New Major Release OpenRules-9: Happy Thanksgiving!

Our team worked hard to prepare a nice Thanksgiving gift for our customers, and today I am happy to announce general availability of OpenRules-9! This major new release comes with a new implementation of our Graphical Explorer and Debugger as a foundation for the current and future OpenRules Interactive Decision Modeling Environment oriented to business users. Watch new Intro Video and read Release Notes 9.0.0. Happy Thanksgiving!

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Extensible DMN

DMN is a modeling language and notation for the precise specification of business decisions and business rules using well-defined tabular formats. This popular standard even includes an interchangeable XML format. However, contrary to XML (eXtensible Markup Language), DMN can hardly be called extensible. Today’s DMN allows a user to define complex problem-specific decision modeling constructs using powerful FEEL boxed expressions (that still are being criticized as too close to programming).  But DMN doesn’t specify means for building simple domain-specific decision tables that look very natural for business users and hide complex implementation details that actually may require programming.

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Using a Decision Model for Orchestration of Decision Models

OpenRules empowers 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. OpenRules allows business analysts to create a special orchestration decision model that describes under which conditions such services should be invoked and how to react to their execution results. Link

Decision Modeling: Declarative vs Procedural

The ultimate objective of Business Decision Modeling:

A business analyst (subject matter expert) defines a business problem, and a smart decision engine solves the problem by finding the best possible decision.

Declarative decision modeling assumes that a business user specifies WHAT TO DO and a decision engine figures out HOW TO DO it. This is quite opposite to the Procedural approach frequently used in traditional programming.

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Business Rules and SQL: Competitors or Partners?

IEEE Spectrum just published the article “The Rise of SQL” about the recent SQL’s comeback caused not only by the ever-increasing use of databases, but also by the use of SQL within the fields of data science, machine learning, big data, and streaming systems. While traditionally, Business Rule Engines did not communicate with databases directly, our customers frequently prefer to use SQL-like business rules to access their data when it is necessary following their business logic. At the same time, they want to preserve the power of SQL dealing with databases of any complexity. Two years ago OpenRules introduced a special product “Rule DB” that does exactly this by empowering Excel-based business rules with a run-time RDBMS communication mechanism. In this post we will explain how to migrate an SQL query to OpenRules.

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Decision Models for Medical Claim Processing

DMCommunity.org Challenge May-2022 still has no submitted solutions. I knew that the problem is not as simple as it sounds because we, at OpenRules, have quite a few claim processing customers, whose decision models address similar and much more difficult problems. When I tried to create a decision model for this challenge, I quickly got a solution that still produced these errors while processing a test-claim:

[E71.313] cannot be reported together with [E72.3]
[E72.3] cannot be reported together with [E71.313]

But the challenge specifically required not to produce duplicate errors. Trying several decision modeling approaches, I built a few “tried-and-failed” decision models before I came up with two solutions which I feel comfortable enough to share here.

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Fast Live Support

OpenRules, Inc. offers fast support online sessions to help you to start working with OpenRules or to address your technical problem.  Upon your request, an OpenRules expert will send you an invite to a remote-support session addressing your particular problem by studying it together with you on your own computer. Anytime you also may order a paid fast-support service that costs only $60.00 USD for up to a 1 hour support session. Link

How Decision Tables work with Big Datasets

Decision tables is the most popular mechanism for representation of business logic – no wonder they play the major role in the DMN standard. However, when it comes to analyzing large amount of data, standard decision tables may not be the best way to do it. In this post, I’ll describe a much better approach implemented in OpenRules.

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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

OpenRules Debuggers

OpenRules Decision Manager provides two Decision Model Debuggers:

While the graphical debugger is the most user friendly debugger, it is currently available only under Windows and Linux. The Command Line Debugger is available under Windows, Mac, and Linux. Continue reading

RESTful Decision Services: Error Handling with OpenRules

Usually input validation is an essential part of business decision models created by OpenRules customers. They add rules that validate input decision variables for null values, empty strings, impossible values like Feb 29 during a non-leap year, and many other problem-specific input errors. These custom error reporting mechanisms usually generate lists of errors with explanations in the JSON response for RESTful decision services. However, while input errors are diagnosed by the decision service, its return code is usually 200 meaning it was a “good” request. In this post I will describe how your service may return code 400 for bad requests.

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Mitigating Log4J Security Vulnerability

On December 12, 2021 Apache Log4J 2.x reported that this widely used Java logging framework has been exposed to a serious security vulnerability. OpenRules Decision Manager like many other Java-based products uses Log4J. To mitigate this problem, we quickly switched to the recommended version 2.15.0 of log4j that was supposed to remove the above vulnerability. However, on December 14 the second vulnerability was discovered and Apache released the version 2.16.0 to address the problem.

Based on the seriousness of these events, we decided to create a new emergency release 8.4.3 of OpenRules Decision Manager that uses log4j version 2.16.0 (not 2.15.0). We’ve already built the first version 8.4.3 and it’s going through thorough testing. For urgent situations we made the evaluation version 8.4.3 available from here. Our team will continue to work hard to make sure that well-tested Release 8.4.3 will be available to all customers tomorrow morning. If you have any questions, please contact support@openrules.com.

