Hardening Rule Data Object Version for Smart Deployment
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Solution Overview
Problem
The existing decision services face inefficiencies in updating rule data object specifications, leading to unnecessary resource consumption and downtime, as they often require updating to the latest version even if older versions of the specifications are sufficient for rule execution.
Innovation Solution
The implementation of a 'hardened' rule data package that determines the minimum required version of the rule data object specification using an intelligent compute processor, which cleans up unused variables and data objects, and a smart deployer that automatically updates decision services to compatible versions without requiring user intervention.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If decision services are updated to the latest version of rule data object specification, then compatibility with new rules is improved, but unnecessary resource consumption and downtime increase
Solution Approach 1:
The system changes the version parameter from always using the latest version to using a determined minimum required version. The intelligent compute processor analyzes the rule package to identify the specific version parameters (data objects, variables, functions) actually used, then sets the RDO specification version to match exactly what is needed, avoiding unnecessary updates to newer versions that would consume additional resources.
Solution Approach 2:
The system extracts only the necessary components from the RDO specification that are actually required by the rule package. Instead of updating to the latest version which includes all new features, the intelligent compute processor identifies and extracts only the specific data objects, variables, and functions that the rule package depends on, then configures the decision service with just those extracted components.
2Adaptability or versatility
If decision services are updated to the latest version of rule data object specification, then compatibility with new rules is improved, but downtime increases
Solution Approach 1:
The system changes the version parameter from always using the latest version to using a determined minimum required version. The intelligent compute processor analyzes the rule package to identify the specific version parameters (data objects, variables, functions) actually used, then sets the RDO specification version to match exactly what is needed, avoiding unnecessary updates to newer versions that would extend downtime.
Solution Approach 2:
The system performs preliminary analysis of the rule package before deployment to determine the minimum RDO specification version required. The intelligent compute processor examines the rule package in advance, identifies the necessary version components, and pre-configures the decision service accordingly, so that when deployment occurs, no unnecessary updating is needed and downtime is minimized.
3Loss of energy
If unused variables and data objects are removed from rule data package, then resource usage is reduced, but complexity of determining compatible version increases
Solution Approach 1:
The system implements self-service through the intelligent compute processor, which automatically analyzes the rule package, identifies used and unused variables and data objects, determines the minimum required RDO specification version, and configures the decision service without human intervention. This automation handles the complexity internally while providing a simple interface to users.
Solution Approach 2:
The system replaces manual analysis and configuration processes with an automated intelligent compute processor. Instead of manually reviewing rule packages to determine compatible versions and removing unused components, the intelligent compute processor performs these tasks automatically using computational algorithms, substituting mechanical human effort with automated processing.
4Ease of operation
If manual updating of decision services is required, then control over updates is improved, but productivity decreases
Solution Approach 1:
The system implements self-service through the smart deployer, which automatically deploys the hardened rule data package to the decision service after the intelligent compute processor has determined the minimum required RDO specification version. The smart deployer handles the updating process without requiring manual user intervention, thereby maintaining control through automated decision-making while significantly improving updating speed and productivity.
Solution Approach 2:
The system performs preliminary determination of the minimum RDO specification version and preparation of the hardened rule data package before deployment. The intelligent compute processor analyzes and prepares everything in advance, so that when the smart deployer executes the deployment, the actual updating process is rapid and requires no manual intervention during the critical update window.
Data Source
AI summary
There are provided systems and methods for hardening of rule data object version for smart deployment. A service provider, such as an electronic transaction processor for digital transactions, may utilize different decision services that implement rules for decision-making of data including real-time data in production computing environments. Rules may correspond to coded statements that perform an automated decision-making service for the computing services and platforms of the service provider. When writing rules different variables for data objects are used, which are updated over time. Thus, a rule authoring application may be updated over time to have more and newer variables, which requires updating of the decision services. To optimize updating of the decision services when deploying new rules, the service provider may determine compatible versions of specifications for the variables. Thereafter, the service provider may determine whether a device service's variable specification requires updating.