Posts tagged Scalability (2)
Payara Micro is packed with most of the features and APIs that come with Payara Server Full Profile even though it doesn't entirely support whole Jakarta EE Full Profile. As an example, Payara Micro supports persistent EJB Timers, which are only required by the Jakarta EE Full Profile and not by the Web Profile. In Payara Micro, it's possible to use persistent EJB Timers, which are stored across your micro instances inside the distributed data grid as long as at least one instance in the data grid is up and running.
Take a look at this quick demo to see some of Payara Micro's dynamic clustering capabilities. I'm running the demo without any extra tools, just Payara Micro itself. To show how Payara Micro dynamically rebalances the cluster, I used
JCache and Payara Micro's
Application server clustering provides a means to make application infrastructure more robust and perform better. However, it is often very inflexible and even a small change in the cluster topology can involve serious maintenance costs. Payara Server supports a new way of clustering based on Hazelcast, which brings much more flexibility, decreases maintenance costs and adds the benefit of JCache support out of the box.
GlassFish has traditionally used Project Shoal to power its clusters. Since Shoal is no longer actively maintained, Payara Server intends to replace Shoal with Hazelcast, which has the added benefit of being JCache compliant.
In the first part of this 'Introduction to Payara Scales' blog, I will give you an overview of the architecture for a Payara Scales cluster and a load balancer upfront, using Amazon CloudFormation and Amazon EC2.
One of the lesser known features and key benefits of Payara Server is that it provides huge flexibility when architecting topologies for High Availability and Scalability. Utilising the embedded Hazelcast Data Grid for web session and JCache clustering brings the potential of many different topologies for scale out.