Virtual Machine Network GUI for Log Visualization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Complex virtual machine networks generate large volumes of log data, making it difficult for system administrators to identify the root cause of issues due to the use of codes or abbreviations that require translation, which is time-consuming and often results in missing important information.
Innovation Solution
A graphical user interface is provided that displays information related to a virtual machine network using a chart with error indicators organized in rows and columns, allowing for quick visualization and filtering of log data entries based on entities and their states, reducing the reliance on administrator experience and creativity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Quantity of substance
If log data entries use codes or abbreviations to reduce file size, then the quantity of log data that can be stored and reviewed is improved, but the ease of understanding and analyzing the log data deteriorates due to translation requirements
Solution Approach 1:
The patent introduces a graphical user interface as an intermediary layer between the administrator and the log data. The GUI translates the coded log entries into visual representations (charts, graphs, color-coded indicators) that convey the meaning of log data without requiring the administrator to read or translate the actual coded entries. This mediator enables easy understanding while preserving the ability to handle large volumes of log data.
Solution Approach 2:
The patent replaces the mechanical process of reading, translating, and manually analyzing text-based log entries with an automated visual system. Instead of administrators manually parsing and translating coded log data, the system automatically generates visual representations that directly communicate the state of virtual machines and hosts, substituting human cognitive processing with automated graphical processing.
2Measurement precision
If system administrators manually review and translate entire log files to find root causes, then the measurement precision of problem identification is improved, but the loss of time increases due to the extensive translation and review process
Solution Approach 1:
The patent extracts the essential information from the log data and presents it in a visual format that highlights only the relevant elements. By taking out the critical state information (such as VM operational status, host health indicators) and presenting it graphically, the system enables administrators to quickly identify root causes without needing to translate or review every detail of the underlying log files.
Solution Approach 2:
The system performs preliminary processing of log data by automatically generating visual representations before the administrator needs to analyze the data. The graphical interface pre-processes the log information, organizing it into meaningful visual patterns and highlights, so that when the administrator views the interface, the root cause information is already prepared and visible, eliminating the need for time-consuming manual translation and review.
3Ease of operation
If log data is filtered by log data entry types or time only, then the ease of operation for reviewing logs is improved, but the loss of information increases because filtering cannot limit entries to just problem-related items
Solution Approach 1:
The patent implements a dynamic filtering mechanism that automatically adjusts the displayed log data based on the current state of virtual machines and hosts. The graphical interface dynamically identifies and highlights entries related to problems based on real-time status information, so the filter adapts to the specific situation rather than using static criteria. This enables easy operation while ensuring that only relevant information is displayed.
Solution Approach 2:
The system uses feedback from the visual interface to improve filtering accuracy. When administrators interact with the graphical display, the system learns which visual elements correspond to actual problems and refines its filtering accordingly. The feedback loop between the visual representation and the filtering mechanism ensures that the system progressively improves its ability to distinguish problem-related entries from normal operations, maintaining both ease of operation and information relevance.
Data Source
AI summary
A graphical user interface for displaying information related to a virtual machine network is disclosed. In an embodiment, a non-transitory computer-readable storage medium stores instructions that, when executed by a computer, enable a graphical user interface to be displayed. The graphical user interface displays information related to a virtual machine network and includes a chart having error indicators organized in rows and columns, wherein an error indicator corresponds to an entity in the virtual machine network at a time and indicates a state of the entity at that time.