Traditionally, the majority of decision tables list their rules in the top-to-bottom order when different rules are placed in rows. Here is an example of a typical single-hit decision table created in Excel in accordance with the OpenRules format: Continue reading
Nowadays, when microservices quickly overcome the legacy style of monolithic applications, it’s only natural to deploy Business Decision Models as Decision Microservices. We’ve just published a new tutorial that in a step-by-step manner explains how to convert OpenRules-based decision models, created and tested by business users, to decision microservices with Spring Boot and then containerize them with Docker. Following the tutorial you will learn how to: Continue reading
The integrated use of Machine Learning (ML) and Business Rules (BR) is one of the most practical trends in the development of modern decision-making software. OpenRules is involved in this development for more than 10 years starting with our successful ML+BR projects for IRS. Along with a general purpose Rule Learner, we also provide Rule Compressor, that uses ML to compress large decision tables to smaller ones. This recent presentation explains how it works. Continue reading
We are aggressively making OpenRules-based services available from cloud environments such as Amazon EC2. In particular, we’ve just re-deployed our Decision Model Analyzer from a 3rd party remote Tomcat to Amazon. It was just a very simple reconfiguration, but the effect is really positive: the Analyzer is now much faster and much more reliable. You may try it yourself without any registration or fee: simply click on the button on the right.
The source code of the Analyzer is included in the OpenRules standard release and can be considered as an example of how to deploy OpenRules web applications created using OpenRules Dialog to cloud. Another example is the game “Nim” that you may play now from the cloud by clicking on the image below: Continue reading