System Simulation and Abnormality Detection
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Large enterprise organizations face difficulties in identifying and resolving abnormalities in legacy applications due to the lack of triage capabilities, which complicates understanding the impact on upstream and downstream systems.
Innovation Solution
A computing platform is used to simulate scenarios for multiple applications, detect abnormalities, and automatically resolve issues by executing commands or notifying administrators if necessary, utilizing machine learning for pattern recognition and resolution.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If system simulation is implemented to detect abnormalities in legacy applications, then abnormality detection capability is improved, but system complexity increases
Solution Approach 1:
The patent introduces a simulation environment as an intermediary layer between the legacy application and the analysis system. This simulation environment receives commands from the system, executes them in a controlled virtual setting, and returns results without directly modifying the legacy application. This mediator approach enables abnormality detection while isolating the complexity from the legacy system itself.
Solution Approach 2:
The patent creates a simulated copy of the legacy application's behavior and environment. Instead of analyzing the complex legacy application directly, the system generates simulated scenarios that replicate its operations. This copying approach allows abnormality detection by comparing simulated behavior against expected patterns, reducing the complexity burden on the original system.
2Productivity
If automated resolution commands are executed to fix abnormalities, then productivity is improved, but risk of system errors increases
Solution Approach 1:
The patent executes resolution commands first in the simulated environment to verify their effectiveness and safety. Only after confirming that the command successfully resolves the abnormality in simulation does the system apply it to the deployed application. This preliminary testing approach enables rapid automated resolution while minimizing the risk of introducing new errors to the production system.
Solution Approach 2:
The system continuously monitors the deployed application after executing resolution commands and compares actual behavior against expected outcomes from simulation. This feedback mechanism allows the system to verify that automated resolutions are working correctly and to detect any unintended side effects, thereby maintaining system stability while achieving high productivity in issue resolution.
Data Source
AI summary
Arrangements for simulation generation and abnormality detection are provided. In some examples, a computing platform may identify a plurality of applications for analysis. The computing platform may execute a plurality of simulated scenarios for each application and, based on execution of the simulated scenarios, the computing platform may capture abnormality results for each application. The abnormality results, as well as application information and/or simulated scenarios may be stored. In some examples, the computing platform may compare deployed versions of each application to the captured abnormality data to identify an abnormality in a deployed version of an application. Based on the identified abnormality, the computing platform may evaluate the identified abnormality to determine whether it can be resolved automatically. If so, the computing platform may execute one or more commands modifying the deployed application to resolve the abnormality.