WildFly is a powerful, modular, & lightweight application server that helps you build amazing applications.
Configuration in WildFly is centralized, simple and user-focused. The configuration file is organized by subsystems that you can easily comprehend and no internal server wiring is exposed. All management capabilities are exposed in a unified manner across many forms of access. These include a CLI, a web based administration console, a native Java API, an HTTP/JSON based REST API, and a JMX gateway. These options allow for custom automation using the tools and languages that best fit your needs.
WildFly does classloading right. It uses JBoss Modules to provide true application isolation, hiding server implementation classes from the application and only linking with JARs your application needs. Visibility rules have sensible defaults, yet can be customized. The dependency resolution algorithm means that classloading performance is not affected by the number of versions of libraries you have installed.
WildFly takes an aggressive approach to memory management. The base runtime services were developed to minimize heap allocation by using common cached indexed metadata over duplicate full parses, which reduces heap and object churn. The administration console is 100% stateless and purely client driven. It starts instantly and requires zero memory on the server. These optimizations combined enable WildFly to run with stock JVM settings and also on small devices while leaving more headroom for application data and supports higher scalability.
Using JBoss Generic JMS Resource Adapter you can use a JMS compatible client to connect WildFly to any broker. This article will describe how to do this with Apache Qpid and thus use JMS over AMQP. Installing Apache Qpid You need to download and untar Apache Qpid Broker-J 8.0.0 from https://qpid.apache.org/download.html. You need to allow for anonymous access. Please use the initial-config.json configuration file. Note that we will start Apache Qpid HTTP server on 9080...Read More >
WildFly 19.1.0 Final is now available for download. As we usually do between WildFly majors, we’ve done an update release to provide the WildFly community with important bug fixes and component upgrades that have become available. Typically these are micro releases, but this time we had one feature that we wanted to make available, so we changed the version to 19.1.0 and released a minor. The feature is related to handling of SameSite cookie attributes....Read More >
Introduction The standard and recommended way to configure the WildFly cloud images is by using environment variables. However, you could find it useful for your use case to configure the server by using a custom CLI management operations script. The following post describes how you can apply management operations to configure the WildFly server image. We will show you how you can execute CLI scripts at the Source-to-Image (S2I) phase and how to use the...Read More >
Until WildFly 19 you could use Eclipse MicroProfile OpenTracing (MPOT) to trace your application using environment variables relying on the SmallRye OpenTracing implementation. With WildFly 19 you can now configure several Jaeger Tracers to be used in your applications. Installing Jaeger Let’s start a jaeger instance using docker : docker run -d --name jaeger \ -p 6831:6831/udp \ -p 5778:5778 \ -p 14268:14268 \ -p 16686:16686 \ jaegertracing/all-in-one:1.16 Now, you can navigate to http://localhost:16686 to...Read More >
Galleon is a tool for provisioning Java runtimes. It comes with plugins for provisioning WildFly server instances. We have been using it internally in WildFly to build and configure the server the past few releases, and we recently introduced it into our OpenShift cloud image to be able to create a server with a smaller footprint than the default. This post will give an overview of how to use Galleon to provide your additions to...Read More >
Introduction In this guide, we will show you how we can containerize a JAX-RS PostgreSQL demo application to run on WildFly in a local OpenShift cluster. We will explore the different options we have to configure the data source subsystem in a cloud-based infrastructure. First of all, we will use the WildFly Datasources Galleon Pack to bring in the PostgreSQL data source and driver configuration to our WildFly server. Later, we will show you how...Read More >
WildFly 18 S2I docker images WildFly s2i builder and runtime Docker images for WildFly 18 have been released on quay.io/wildfly Changes since last release: New env variable GALLEON_PROVISION_LAYERS=<layers list> that you can use during s2i to provision a custom WildFly server. It does replace the GALLEON_PROVISION_SERVER that was only offering a subset of Galleon layers. You can now provision WildFly server by directly providing Galleon layers. This offers a lot of flexibility when composing a...Read More >