In my previous blog post,here,I examined the JSR-375 specifications and their implementation by Jakarta EE and, more specifically, by the Payara Platform (Server and Micro).

I presented a brief overview of the JSR-375 specifications and their new features, focusing on the notion of Identity Store and illustrating, with a simple example, one of the most common use cases: the LDAP (Lightweight Directory Access Protocol) based authentication and authorization process.

Co Authored with Nicolas Frankel (Hazelcast Developer Advocate), this article is also available as a PDF.

The Hazelcast In-Memory Data Grid (IMDG) is an efficient method of storing data in a distributed way within the memory of the different processes of the cluster. Because it is distributed, searching the data locally requires 'moving' the data to your instance so it can be accessed, which is not overly efficient.  Hazelcast SQL allows distributed queries which perform the search where the data is, and then transfers only the results to your process. Since the Payara products already use Hazelcast IMDG, using the Hazelcast SQL capabilities is straightforward: just add the additional JAR library to start using it.

Payara Microでは、Webアプリケーションを自己完結型で簡単に実行することができます。2016年5月のPayara Serverリリースからは、WARファイルの内容とPayara Microを構成するクラスやリソースを束ねる “Uber JAR” を作成する簡単な方法があります。

この “Uber” Jarは、Dockerコンテナ内でアプリケーションを実行するための最良の方法ではないことに注意してください。アプリケーションに小さなコード変更を加えるたびに、バイナリ全体のアップデートが必要になるためです。より良い方法は、Payara Microインスタンスを起動して、インストールが必要なアプリケーションを指定することです。詳細については Payara Micro Docker Image documentation をご覧ください。

(最終更新日 2021/04/06)

Microservices architecture allows developers to apply best practices for larger systems learned over time with containerized Jakarta EE (Java EE) application deployments in any environment: on premise, in the cloud, or hybrid.  Using Payara Micro in the cloud offers benefits ranging from reduced expenses, seamless integration with cloud platforms and tools for management and automation, to automatic and elastic clustering. 

In this tutorial, I will explain how to create, run and debug a Payara Micro application in Visual Studio Code. (If you're interested in learning more about using Payara Server in VSCode, please checkout ourprevious blogs.)

In this short video, Rudy de Busscher demonstrates how to use MicroProfile Config with etcd.

Payara Micro is a lightweight middleware platform for containerized Jakarta EE application deployments, but it still provides a lot of APIs and functionality for developers. On top of all Jakarta EE Web Profile APIs, Payara Micro also supports a additional Jakarta EE APIs, and it also provides the same MicroProfile, Payara, and JCache APIs as our complete application platform, Payara Server. In this article, we’ll show you how to make use of Jakarta Messaging (JMS) in Payara Micro to send and receive messages to and from a JMS broker.

MicroProfile Health is an API designed specifically for use in cloud and containerized environments, where you want to quickly determine if an instance of an application is unhealthy and restart it. How exactly do you use it though? In this session, I’ll run through how to add some health checks to your application, and how to configure a number of cloud providers and containers to effectively use them to restart your application instances.

Payara Micro 5.201 adds two command line options that make preparation of container images easier, as well as enable class data sharing on HotSpot Java Virtual Machine.

One of the performance metrics that are frequently compared  by developers are startup times. Payara Server is designed to be manageable at runtime, with a central management server (DAS - domain administration server) and multiple instances, and as such is not optimized for extremely fast startup time. Payara Micro on the other hand, is optimized to run predefined workloads with a stable configuration at runtime, and is therefore a better fit for for comparing start up time metrics.

In this blog, let's take a look at how you can configure Payara Micro for fast startup time by utilizing the class data sharing feature of Eclipse OpenJ9.