Error Management Compute Device For Integration Analytics
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Solution Overview
Problem
Conventional large-scale computer systems face inefficiencies due to errors arising from imperfect integration of new or modified components, making it difficult to determine the presence and magnitude of errors.
Innovation Solution
A system comprising an error management compute device that captures, analyzes, and manages errors by subscribing to error topics in an event stream, obtaining error data from various sources, and providing visual representations and analytics to identify and rectify errors.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If new or modified components are integrated into the existing system to accommodate changing needs, then the system's adaptability is improved, but the presence and magnitude of processing errors increase and become difficult to determine
Solution Approach 1:
The system performs preliminary error detection and classification by subscribing to error topics in the event stream before errors propagate through the system. Error data is captured and analyzed in real-time, allowing proactive identification of integration errors before they cause significant processing issues.
Solution Approach 2:
The system implements continuous feedback by monitoring error topics in the event stream and providing visual representations of error analytics. This feedback loop enables real-time observation of error patterns and magnitudes resulting from component integration, allowing teams to assess the impact of changes immediately.
2Reliability
If manual identification and rectification of processing errors is performed, then error resolution is achieved, but significant inefficiencies occur in the system
Solution Approach 1:
The system enables self-service error management by automatically capturing, analyzing, and visualizing error data from the event stream. Error analytics are generated automatically, providing teams with actionable insights without requiring manual error identification, thus maintaining error resolution while eliminating manual inefficiencies.
Solution Approach 2:
The system replaces manual mechanical error identification processes with automated computational analysis. By substituting human manual inspection with automated error data capture and analytics generation, the system resolves errors more efficiently while maintaining reliability.
3Adaptability or versatility
If continual changing of components is performed to enable the institution to operate, then the system's adaptability is improved, but processing errors increase and require manual rectification
Solution Approach 1:
The system implements a universal error management approach that handles errors from any component integration through a single centralized mechanism. By subscribing to error topics in the event stream and providing unified visual analytics, the system manages errors from diverse sources through one multi-functional platform, reducing overall complexity.
Solution Approach 2:
The system introduces an intermediary error analytics layer between component integration and error resolution. This intermediary captures error data from the event stream, performs automated analysis, and presents unified error information, simplifying the complex task of managing errors from continual component changes.
Data Source
AI summary
Technologies for providing enhanced management of processing errors include a compute device. The compute device includes circuitry configured to obtain error data indicative of errors resulting from integration of a component configured to add functionality to a data processing system of an institution. The compute device is also configured to perform statistical analysis on the obtained error data to produce error analytics data and produce a visual representation indicative of the error analytics data to enable efficient remediation of the errors.