The Payara Platform 5.192 release comes with an update to MicroProfile. Compared to  MicroProfile 2.1, four components were updated in MicroProfile 2.2:

Hello and welcome to the second issue of our monthly round up where we feature a curated list of interesting articles and videos created by the community that we have enjoyed and found interesting. Cant wait until the end of the month? then visit our twitter page where we post all these articles as we find them! 

Hello and welcome to the first issue of our monthly round up where we feature a curated list of interesting articles and videos created by the community in the last month that we have enjoyed taking in.

The 5.191 Payara Platform release brought with it support for MicroProfile 2.1. For those who don't know, the only specification updated in this version of MicroProfile was OpenTracing, going from 1.1 to 1.2.

MicroProfile

For those who did not come across Eclipse MicroProfile yet, let me give you a quick introduction. In 2016, a group of vendors and individuals started an initiative to optimize Enterprise Java for a microservices architecture.

The goal of MicroProfile.IO is to optimise Java EE for a micro-service architecture. It is based on some of the Java EE specifications and standardise a few technologies from the micro-services space.

Java EE 8 fully supports asynchronous handling of REST requests and responses, on both client and server side. This is useful to optimize throughput of an application or even when adopting reactive principles. MicroProfile type-safe REST client API also supports this concept to allow you to call REST services asynchronously with a much more straightforward way with plain Java interfaces.

Payara Server provides many metrics within JMX beans. The most interesting metrics are the statistics around pools for HTTP threads and JDBC Connection pooling.

On the other hand, Payara Server also implements the MicroProfile Metrics specification. The retrieval of useful metrics from the running instance in the areas of CPU, memory, Class loading, and other MicroProfile specifications (like Fault Tolerance), are possible through the implementation of the MicroProfile Metrics in Payara Server.

In the previous blog of this series, we learned different ways to troubleshoot Java EE application. This blog will continue to focus on different ways and techniques to catch potential issues in the early stages and how to find the root cause of application performance issues.