OpenRules is Shining in the Serverless World

When 3.5 years ago we introduced a new OpenRules Decision Manager, it was specifically designed as a Decision Intelligence Framework for creation, debugging, and management of Superfast Decision Microservices for that time brand new Serverless world. Over the last 3 years we witnessed how major corporate customers migrated their rules-based applications deployed on the large web servers to OpenRules. Over the last few weeks we saw how several new customers were really surprised that they don’t need anymore heavy lifting for building and managing their rules-based light-weighted microservices. In this brief post I share a working sample that demonstrates how easy it is to build, test, debug, deploy, and run RESTful decision services with OpenRules using any on-cloud or on-premise infrastructure.

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Decision Services Handling Large Payloads

On Apr 20, 2022 I shared recent OpenRules experience building decision services capable to handle huge payloads with sound performance. He described how putting a decision service into a cloud-based environment supporting parallel execution allowed a large US corporation improve the performance 100 times! Watch Recording

Java API for Decision Service Invocation

OpenRules Decision Manager deploys decision models as cloud-based decision services such as AWS Lambda with “one-click“. In this post I will explain how to invoke deployed OpenRules services from any Java application. There are at least 3 options:

  • Using the standard Java HttpURLConnection
  • Using DecisionServiceClient API
  • Using automatically generated API

You can try to run all three options using the sample decision project “VacationDaysLambda” included in the standard OpenRules installation. Continue reading

Rules-based Service Orchestration

OpenRules provides business users with abilities to build and deploy operational decision microservices. Now we empowered business users with an ability to assemble new decision services by orchestrating existing decision services independently of how they were built and deployed. The service orchestration logic is a business logic too, so it’s only natural to apply the decision modeling approach to orchestration. In this post I will explain how to orchestrate different services by creating a special orchestration decision model that describes under which conditions such services should be invoked and how to react to their execution results.

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DecisionMicroservices.com

Recently OpenRules, Inc. registered the domain “DecisionMicroservices.com“. Why did we do it? Because OpenRules Decision Manager dramatically simplifies the creation and maintenance of Operational Decision Microservices! Since we made the first SaaS Rule Engine available in AWS Marketplace on March 3, we experience a strong increase in the number of downloads and requests from the existing customers and prospects who want to develop their domain-specific Decision Microservices. Continue reading

Packaging Decision Models into an Executable JAR

OpenRules business decision models can be deployed as a RESTful web service with a single click effectively utilizing SpringBoot and Maven – read how to do it here. In this post we will describe how you can package a business decision model into an executable JAR-file that can be deployed on the local server and tested from POSTMAN or Java. Continue reading

OpenRules SaaS Rule Engine

This month OpenRules Decision Manager became the first SaaS Rule Engine available in AWS Marketplace. It gives our customers an opportunity to execute OpenRules-based decision services using a “Pay-As-You-Go” pricing model. You may read the Press Release approved by the AWS Marketplace team.  Using your AWS account, you can now subscribe to our AWS SaaS Subscription that allows you to pay a minimal fee for only what you actually use with all charges coming from Amazon AWS Marketplace. Continue reading

Deploying Decision Models as RESTful Web Services and Docker Containers

OpenRules Decision Manager can be deployed a business decision models as a RESTful web service that accepts HTTP requests at your local or remote server and produces with proper responses in the JSON format. As usual, you create and test your decision model in Excel and then simply add the property  “spring.boot=On”  to the file “project.properties”. Then you only need to double-click on the provide file “runLocalServer.bat” (the same for all models). Continue reading