Karina Varela and myself would like to invite you to this free technical exploration (with hands-on labs) on IBM Business Automation Manager Open Edition (BAM) which is the new name for the former Red Hat PAM/DM products that have recently moved to the IBM Business Automation portfolio. After this session, you will have a good understanding of what thisRead more →
The Decision Model and Notation (DMN) is an effective, yet standardized, tool for designing complex decisions, in special decision tables. Even though you, DMN developer, already knew about the existence of this capability, here’s something you didn’t know: there is a new DMN Decision Table column data type constraint enhancement in the DMN Editor. Let’s checkRead more →
Managing exceptional rules is easy, thanks to Drools and Kogito! In this use-case, we have a base business process and a default knowledge base with rules, which can be overridden by specific entities or departments as needed. We actually have several architectural options we could implement! The simplest architectural option I can think about, drawsRead more →
The latest Drools 8.31.0.Final comes with a Reactive Messaging example, which demonstrates reactively consuming messages from a Kafka topic, firing rules and then sending result messages to another Kafka topic. You can find it in https://github.com/kiegroup/drools/tree/main/drools-drl-quarkus-extension/drools-drl-quarkus-examples/drools-drl-quarkus-examples-reactive. This blog post explains how it works. How To Run the Example Clone drools repository Go to the exampleRead more →
The Drools team is happy to announce that our rule engine reached the 8 Final release. Drools 8-series is a natural evolution of the 7.x-stream, incorporating many features and lessons learned integrating with Kogito and many cloud-native use cases. The purpose of this article is to give a high level overview of the features introducedRead more →
Memory issues are another frequent topic in Drools trouble-shooting. This article will explain how to solve issues categorized in 3 types. Long term memory leak while using Drools applications The word "Memory leak" is typically used for the situation where a JVM triggers Full GCs but the footprint is constantly increasing. In this case, let’sRead more →
Following up from a previous blog post about integrating Drools with the Open Prediction Service, in this new post we want to share the current results from another exploration work: this time integrating Drools with research on Transparent Machine Learning by IBM. Introduction Transparency is a key requirement in many business sectors, from FSI (FinancialRead more →
We’re introducing an (experimental) DMN FEEL handbook, an helpful companion for your DMN modeling activities! You can access this new helpful resource at the following URL: https://kiegroup.github.io/dmn-feel-handbook. Key features include: FEEL built-in functions organised by category tested and integrated FEEL examples Responsive design: easily access on Mobile, Tablet and Desktop from your favourite browser! …andRead more →
Comparison of a JSON array based approach vs Jackson Inheritance Annotations Introduction: “Kogito is a next generation business automation toolkit that originates from well known Open Source projects Drools (for business rules) and jBPM (for business processes). Kogito aims at providing another approach to business automation where the main message is to expose your businessRead more →
This short tutorial walks you through the configuration and deployment of a simple Drools serverless application, including autoscaling with scale to zero, thanks to Kogito, Quarkus, OpenShift Serverless with Kubernetes and Knative! Step 1: Drools app creation with code.quarkus.io To generate the application as shown in the video, you can use this link: https://code.quarkus.io/?e=org.kie.kogito%3Akogito-quarkus-decisions&e=resteasy-jackson&e=kubernetes&e=container-image-jib TheRead more →
