Hi WildFly community, We would like to advertise the existence of the WildFly Glow <https://github.com/wildfly/wildfly-glow>project. WildFly Glow is an evolution of the WildFly Galleon <https://docs.wildfly.org/galleon/>provisioning tooling. It is currently an Alpha, and getting feedback from the community at this point would be very valuable! The goal of this project is to offer some tooling to identify the set of Galleon feature-packs and layers that are required by your application. The entry-point of this discovery being the application deployment. Automatic identification of WildFly Galleon layers Today, in order to trim a WildFly server to fit the application requirements, you have to first identify the set of WildFly Galleon layers <https://docs.wildfly.org/30/Galleon_Guide.html#wildfly_galleon_layers>to use. WildFly Glow identifies the layers for you by scanning your application war (jar or ear) files. This application to Galleon layers mapping is based on rules contained in WildFly Galleon layers (starting WildFly 29). These rules express the Java types, annotations and files (XML descriptors, properties files, ...) that are bound to the usage of a given Galleon layer. An example of rules can be found in the jaxrs <https://github.com/wildfly/wildfly/blob/main/ee-feature-pack/galleon-shar.... In this example we look for REST API usage and a servlet class located in a web.xml file. Once the layers are identified, the Galleon feature-packs that define them are selected and included. Centralized knowledge of WildFly Galleon feature-packs You can today extend a WildFly server at provisioning time by the means of extra Galleon feature-packs. For example, some feature-packs exist to connect to databases, to enable a gRPC endpoint, to enable the Keycloak SAML protocol, to replace the JSF implementation with myFaces, to integrate resteasy-spring features into WildFly, etc (non exhaustive list). WildFly Glow has, per WildFly version, the knowledge of compatible Galleon feature-packs. It offers a centralized view on extra features you can add to your WildFly server. Going beyond discovered Galleon layers WildFly Glow does more than identifying Galleon feature-packs and layers. Provisioning WildFly Glow tooling allows you to provision a WildFly server or a WildFly Bootable JAR or produce a Docker image. WildFly additional features discovery Not all WildFly server features can be discovered by scanning your application deployment. A good example is the usage of SSL to secure the http server access. Another one is the need for WildFly tooling (e.g. WildFly CLI, elytron tooling, ...). WildFly Glow allows you to include, according to what has been discovered in the deployment, a set of additional WildFly features called `add-ons` that makes sense for your application. Implementation wise, such add-ons are Galleon layers. For example, the SSL add-on is implemented by the undertow-https <https://github.com/wildfly/wildfly/blob/main/ee-feature-pack/galleon-shar.... Connection to databases WildFly Glow detects that your application requires a datasource and will suggest you with database `add-ons` to be included in order to connect to the DB of your choice (postgresql, mysql, ...). The Datasources feature-pack layers implement these add-ons. For example, the postgresql <https://github.com/wildfly-extras/wildfly-datasources-galleon-pack/blob/m.... High Availability profile handling Currently, to provision an HA WildFly server using galleon layers, you need to exclude the non HA Galleon layers and include their HA counterparts (e.g.: ‘jpa-distributed <https://github.com/wildfly/wildfly/blob/main/ee-feature-pack/galleon-shar... layer used instead of the ‘jpa’ <https://github.com/wildfly/wildfly/blob/main/ee-feature-pack/galleon-shar..., ‘ejb-dist-cache <https://github.com/wildfly/wildfly/blob/main/ee-feature-pack/galleon-shar... instead of the ‘ejb-local-cache <https://github.com/wildfly/wildfly/blob/main/ee-feature-pack/galleon-shar...). When the HA profile is enabled, WildFly Glow handles the correct inclusions and exclusions of layers. WildFly Glow tooling WildFly Glow offers currently 2 main usages: * A Command Line interface (`wildfly-glow` CLI) that scans your deployment and can provision a WildFly server, a WildFly Bootable JAR and a Docker image (to be deployed on Kubernetes). From the CLI you can discover the list of available `add-ons` and enable them. WildFly Glow currently supports Wildfly 29 and 30. The latest WildFly major (currently 30.0.0.Final) is the default when no WildFly version is specified. * An integration with the WildFly Maven plugin (Starting 5.0.0.Alpha2) `package` goal, to provision a WildFly server without specifying feature-packs and layers. Current status We are currently at an Alpha level and working to reach a Beta level of quality. We have a draft PR <https://github.com/wildfly/wildfly/pull/17153>that updates the WildFly integration testsuite to use the WildFly Glow arquillian Maven plugin (that scans arquillian test deployments) instead of relying on hard coded Galleon layers. 100% of the tests that use Galleon provisioning have been updated. We plan to put in place a WildFly quickstarts <https://github.com/wildfly/quickstart>preview branch that updates all quickstarts to rely on WildFly Glow. We also plan to integrate more feature-packs inside the WildFly Galleon feature-packs registry <https://github.com/wildfly/wildfly-galleon-feature-packs/tree/release>;. Some candidates for which we have Proof of Concept integrations are: keycloak <https://github.com/jfdenise/keycloak/tree/layers_metadata_final>;, myfaces <https://github.com/wildfly-extras/wildfly-myfaces-feature-pack>;, graphql <https://github.com/jfdenise/wildfly-graphql-feature-pack/tree/layers_meta...;, resteasy-spring <https://github.com/jfdenise/resteasy-spring/tree/galleon-layer>;. BTW: if you are defining Galleon feature-packs for WildFly that would be helpful for the community, we should get in touch. A good way to get started with WildFly Glow is by downloading the latest CLI (1.0.0.Alpha7) from here <https://github.com/wildfly/wildfly-glow/releases>and scan your deployments. Feel free to provide us with your feedback! Thank-you. JF Denise