Web Data Flow Simulation for End-to-End Anomaly Detection
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Solution Overview
Problem
Conventional technologies fail to provide real-time end-to-end data propagation monitoring in web applications, leading to inadequate testing coverage, increased maintenance costs, and difficulty in identifying issues in complex systems, while lacking scalability and insights into data flow performance.
Innovation Solution
A web applications data flow simulation system that tracks data propagation between multiple web applications, creating a JSON object array to detect anomalies, and provides a 'data flow meter' for efficient issue diagnosis and real-time monitoring, enabling scalability and improved test coverage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If conventional technologies are used for web application testing, then development and maintenance proceed with standard tools, but testing coverage is inadequate and defects are difficult to detect in complex systems
Solution Approach 1:
The patent introduces an intermediary system that injects simulated data objects into the web application's data flow and intercepts responses from downstream systems. This intermediary approach enables comprehensive testing without requiring direct modification of the complex existing system architecture, thereby improving testing coverage while managing system complexity.
Solution Approach 2:
The patent creates copies of real data objects (JSON, XML, etc.) and injects them into the system for testing purposes. These simulated data objects replicate the structure and behavior of production data, enabling thorough testing of data propagation and anomaly detection without needing access to actual production data, thus enhancing testing coverage while maintaining system integrity.
2Measurement precision
If real-time data propagation monitoring is implemented, then data flow issues can be detected, but the system requires complex tracking and simulation infrastructure
Solution Approach 1:
The monitoring system uses an intermediary that positions itself in the data flow path to inject test objects and capture responses. This intermediary approach enables precise measurement of data propagation without requiring complex instrumentation throughout the entire system, achieving accurate monitoring with reduced infrastructure complexity.
Solution Approach 2:
The simulated data objects are designed to be universal and adaptable to multiple data types and formats (JSON, XML, etc.). This multi-functionality allows a single monitoring infrastructure to track diverse data flows across different systems and protocols, achieving comprehensive monitoring accuracy without proportionally increasing infrastructure complexity.
3Reliability
If comprehensive anomaly detection is performed across multiple web applications, then defects can be identified early, but the testing and monitoring overhead increases
Solution Approach 1:
The system uses simulated copies of data objects that replicate production data structures. These copies enable comprehensive anomaly detection across multiple web applications without requiring access to actual production data or systems, thereby improving defect detection capability while maintaining testing efficiency through isolated simulation environments.
Solution Approach 2:
The intermediary system implements feedback mechanisms that automatically analyze responses from downstream systems and identify anomalies. This automated feedback loop enables comprehensive monitoring across multiple applications without manual intervention, improving defect detection while maintaining testing efficiency through systematic automated analysis.
Data Source
AI summary
Methods, system, and non-transitory processor-readable storage medium for a web applications data flow simulation system are provided herein. An example method includes a web applications data flow simulation system that detects an event in a source web application, where a plurality of web applications comprises the source web application. The web applications data flow simulation system tracks propagation of data between the plurality of web applications in response to the event, to create a data propagation chain comprising a plurality of JavaScript Object Notation (JSON) objects in a JSON object array. The web applications data flow simulation system reports to the source web application an anomaly detected in the plurality of web applications caused by the event.