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Chapter 6. Technology preview


This section lists features that are in Technology Preview in Red Hat Process Automation Manager 7.13. Business Central includes an experimental features administration page that is disabled by default. To enable this page, set the value of the appformer.experimental.features property to true.

Important

These features are for Technology Preview only. Technology Preview features are not supported with Red Hat production service level agreements (SLAs), might not be functionally complete, and Red Hat does not recommend using them for production. These features provide early access to upcoming product features, enabling customers to test functionality and provide feedback during the development process.

For more information on Red Hat Technology Preview features, see Technology Preview Features Scope.

6.1. Prediction Service API

You can use the prediction service API to provide a prediction service that assists with user tasks. The prediction service can use artificial intelligence (AI). For example, you can use the Predictive Model Markup Language (PMML) models or Statistical Machine Intelligence and Learning Engine (SMILE) to implement the service.

You can deploy a high-availability Red Hat Process Automation Manager authoring environment on Red Hat OpenShift Container Platform 4.x using the operator.

6.3. OpenShift operator installer wizard

An installer wizard is provided in the Red Hat OpenShift Container Platform operator for Red Hat Process Automation Manager. You can use the wizard to deploy a Red Hat Process Automation Manager environment on Red Hat OpenShift Container Platform with the operator.

6.4. Authoring perspective customization

You can perform the following tasks to customize the Business Central authoring perspective:

  • Open a Business Central project directly using an URL path parameter, without going through a list of spaces and projects.
  • Hide or show the project toolbar, Metrics tab, and Change Request tab according to your requirements.
  • Enhance the pagination.
  • Customize the number of assets present on the project screen.

6.5. Red Hat build of OptaPlanner new constraint collectors

In order to provide a full implementation of some pre-existing OptaPlanner examples using the Constraint Streams API, the standard library of constraint collectors has been extended to include the following constraint collectors:

  • One constraint collector takes point values such as dates, orders them on a number line, and makes groups of consecutive values with breaks between the groups available downstream.
  • Another constraint collector takes interval values such as shifts, creates clusters of consecutive and possibly overlapping values with breaks between clusters, and makes the clusters available downstream.

These new collectors are in technology preview. Their interfaces, names, and functionality are subject to change. They have been placed in an experimental package outside of the public API to encourage public feedback before they become an officially supported part of the OptaPlanner public API.

6.6. Red Hat build of Kogito and Kafka integration

Red Hat build of Kogito decision microservices integration with managed Kafka by using the org.kie.kogito:kogito-addons-{quarkus|springboot}-events-decisions event-driven add-on is now available as technology preview. On Red Hat build of Quarkus, you can add the io.quarkus:quarkus-kubernetes-service-binding dependency to the application to handle the service binding created by the managed Kafka. On Spring boot, you must add the mappings field to the created service binding which must contain the required environment variables needed by the application. Another solution is to use the custom configuration maps available in the Red Hat build of Kogito operator.

You can use the Quarkiverse File Vault extension to store credentials as keystore files and use the file method to use the keystore files with the Process Instance Migration (PIM) Keystore Vault.

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