Integration Component Assessment Architecture
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Solution Overview
Problem
The complexity of integrating disparate applications in modern distributed computing systems, particularly with the rise of cloud migration and emerging technologies like IoT and blockchain, leads to inefficiencies and error-prone integration processes due to the manual selection of integration components.
Innovation Solution
A systematic approach using integration assessment architecture that determines suitable integration components by associating integration interface requests with key characteristics, fulfillment data, and integration policies, providing a user interface for component recommendations and selective deployment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of time
If manual selection of integration components is used, then flexibility in component choice is maintained, but time consumption and error rate increase
Solution Approach 1:
The system performs self-service by automatically determining integration components without human intervention. The processor autonomously receives integration interface requests, determines key characteristics, identifies candidate components, and selects optimal components based on predefined criteria, eliminating the need for manual selection and thereby reducing time consumption while maintaining operational simplicity
Solution Approach 2:
The manual mechanical process of component selection is replaced with an automated computational system. The processor executes algorithms that automatically analyze integration requirements, evaluate candidate components against key characteristics, and make selection decisions, substituting human manual operations with automated electronic processing to reduce time and errors
2Productivity
If automated determination of integration components is implemented, then time consumption and errors are reduced, but system complexity increases
Solution Approach 1:
The automated determination system is segmented into distinct functional modules: receiving integration interface requests, determining key characteristics, identifying candidate components, evaluating components against characteristics, and selecting optimal components. This segmentation allows each module to perform a specific function independently, managing overall system complexity while achieving high productivity through coordinated automated operations
Solution Approach 2:
The system introduces an intermediary processing layer between the integration interface request and the final component selection. This intermediary automatically determines key characteristics, identifies candidates, and evaluates suitability, acting as a mediator that automates the selection process to improve productivity while containing complexity within the intermediary layer rather than requiring complex manual procedures
Data Source
AI summary
Systems and methods include determination of an integration style of a first interface between two or more applications, determination of a first message flow of the first interface, the first message flow between two of the two or more applications and associated with an integration domain and the integration style, determination of a first one or more key characteristic values associated with the first message flow, determination of a plurality of integration components associated with the integration domain and the integration style, each of the determined plurality of integration components associated with fulfillment data of each of a plurality of key characteristic values, determination, for each of the plurality of integration components, of an integration score based on fulfillment data associated with the integration component for the first one or more key characteristic values, and determination of one or more of the plurality of integration components to implement the first message flow based on the determined integration scores.