Chapter 2. Red Hat Process Automation Manager components

Red Hat Process Automation Manager is made up of Business Central and Process Server.

  • Business Central is the graphical user interface where you create and manage business rules. You can install Business Central in a Red Hat JBoss EAP instance or on the Red Hat OpenShift Container Platform (OpenShift).

    Business Central is also available as a standalone JAR file. You can use the Business Central standalone JAR file to run Business Central without needing to deploy it to an application server.

  • Process Server is the server where rules and other artifacts are executed. It is used to instantiate and execute rules and solve planning problems. You can install Process Server in a Red Hat JBoss EAP instance, on OpenShift, in an Oracle WebLogic server instance, in an IBM WebSphere Application Server instance, or as a part of Spring Boot application.

    You can configure Process Server to run in managed or unmanaged mode. If Process Server is unmanaged, you must manually create and maintain KIE containers (deployment units). A KIE container is a specific version of a project. If Process Server is managed, the Process Automation Manager controller manages the Process Server configuration and you interact with the Process Automation Manager controller to create and maintain KIE containers.

    The Process Automation Manager controller is integrated with Business Central. If you install Business Central on Red Hat JBoss EAP, use the Execution Server page to create and maintain KIE containers. However, if you do not install Business Central, you can install the headless Process Automation Manager controller and use the REST API or the Process Server Java Client API to interact with it.

  • Red Hat Business Optimizer is integrated in Business Central and Process Server. It is a lightweight, embeddable planning engine that optimizes planning problems. Red Hat Business Optimizer helps Java programmers solve planning problems efficiently, and it combines optimization heuristics and metaheuristics with efficient score calculations.