onto the scene with a tidal wave of updates, the November 2023 release of Payara Platform is here. This release brings enhancements, security fixes, and bug fixes, ensuring a more robust and efficient environment for your mission critical workload. Payara Enterprise 6.8.0 comes with 4 improvements, 3 bug fixes, 1 security fix and 1 component upgrade. Payara Community 6.2023.11 also comes with 4 improvements, 3 bug fixes, 1 security fix and 1 component upgrade.

Garbage collection is a cornerstone feature in the Java Language. It automates memory management by reclaiming memory occupied by objects that are no longer in use, freeing you the developer up from manual memory allocation and deallocation tasks. This feature is vital for preventing memory leaks and ensuring that applications run efficiently over time.

Deploying Jakarta EE applications to the cloud can be a complex task if you are using traditional deployment options like containers, Kubernetes or other such options, but not with Payara Cloud. Uploading a Jakarta EE binary artefact (.war file) and deploying it to the cloud can be achieved in four straightforward steps. They are: