Capital one services, llc (20240345938). DISCOVERY CRAWLER FOR APPLICATION DEPENDENCY DISCOVERY, REPORTING, AND MANAGEMENT TOOL simplified abstract
Contents
DISCOVERY CRAWLER FOR APPLICATION DEPENDENCY DISCOVERY, REPORTING, AND MANAGEMENT TOOL
Organization Name
Inventor(s)
Muralidharan Balasubramanian of Gaithersburg MD (US)
Eric K. Barnum of Midlothian VA (US)
Julie Dallen of Vienna VA (US)
David Watson of Alexandria VA (US)
DISCOVERY CRAWLER FOR APPLICATION DEPENDENCY DISCOVERY, REPORTING, AND MANAGEMENT TOOL - A simplified explanation of the abstract
This abstract first appeared for US patent application 20240345938 titled 'DISCOVERY CRAWLER FOR APPLICATION DEPENDENCY DISCOVERY, REPORTING, AND MANAGEMENT TOOL
Simplified Explanation: The patent application describes techniques for monitoring the operating statuses of an application and its dependencies without requiring modifications to the underlying software.
Key Features and Innovation:
- Monitoring application collects and reports operating status of monitored application and dependencies.
- Problem service root cause analysis for unhealthy states.
- Dependency analyzer and discovery crawler for automatic configuration.
- Machine learning for performance pattern recognition.
- Testing response of monitored application through API call modifications.
Potential Applications: This technology can be applied in various industries such as IT, software development, and system monitoring.
Problems Solved: The technology addresses the need for efficient monitoring of application and dependency statuses without disrupting the underlying software.
Benefits:
- Improved monitoring capabilities.
- Automated configuration and updates.
- Enhanced performance pattern recognition.
- Efficient testing of application responses.
Commercial Applications: The technology can be utilized in IT companies, software development firms, and organizations requiring robust monitoring solutions.
Prior Art: Readers can explore existing patents related to monitoring software applications and dependencies for further research.
Frequently Updated Research: Stay informed about advancements in machine learning algorithms for performance analysis and monitoring software technologies.
Questions about Monitoring Software Applications: 1. How does the technology ensure accurate root cause analysis of unhealthy states? 2. What are the potential challenges in implementing machine learning for performance pattern recognition in monitoring applications?
Original Abstract Submitted
techniques for monitoring operating statuses of an application and its dependencies are provided. a monitoring application may collect and report the operating status of the monitored application and each dependency. through use of existing monitoring interfaces, the monitoring application can collect operating status without requiring modification of the underlying monitored application or dependencies. the monitoring application may determine a problem service that is a root cause of an unhealthy state of the monitored application. dependency analyzer and discovery crawler techniques may automatically configure and update the monitoring application. machine learning techniques may be used to determine patterns of performance based on system state information associated with performance events and provide health reports relative to a baseline status of the monitored application. also provided are techniques for testing a response of the monitored application through modifications to api calls. such tests may be used to train the machine learning model.
