Learn how to avoid common microservices pitfalls and uncover expert acknowledged design patterns and best practices.

 

First quarter of 2018 will bring with it our long-awaited Payara 5, fresh out of Beta. Scheduled for a Q1 release (download the Release Candidate here), Payara 5 brings with it a host of improvements to Payara Server and Payara Micro. Bringing long-awaited upgrades to a raft of APIs, as well as a rethinking of the cluster concept, Payara 5 also brings us up to date with Eclipse MicroProfile 1.2 and the core functionality of GlassFish 5.

 

Configuration is an important aspect of programming. However, a standard approach to it has been missing in Java for a long time. A year ago, the MicroProfile project decided to change that. I'm glad I could be part of it and help design the new API. One year later, a common configuration API aiming to set a standard is a reality, with several released versions and multiple projects that provide it. Payara Server and Payara Micro have supported MicroProfile Config API since version 4.1.2.173. We added support for Config 1.1 in version 4.1.2.174 and completed the support for all Eclipse MicroProfile 1.2 features in version 4.1.2.181. So let's summarize what's new since Config 1.0.

Have you ever wondered how Micro is Payara Micro?

At first, this was a fun experiment installing a terminal app on my Android phone and playing around with some Linux commands. One thing lead to another and I ended up running a Payara Micro instance on my device! In this article, I'm going to show you exactly how to do that.

 

Payara Micro supports Hazelcast out of the box, and can be used for clustering. This allows members in the cluster to distribute data between themselves, amongst other things. By default, Hazelcast comes with multiple ways to discover other members in the same network. A multicast discovery strategy is commonly used for this purpose; a multicast request is sent to all members in a network and the members respond with their IP addresses. Another strategy must be employed if a member cannot or does not wish to provide their IP address.

Admitting When You’re Wrong

Just recently, I have had to admit being wrong. Very wrong. Way back at the start of October, I was feeling the familiar sensation of panic and dread that only happens right before I need to give a presentation that includes a demo! In the end, there were major problems with the AV setup in the room I was allocated, so even arriving as early I could to set up didn’t give the techs enough time to hook up my laptop successfully.

Both Payara Server and Payara Micro can cluster together and share data using Hazelcast. Out-of-the-box, there is no configuration needed, since Hazelcast uses multicast to discover and join other cluster members. However, when running in cloud environments like AWS, for example, there are a lot of things which can stop discovery being quite so straightforward. The key thing is that Multicast is not available, meaning another discovery strategy is needed; the most common generic alternative is to use TCP, but this assumes that you know at least the intended subnet that your cluster members will be in ahead of time.

 

As previously reported on this blog, the Request Tracing Service was improved drastically in release 4.1.1.171 and implemented the configuration of a historic trace record storing for increased productivity purposes. In addition to these changes, we also made the configuration on the Request Tracing Service in Payara Micro for the same release. These changes to Payara Micro make it simpler to configure the Request Tracing Service when starting a new instance!

 

The Payara Micro 173 release had a few changes which will make the lives of Docker users easier. This blog will cover the changes which affect Payara Micro in Docker,  demonstrating the following:

• Using the new Payara Micro 5 Docker image, which provides Java EE 8 features.

• Deploying applications without the targetted database being present.

• Adding library JARs from the command line.

Have you ever wondered how you can improve the performance of your applications under high load? You've probably heard that reactive design can help meet better response time and make your applications more flexible. In this presentation, I will show that you don’t need to rewrite your Java EE applications from scratch to achieve that!