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 →
Last 6 months
This is a second iteration of a previous post, where we implemented EIP patterns using just Drools and Apache Camel. In this post instead, I want to share with you how to implement a complete, end-to-end Content Based Routing solution using Quarkus as a developer platform, including: Drools DMN Engine, Kogito, Apache Camel, AtlasMap andRead more →
an experimental JBang catalog to quickly operate some KIE capabilities, such as DMN and FEEL evaluation on the Command Line!
In this post I want to share an interesting use-case of Healthcare message routing, which we implemented using the Drools DMN Engine and Apache Camel, in order to route and dispatch Patient’s Admission-Discharge-Transfer message types to the required Kafka topics and therefore queuing the message to the appropriate sub-system. I believe it is both aRead more →
On 2021 January 19th, Mario and myself will present at the perpetual DecisionCAMP monthly events! Since DecisionCAMP 2020 held virtually, the organizers have decided to institute a series of perpetual meetups, in addition to the annual conference; you can join the community following the instructions here. Event Title Kogito: Cloud-native Business Automation Event Abstract KogitoRead more →
In this article, we will describe some of the recent updates to the DMN Validation module (kie-dmn-validation) and how the migration to make use of the Executable Model enabled a number of use-cases, such as porting the functionality on the Kogito platform. Introduction The Drools DMN Engine provides static and semantic validation of DMN models:Read more →