SPA Event Correlation for Accurate Virtual Page Transition Metrics
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Solution Overview
Problem
Traditional performance metric monitoring techniques are inadequate for Single Page Applications (SPAs) due to their changed loading behaviors, leading to inaccurate metrics and difficulties in connecting the chain of events and cause and effect across disparate systems.
Innovation Solution
Implementing an application intelligence platform with agents installed at individual machines to monitor and analyze application performance, using dynamic baselines and configurable thresholds to identify issues, and perform anomaly detection, thereby correlating cause-based events with virtual page transitions in SPAs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If traditional performance metric monitoring techniques are used for SPAs, then the monitoring system remains simple and compatible with conventional web pages, but the performance metrics become inaccurate and cannot properly track virtual page transitions
Solution Approach 1:
The patent segments the monitoring approach by introducing virtual page view concepts that divide the monitoring of SPA transitions into discrete, trackable units. Each virtual page view is associated with specific XHR requests and events, allowing precise measurement of performance metrics for individual page transitions rather than treating the entire SPA as a single unit.
Solution Approach 2:
The patent introduces an intermediary monitoring layer that sits between the SPA application and the performance monitoring system. This intermediary captures and correlates XHR requests, events, and virtual page view transitions, enabling accurate performance tracking without requiring changes to the core SPA application logic or browser infrastructure.
2Adaptability or versatility
If conventional agents monitor web application performance data in browsers, then the agents maintain simplicity and broad compatibility, but they fail to keep up with newer loading behaviors of SPAs and report inaccurate metrics
Solution Approach 1:
The patent implements dynamic monitoring that adapts to SPA loading behaviors by tracking virtual page view transitions and correlating them with XHR requests in real-time. The system dynamically adjusts its monitoring approach based on the detected SPA architecture, identifying causal relationships between events and page transitions that conventional static monitoring cannot capture.
Solution Approach 2:
The patent incorporates feedback mechanisms where the monitoring system continuously observes XHR requests, events, and virtual page view transitions, then uses this feedback to refine its performance measurements. By analyzing the causal relationships between events and page transitions, the system provides accurate feedback on SPA performance that accounts for the unique loading behaviors of single-page applications.
3Loss of information
If data is collected across disparate systems and tools in network architecture, then comprehensive monitoring coverage is achieved, but it becomes difficult to piece together monitoring data and connect the chain of events and cause and effect
Solution Approach 1:
The patent merges previously disparate monitoring data sources by correlating XHR requests, events, and virtual page view transitions within a unified monitoring framework. This integration allows the system to piece together the complete chain of events and cause-effect relationships across what were previously separate data streams, providing a cohesive view of SPA performance.
Solution Approach 2:
The patent introduces an intermediary correlation layer that connects disparate monitoring data sources. This intermediary captures XHR requests, events, and virtual page view transitions from different parts of the system and correlates them based on causal relationships, making it possible to trace the complete chain of events from user interaction through XHR requests to virtual page transitions without requiring direct integration of all underlying systems.
Data Source
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AI summary
In one embodiment, a monitoring process detects one or more events capable of causing a future state change in a browser application having initially loaded a single page application (SPA) page, and maintains one or more causality chains of the one or more events, each causality chain tracing events of that causality chain to a respective root cause event of that causality chain. Upon detecting a virtual page transition to create a new virtual page, the monitoring process may determine that a cause of the virtual page transition matches a particular root cause event of a particular causality chain, and correlates all events of the particular causality chain to the new virtual page (e.g., where events may notably include XHRs). In another embodiment, the monitoring process may further set a start time of the particular root cause event as the start time of the new virtual page.