Advancing AWS Lambda Decision Services

AWS Lambda has recently extended the capability to track the current state of a function through its lifecycle. In this post AWS wrote: “We’re extending the General Update from September 30 2021 to December 5 2021. The End of Delayed Update date is now also changed to December 6 2021.” With this change, all users of AWS Lambda need to update their AWS SDK-based automation workflows. How would it affect OpenRules-based decision services deployed as AWS Lambdas?

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Decision Services: Free POC Development

OpenRules Decision Manager becomes so powerful and easy to use that it dramatically reduces the efforts needed to develop new decision models and deploy them on cloud as decision microservices. Usually everything is done in Excel with our graphical Explorer without any coding. Along with development of large decision-making applications, our team has great practical experience of rapid creation of working prototypes or Proof of Concepts (POC). After a brief meeting with a customer, we quickly (usually within 1-3 days!) put together a POC tested locally and deployed on cloud, so the customer may start testing it remotely without any installations! Continue reading

OpenRules Release 8.4.2 improves Validation and Consistency Checking of Rule Repositories

Our customers will appreciate the new OpenRules Release 8.4.2 as it essentially improves the validation and consistency checking of their Rule Repositories. It provides much better error diagnostics in business friendly terms. In the Release 8.4.2 we actually implemented a new built-in compiler that runs during the BUILD phase (build.bat), so the majority of errors can be caught before Java code generation. We also added an ability to use CSV-files in situations when XLS-files are too big/slow to handle. We removed Maven Wrapper from all samples and made a free Apache Maven a pre-requisite. Release Notes

When to use Machine Learning, Optimization, and/or Business Rule Engines

Last week I listened the webinar “The Art of Knowing How to Leverage Decision Intelligence” presented by Roy Schulte, Distinguished VP Analyst at Gartner. Describing the major trends in decision intelligence and why it is growing, Roy concentrated on the question “when to use machine learning, optimization or business rule engines”:

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Using CSV Files in OpenRules

When it comes to handling large collections of data in business rules, OpenRules customers frequently use Excel-based DecisionData tables and/or decision tables of the type “BigTable“. It works fine when Excel tables contain thousands or even tens of thousands rows. However, when an Excel file contains hundreds of thousands rows Excel itself becomes much slower to search and requires much more time and memory to be downloaded in OpenRules. In this case we recommend our customers to switch from the Excel to the CSV format.

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Using DecisionData Tables in OpenRules

OpenRules Decision Manager provides all necessary tools to build, test, and debug your business decision models. The same people (subject matter experts) who created decision models can create test cases for these models using simple Excel tables or objects coming from the outside world (from Java, XML, or JSON). This post explains how to create and use test cases and data tables.

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Continuous Digital Decisioning

Modern enterprises quickly evolved from monolithic to microservices architectures and they naturally expect that rules-based decision services to be good citizens of the new CI/CD world. My DecisionCAMP-2021 presentation https://lnkd.in/g_rWAazF shares OpenRules experience of developing, integrating, and deploying operational decision microservices which satisfy the requirements of modern enterprise architectures including security, continuous integration and delivery/deployment. Using specific examples, it explains how business analysts may represent and maintain these requirements in their business decision models.
Keywords: Business Decision Models, Decision Microservice, Invocation Context, Authorized access, Security, CI/CD Watch

Titanic Booking Service

This is the name of the DMCommunity.org Aug-2021 Challenge that is supposed to predict survivors of the Titanic tragedy based on partially known actual results. Dr. Bob Moore has already submitted a very good analysis of this challenge and applied several ML-based approaches to solve it. It inspired me to ponder the same challenge from a bit different angle. I thought I could try two approaches: 1) using common sense or human prejudice-based rules to predict who could survive; 2) using our very simple Rule Learner to let ML algorithms to do the same. I spent almost the whole day today working on this problem, and this post describes what and how I did. It is interesting to compare the final results:

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Operational Decision Microservices in the CI/CD World

On Sep 14 I will present “Continuous Digital Decisioning or Operational Decision Microservices in the CI/CD World” at DecisionCAMP-2021. In this presentation we plan to share recent OpenRules experience of developing, integrating, and deploying operational decision microservices which satisfy the requirements of modern enterprise architectures including security, continuous integration and delivery/deployment. Here are two key slides:

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Securing OpenRules Decision Services

Release 8.4.1 of OpenRules Decision Manager is about “Securing OpenRules Decision Services” – click on this link to see the new tutorial that describes how to secure decision services using JWT Authentication and SSL communication. Release 8.4.1 also provides business users with an additional control over input and output of their decision models allowing them to validate incoming JSON requests and choose which decision variables to exclude from the produced responses. Read Release Notes

Glossary: Controlling Decision Model Input and Output

Glossary with UsedAs-properties

Being at the heart of any decision model, OpenRules Glossary uses columns “Variable Name”, “Business Concept”, “Attribute”, and “Type” to define all used decision variables. It is recommended to add the optional column “Description” with plain English descriptions of these variables.

