Automated system for real-time monitoring and troubleshooting of UI applications in production

Abstract

Automated system (100) for real-time monitoring and troubleshooting of UI applications in production, comprising: a user interaction tracker configured to capture and log user actions, including clicks, keystrokes, scrolling, and navigation; a fault detection module that identifies UI crashes, unresponsive elements, and performance issues in real time; a session replay module that records and visualizes user interactions to accurately reproduce problems; a performance monitoring module that monitors user interface responsiveness, loading times, and latency to detect slowdowns; an AI-based debugging module that analyzes error patterns and suggests automatic solutions; an automated alerting system that provides real-time notifications of critical UI errors; a cross-platform compatibility framework that supports web, mobile, and desktop applications.

Description

[0001] The present invention relates to an automated monitoring and troubleshooting system for UI (User Interface) applications in production environments. More specifically, it is a system that tracks user interactions, detects anomalies, and provides real-time insights to optimize problem identification and resolution.

[0002] As web and mobile applications become increasingly complex, ensuring their stability, usability, and performance in real-world production environments has become a critical challenge. Bugs, UI inconsistencies, and performance bottlenecks can negatively impact the user experience, leading to customer dissatisfaction, lost revenue, and increased support costs. Traditional debugging and monitoring methods have several limitations, including delayed problem detection, limited visibility into user actions, difficulty reproducing errors, manual log analysis, and high downtime for problem resolution. Many software issues are only discovered after users report them, making troubleshooting time-consuming and inefficient.Existing monitoring tools primarily focus on backend performance and often fail to capture UI interactions and anomalies in real time.

[0003] To address these challenges, an automated real-time monitoring and debugging system is needed that continuously tracks user actions, detects anomalies, and provides insights into user interface behavior. Such a system should automatically log UI errors, crashes, and performance degradations, while also capturing session replays and event timelines to help developers accurately reproduce issues. By integrating AI-driven analytics, the system can proactively detect issues, suggest possible root causes, and minimize manual intervention through automatic debugging recommendations and alerts. Implementing this solution would significantly reduce problem resolution time, improve the user experience, and increase software reliability to ensure seamless and efficient UI performance in production environments.

[0004] To solve this problem, the present invention provides an automated system (100) for real-time monitoring and troubleshooting of UL applications in production.

[0005] The system continuously monitors and logs user actions within the user interface to detect anomalies, errors, or unexpected behavior.

[0006] The system automatically identifies and logs UI errors, crashes, and performance bottlenecks, reducing the dependence on manual troubleshooting.

[0007] The system analyzes logged events, recognizes patterns, and suggests possible root causes and solutions to resolve problems faster.

[0008] The system records session replays and event timelines so developers can reproduce and investigate issues with high accuracy.

[0009] The system continuously monitors user interface responsiveness, load times, and other performance metrics to ensure optimal application performance in production.

[0010] The system warns in real time about critical errors, performance degradations and unusual user behavior, enabling rapid intervention and resolution.

[0011] The system is designed to integrate into existing software development, testing, and DevOps pipelines, enabling efficient debugging and monitoring workflows.

[0012] In one embodiment, an automated system for real-time monitoring and troubleshooting of UI applications in production is provided. The system provides an automated real-time monitoring and troubleshooting solution for UI applications in production environments. It continuously tracks user interactions, detects anomalies, and identifies performance bottlenecks to ensure smooth application performance. Traditional debugging methods rely on manual log analysis and post-mortem debugging, which are time-consuming and inefficient. To overcome these challenges, the system integrates UI-assisted analysis, event logging, and automated debugging to improve problem detection and resolution.

[0013] In one embodiment, the system captures and logs UI events, errors, and crashes in real time, allowing developers to analyze user interactions and detect abnormal behavior. It includes session replay and event visualization capabilities that enable developers to accurately and efficiently reproduce issues. Furthermore, the system continuously monitors key performance metrics such as UI responsiveness and load times to proactively detect and address performance degradations. By leveraging AI-driven insights, it can suggest potential root causes and recommend solutions, significantly reducing problem resolution time.

[0014] In one embodiment, the system increases software reliability, reduces problem resolution time, and improves the overall user experience by automating tracing, troubleshooting, and performance monitoring. The invention is explained again below with reference to the figure. It shows: Fig. : A block diagram of an automated system for real-time monitoring and troubleshooting of UL applications in production.

