Back in 2016, we wrote about the importance of automation in taking applications from development to production with Payara Server. Since then, there have been a lot of changes both in Payara Server and Payara Micro and the wider tech landscape.
It may be hard to believe in 2018, but there was once a time before Amazon Web Services. In 2006, Amazon launched what was to become the most dominant platform in cloud computing - the Elastic Compute Cloud (EC2). While there were a lot of early adopters who could see the benefits of "Infrastructure as a Service" (IaaS) style cloud computing - a notable example being Dropbox - there were many who were sceptical of the hype around the "cloud" and prompted stickers like the one pictured.
Payara Server 5 and Payara Micro 5 are here! We've already blogged about some improvements in Payara Server & Payara Micro 5, but there are many more.
We know you'll be excited to find that this release includes several usability improvements making Payara Server & Payara Micro's architecture even more innovative, microservices-ready, cloud-native and optimized for production deployments.
Our Payara Engineers have been working very hard on lots of new features ready for our final 5.181 release! One of the key features we intend to deliver is compatibility with MicroProfile 1.2, which will include (among other things) a Fault Tolerance API.
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.
Do you still think that Java EE is heavy-weight, cumbersome and doesn’t keep up with modern trends? I’ll show you that there are already production-ready enterprise and open source solutions to bring more flexibility than the traditional Java EE servers from the past. They strive to provide lightweight and extensible runtimes to power microservices, cloud deployments and reactive architectures already. Their individual efforts are naturally followed by an open collaboration within the MicroProfile project.