Virtual Computing Troubleshooting System with Ranked Cause Analysis
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Solution Overview
Problem
Conventional troubleshooting methods for virtual computing systems are inefficient, as they require users to manually sift through extensive data and explore numerous potential causes, leading to time-consuming and disruptive problem-solving processes, especially in large environments with thousands of components.
Innovation Solution
A troubleshooting system that receives search queries, parses them to identify relevant categories, determines possible causes, ranks them based on pre-determined criteria, and displays the highest ranked causes, guiding users directly to the most probable solutions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional troubleshooting methods are used where users manually sift through extensive data, then comprehensive problem analysis is achieved, but troubleshooting time and user effort increase significantly
Solution Approach 1:
The troubleshooting system automatically analyzes system data, generates possible causes, and ranks them without requiring manual user intervention. The system serves itself by autonomously processing logs, metrics, and event data to identify and prioritize potential issues, eliminating the need for users to manually sift through extensive data while maintaining comprehensive analysis.
Solution Approach 2:
The patent replaces the mechanical manual troubleshooting process with an automated computational system. Instead of users manually analyzing data, the system uses automated data processing, pattern recognition, and cause ranking algorithms to perform the analysis, substituting human effort with machine-based automated analysis that is both faster and equally comprehensive.
2Reliability
If users explore numerous potential causes manually, then thorough troubleshooting is achieved, but system disruptions increase
Solution Approach 1:
The system performs preliminary analysis by automatically generating and ranking possible causes before users need to investigate them. By pre-processing the data and organizing potential causes in order of likelihood, the system enables users to focus immediately on the most probable issues without needing to explore numerous potential causes manually, thereby reducing system disruptions.
Solution Approach 2:
The system extracts and isolates the most relevant possible causes from the vast amount of system data, presenting only the top-ranked candidates to users. This extraction process separates the critical information from the noise, allowing thorough troubleshooting to focus on a small subset of high-probability causes rather than requiring exploration of all potential issues, thus minimizing system disruptions.
3Ease of operation
If manual troubleshooting processes are used, then user control over the process is maintained, but troubleshooting efficiency decreases
Solution Approach 1:
The system dynamically adapts to user needs by allowing interaction with the ranked causes while maintaining automated efficiency. Users can review, filter, and explore the automatically generated causes in detail, preserving user control and ease of operation. Simultaneously, the automated generation and ranking processes maintain high troubleshooting efficiency by eliminating manual data sifting, creating a dynamic balance between user control and system efficiency.
Data Source
AI summary
A system and method include receiving, by a troubleshooting system of a virtual computing system, a search query for troubleshooting a problem associated with a component of the virtual computing system. The search query is received via a troubleshooting interface of the troubleshooting system. The system and method also include parsing the search query, including associating a troubleshooting category with the parsed search query, determining possible causes of the problem from the troubleshooting category, and ranking the possible causes based on a pre-determined criteria. The system and method additionally include displaying a subset of highest ranked possible causes of the problem on the troubleshooting interface.