[0015] Fig.shows a block diagram of an automated system for real-time monitoring and troubleshooting of UI applications in production. The system is designed to continuously track user interactions, detect anomalies, and provide real-time insights to optimize problem identification and resolution. By integrating UI-enabled analytics, event logging, and automated debugging mechanisms, the system increases the efficiency of software maintenance and improves the user experience. Conventional debugging methods often rely on post-mortem analysis and manual log inspection, making problem resolution time-consuming and inefficient. This invention overcomes these challenges by providing a proactive, automated, and intelligent debugging approach.

[0016] The system includes several key components, including a user interaction tracker that captures and logs user actions such as clicks, keystrokes, scrolling behavior, and navigation patterns. An error detection and logging module monitors the application in real time to detect UI crashes, unresponsive elements, script errors, and performance bottlenecks. A session replay and visualization module records user sessions and creates visual timelines of interactions to help developers accurately reproduce and diagnose issues. The performance monitoring module continuously tracks UI responsiveness, load times, resource consumption, and latency to detect performance degradations.In addition, an AI-powered debugging engine analyzes logged data, detects patterns, and correlates errors with user interactions to help developers determine the root cause of problems.

[0017] The system operates in real time, collecting user interaction data and monitoring system behavior. AI-driven models analyze this data to detect anomalies, such as UI element failures or slow response times. Once a problem is detected, the system automatically logs error details, captures stack traces, and maps affected UI components, reducing the dependence on manual debugging. Developers can access session replays to visualize the exact sequence of events that led to a problem, contributing to faster and more accurate resolution. Additionally, the system provides automatic alerts and reports that inform the development team about critical errors and enable proactive intervention before issues impact end users.

[0018] To improve troubleshooting efficiency, the system integrates machine learning algorithms that detect recurring patterns, classify errors according to their severity, and suggest possible solutions. Over time, the AI ​​component improves its accuracy, making error detection and resolution more effective. The system also provides insights for performance optimization, ensuring that user interface responsiveness and overall application performance remain at an optimal level. Designed for cross-platform compatibility, the system supports web, mobile, and desktop applications, making it versatile for different software architectures. It can be deployed in various environments, including cloud-based, on-premises, or hybrid solutions, ensuring scalability and adaptability for companies of all sizes.By automating tracking, troubleshooting, and performance monitoring, the system significantly reduces problem resolution time, increases software reliability, and improves the overall user experience in production environments. List of reference symbols 100 systems

Claims

[1] Automated system (100) for real-time monitoring and troubleshooting of UI applications in production, comprising: a user interaction tracker configured to capture and log user actions, including clicks, keystrokes, scrolling, and navigation; a fault detection module that identifies UI crashes, unresponsive elements, and performance issues in real time; a session replay module that records and visualizes user interactions to accurately reproduce problems; a performance monitoring module that monitors user interface responsiveness, loading times, and latency to detect slowdowns; an AI-based debugging module that analyzes error patterns and suggests automatic solutions; an automated alerting system that provides real-time notifications of critical UI errors; a cross-platform compatibility framework that supports web, mobile, and desktop applications. [2] The system of claim 1, wherein the AI-based troubleshooting engine uses machine learning algorithms to predict recurring problems and provide recommended fixes. [3] The system of claim 1, wherein the session replay module enables tracking of timestamped events so that developers can analyze the sequence of actions leading to errors. [4] The system of claim 1, wherein the error detection module categorizes problems based on severity and frequency and prioritizes critical errors for immediate resolution. [5] The system of claim 1, wherein the performance monitoring module continuously tracks frame rates, rendering times, and network latency to detect user interface slowdowns. [6] The system of claim 1, wherein the automatic alerting system provides customizable alert thresholds that ensure tailored notifications based on the severity of the problem. [7] The system of claim 1, wherein the cross-platform compatibility framework supports integration with third-party debugging tools and development pipelines. [8] The system of claim 1, wherein session replay data is encrypted to ensure user privacy and compliance with data protection regulations. [9] The system of claim 1, wherein UI-driven insights generate periodic reports detailing UI performance trends and potential optimization strategies.

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