Cloud-Based Deep Tracing for Proactive User Experience Monitoring
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Solution Overview
Problem
Conventional digital experience monitoring tools are reactive and lack the ability to obtain end-to-end data, providing limited insights for remedial actions and being snapshot-based, which hinders proactive issue resolution and performance optimization in cloud-based systems.
Innovation Solution
A cloud-based system that enables deep tracing by initiating a tracing session on user devices, performing multiple traces to a destination, collecting metrics, and displaying a network map between the user device and the destination, allowing for proactive troubleshooting and performance analysis.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If conventional EUEM tools focus on observations and snapshots in time, then implementation complexity is reduced, but measurement precision and continuous monitoring capability deteriorate
Solution Approach 1:
The system performs preliminary actions by proactively initiating tracing sessions and collecting performance data before issues manifest. The deep tracing capability is pre-configured to continuously monitor network paths, application performance, and user experience metrics, enabling early detection of performance degradation without waiting for reactive observations.
Solution Approach 2:
The invention implements continuous monitoring through persistent tracing sessions that continuously collect performance data across multiple time points. Instead of periodic snapshots, the system maintains ongoing traces of network traffic, application responses, and user interactions, ensuring uninterrupted visibility into system performance and enabling real-time anomaly detection.
2Ease of operation
If conventional DEM uses reactive data gathering techniques, then ease of operation is improved, but productivity and proactive issue resolution capability deteriorate
Solution Approach 1:
The system implements continuous feedback loops where performance data is constantly collected, analyzed, and used to trigger automated responses. The deep tracing mechanism provides real-time feedback on network performance, application health, and user experience metrics, enabling proactive identification and resolution of issues before they impact users. IT administrators receive continuous updates and can take corrective actions based on live data.
Solution Approach 2:
The system performs preliminary diagnostics and performance assessments continuously in the background, preparing diagnostic information and performance baselines before issues occur. This preliminary action enables rapid incident response by having pre-collected data and established performance thresholds ready for immediate comparison when anomalies are detected.
3Device complexity
If conventional tools provide limited end-to-end data visibility, then device complexity is reduced, but loss of information increases
Solution Approach 1:
The system segments the end-to-end user experience into multiple measurable components including network path performance, application server response, intermediate service performance, and client device metrics. Each segment is independently traced and monitored, allowing detailed analysis of specific failure points while maintaining overall end-to-end visibility. This segmentation enables precise identification of performance bottlenecks without requiring monolithic system complexity.
Solution Approach 2:
The invention introduces intermediary tracing components that capture and relay performance data from various system layers. These intermediaries include network probes, application agents, and service monitors that collect metrics at different levels and aggregate them into comprehensive end-to-end performance views. The intermediaries enable detailed information collection without directly increasing the complexity of core system components.
Data Source
AI summary
Techniques for deep tracing of one or more users via a cloud-based system include receiving a request from an administrator to actively troubleshoot a user; causing a user device associated with the user to create a deep tracing session based on the request; assisting the user device in performing one or more traces of a plurality of traces to a destination; receiving results from any of the plurality of traces and results from metrics collected at the user device; and displaying a network map between the user device and the destination.