Additionally, OpenRules 8.4.1 Glossary may include optional columns “Used As” and “Default Value” that allow you to effectively control the input and output of the decision model. It can be especially important when your decision model is deployed as a RESTful web service, and you want to validate the incoming JSON structure and decide which variables should be included in the outgoing JSON structure.

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Glossary at the Heart of the Decision Model

Any practical decision modeling tool allows a user to represent a business glossary that specifies all decision variables and thus is at the heart of any decision model. The DMN standard does not explicitly specify a glossary letting different implementation products to compete. So, the modern digital decisioning systems use different constructs to organize their glossaries. In this post and follow-ups I will describe how OpenRules deals with its most important tables of the type “Glossary” which are always the focal point of any decision modeling process.

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OpenRules Decision Manager 8.4.0

This new Release 8.4.0 is a response to practical needs of our large and mid-size customers. It essentially enhances deployment capabilities including:

Read Integration/Deployment, Release Notes, an updated User Manual for Developers, and try it from here.

Rules-based Machine Learning

The integrated use of Rule Engine and Machine Learning (ML) products becomes more and more popular. OpenRules Rule Learner is a good example of such integration. While there are plenty of powerful Machine Learning algorithms available off-the-shelf, it can be quite practical to use rules-based machine learning instead. The classical rules-based technology may address learning problems considering historical and constantly changing operational data. In such situations a “Rule Engine” plays a role of a “Rule Learner”. Here is a good example.

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OpenRules Growing Popularity

Since the beginning of 2021 OpenRules Decision Manager‘s popularity is growing at an unusually high pace. The last month our website had 33K visitors that is much more than traditional 20K visitors per month. We’ve already closed several very important deals this year, and now several other large customers have successfully completed their POCs building and deploying OpenRules-based decision microservices on their preferred clouds. Here are important factors that contribute to this success:

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Benchmarking Decision Service

For years many Rule Engine customers were satisfied with their performance as the majority of rule engines delivered in general good performance.  However, the picture changed dramatically in the last 3-4 years when the number of rules-based real-time transactions started to grow from hundreds of thousands or several millions to hundreds of millions per day. The typical execution time of 50-100 milliseconds per transaction what used to be considered as a good performance indicator is not sufficient anymore. Nowadays large customers require the performance that goes down to only a few milliseconds per transaction or in many cases under 1 millisecond. This real-world requirement along with the dramatic shift to cloud-based deployment was the main reason why two years ago we redesigned our Classic OpenRules product and built its new implementation known today as “OpenRules Decision Manager“.

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ProcessCon-21

Last week I was on the panel “Hyper Automation and the Convergence of #BPM, #RPA, #Rules, & #iPaaS” of the ProcessCon-21, a User Conference organized by our partner ProcessMaker. Together with leaders from UiPath, SnapLogic, and ProcessMaker we discussed the latest trends in low-cod/no-code development and much more. Watch Video. You may also check out this webinar “Building lightweight composable process applications using rules + workflow

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Rule Debugger for Business Users

Whether you like it or not, your business decision models will contain bugs like regular software always does. They will fail to produce expected results for certain inputs and under different unforeseen circumstances. As a result, their authors, who are usually business people, will have troubles to understand why certain rules were not executed while others did. For real-world business models even the best explanation reports and execution traces could be difficult to follow. When complex logical errors occur, decision model authors discover that their business rules and decision management environment is only as good as the rule debugging tools it offers! Continue reading

New Release 8.3.0 with Graphical Explorer

New OpenRules Decision Manager Release 8.3.0 comes with a Graphical Integrated Decision Modeling Environment called “Decision Model Explorer“. It automatically builds decision model diagrams, opens Excel files associated with different nodes, and allows business people to modify, test, and deploy their decision models from one place. Watch the video and read more. Join our free webinar on Feb 5, 2021 – register here. Continue reading

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

Text Interpolation in OpenRules

Many popular languages (e.g. Angular or Mustache) use text interpolation to incorporate dynamic string values into the text. OpenRules Decision Manager Release 8.2.1 gives our customers an option to use text interpolation by putting text decision variables in the double curly braces {{ and }}.  For example, see how it’s being used in the standard sample project “PatientTherapy”:

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Partnership with ProcessMaker

Today ProcessMaker and OpenRules announced a new partnership that provides our customers with an integrated business process and decision management solution. The partnership adds high performance decision services created in OpenRules and deployed as AWS Lambdas to business applications built with ProcessMaker. It unlocks a powerful new level of sophistication for process, workflow, and business rules designers around the globe. This webinar demonstrates an implementation of a loan origination process in ProcessMaker that utilizes complex decision services built in OpenRules. Read Press Release.

 

RuleDB.com – Accessing Database from Business Rules

Traditionally, Business Rule Engines do not communicate with databases directly and expect to receive input and provide output via intermediate objects defined in Java, JSON, or XML. However, our customers frequently prefer to use business-friendly rules defined in Excel instead of separately defined SQL statements. Our new product “Rule DB” does exactly this. In this post I will describe how it works using the MySQL Sample Database. 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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