At DecisionCAMP-2020 we had a lot of discussions about the orchestration of the decision services and how to invoke different decision services when states of the business objects change over time. One of the most popular orchestration technique is a Pub/Sub architecture with State machines. The Challenge “Dynamic Loan Approval” is an example of perpetually running decision-making applications which should be able to learn from already executed transactions and evaluate new facts as they become available. This post describes how we implemented this application utilizing OpenRules-based GUI connected to AWS Lambda, EventBridge, SNS, and SQS. Continue reading
On June 30 I will present “Developing Decision Optimization Microservices for Real-World Decision-Making Applications” at DecisionCAMP-2020. Preparing my presentation, I thought about the major points I want to make. Of course, first of all, I want to demonstrate how to develop optimization services, but I also want to stress how the proposed approach helps to bring already great optimization tools into the everyday reality of business application development. Continue reading
There are already several good responses to the DMCommunity’s April-2020 Challenge “Doctor Planning”. Below I am describing how I tried to use this challenge to create a complete decision optimization service. I ended up with a working Worker Scheduler that shows a solution for this particular challenge in Fig. 1 (click to open):
OpenRules offers two open source products to support an integrated use of “Business Decision Modeling with Rule Engines and CP/LP Solvers“:
In this post I will describe how you can deploy decision optimization models as AWS Decision Microservices without programming or complex configuration. Continue reading
In these uncertain times, to do our part we want to help US businesses, especially health organizations to quickly make important operational decisions. OpenRules offers immediate assistance in creation and deployment of your decisions services on-cloud or on-premise.
- If you need a quick implementation of optimization decision services, we will help you to define and resolve your problem with the freely available Java Solver.
- If you need to quickly create a rules-based decision service and deploy it to AWS cloud, we will give you 3 months free access to our SaaS Rule Engine.
Contact us at email@example.com and we will setup a call to discuss how we can be in help. As the CTO at OpenRules, I’d allocate my personal time to help you with your urgent decision automation problems for free – email me directly at firstname.lastname@example.org.
OpenRules business decision models can be deployed as operational decision services utilizing the Serverless architecture provided by AWS. Deploying your decision models as AWS Lambda functions you don’t even think about servers and pay only for the execution time your services actually consume. Continue reading
OpenRules Decision Manager takes an Excel-based business decision model and converts it into highly efficient Java code. When you make changes to the business model, the code will be automatically re-generated, so we do not expect you to even look at this code. The authors of business decision models will always maintain their original models using mainly Excel.
OpenRules Decision Manager offers several integration and deployment facilities for converting your business decision models to operational decision services on-premise or on-cloud. We want you to be able to go through the deployment process without programming or complex configuration. This process should be easily repeatable as you will need to do it again and again when you modify your original business decision models. So, we tried to simplify the deployment process as much as possible. As our customers started to explore different deployment options, we plan to post several articles that describe these options in more details using the standard examples included into the OpenRules Decision Manager 8.1.1 installation.