Client-Side Logging for Enterprise App Diagnostics
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Solution Overview
Problem
Current methods for diagnosing issues with enterprise mobile applications are inadequate as customer service representatives cannot access all server logs, leading to either incomplete or overly extensive data transmission, which complicates troubleshooting and resolution processes.
Innovation Solution
A system and method that generates a deep link to mine specific logging data from a client device and transmit it to a server, allowing for targeted data collection and analysis to diagnose client-side issues efficiently.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If all runtime activities of the enterprise application are captured and transmitted to the remote server, then diagnostic completeness is improved, but data transmission volume increases and application performance deteriorates
Solution Approach 1:
The patent extracts only the necessary diagnostic information from the extensive runtime activities by implementing selective logging. The system captures specific events (login attempts, navigation actions, errors) while filtering out redundant data, thereby obtaining sufficient diagnostic data without transmitting the entire runtime activity log.
Solution Approach 2:
The logging system is segmented into different categories (login events, navigation events, error events, etc.). The system transmits only the relevant segments based on the diagnostic needs, rather than transmitting all runtime activities as a single large dataset.
2Reliability
If critical local errors are logged and transmitted to the remote server, then diagnostic capability is improved, but diagnostic comprehensiveness deteriorates
Solution Approach 1:
The system performs preliminary classification of log events into different categories (login, navigation, errors, etc.) before transmission. This preliminary organization allows the system to transmit comprehensive diagnostic information in a structured manner, ensuring both capability and comprehensiveness are maintained.
Solution Approach 2:
The logging system is designed to capture multiple types of events (login attempts, navigation actions, errors, performance metrics) within a single unified framework. This multi-functional approach ensures that diagnostic capability is maintained while comprehensiveness is improved by capturing diverse diagnostic information in one system.
3Loss of information
If comprehensive logging of all runtime activities is implemented, then diagnostic thoroughness is improved, but system complexity and processing requirements increase
Solution Approach 1:
Different logging and transmission strategies are applied to different event types based on their diagnostic value. High-priority events (errors, login failures) are logged and transmitted comprehensively, while low-priority events are summarized or excluded, reducing overall system complexity while maintaining diagnostic thoroughness for critical issues.
Data Source
AI summary
Systems and methods are provided for diagnosing an issue associated with an enterprise application on a client device by initiating a communication from the client device to a CSR device to report the issue, generating a matter identifier associated with the reported issue, transmitting a communication containing a deep link to the client device, invoking the deep link to initiate mining of logging data corresponding to the use of the enterprise application and stored locally on the client device, formatting and/or tagging the mined logging data with the matter identifier, transmitting the formatted mined logging data from the client device to the CSR device and/or a proprietary server, analyzing the mined logging data to diagnose a source of the reported issue, and attempting to resolve the reported issue based on the analysis of the mined logging data.