Proactive Monitoring Tree with Severity Sorting
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing performance-monitoring tools in cloud-based computing systems do not provide an effective way to diagnose performance problems in virtualized environments, where bottlenecks can arise at both virtual-machine and host-system levels, making it difficult to identify and resolve issues.
Innovation Solution
A proactive monitoring tree system is introduced, which visualizes performance information hierarchically, allowing users to navigate and understand relationships among virtual machines and host systems through a user interface that aggregates performance metrics, compares them against thresholds, and displays performance states using colors, enabling easy identification of bottlenecks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If performance-monitoring tools display all performance data for virtual machines and host systems, then complete performance information is provided, but the complexity of the interface and difficulty of identifying problems increases
Solution Approach 1:
The performance monitoring interface is segmented into a hierarchical tree structure with multiple levels (data center, cluster, host, virtual machine). Users can navigate through these segments to view performance data at different granularities, displaying complete information while maintaining interface simplicity through progressive disclosure.
Solution Approach 2:
The patent adds a hierarchical dimension to the performance monitoring interface. Instead of displaying all data in a flat structure, performance metrics are organized across multiple hierarchical levels, allowing complete information to be presented in an structured, navigable format that reduces perceived complexity.
2Loss of information
If performance data for multiple entities is displayed simultaneously, then comprehensive monitoring is achieved, but the ability to quickly identify bottlenecks decreases
Solution Approach 1:
The patent applies color-coding to visual indicators representing performance states of entities. Different colors indicate different performance levels (e.g., green for normal, yellow for warning, red for critical), enabling users to quickly identify bottlenecks and problem areas while maintaining comprehensive monitoring coverage across multiple entities.
Solution Approach 2:
The interface applies different visual properties to different entities based on their performance states. Each entity's visual indicator is customized according to its specific performance condition, allowing users to quickly distinguish problematic entities from normal ones while monitoring all entities comprehensively.
3Measurement precision
If detailed performance metrics are displayed for all entities, then complete diagnostic information is provided, but the time required to analyze performance data increases
Solution Approach 1:
The system pre-calculates and pre-processes performance metrics, organizing data in advance according to the hierarchical structure. Performance states are determined beforehand and visual indicators are prepared, so when users access the interface, diagnostic information is already organized and ready for immediate analysis, reducing diagnosis time while maintaining measurement precision.
Solution Approach 2:
The interface allows dynamic adjustment of the level of detail displayed. Users can expand or collapse nodes in the hierarchical tree to view detailed performance metrics only for specific areas of interest, rather than displaying all details simultaneously. This dynamic control enables complete diagnostic information to be available on demand while reducing analysis time through selective disclosure.
Data Source
AI summary
The disclosed embodiments relate to a system that displays performance data for a computing environment. During operation, the system first determines values for a performance metric for entities that comprise the computing environment. Next, the system displays the computing environment as a tree comprising nodes representing the entities and edges representing parent-child relationships between the entities. While displaying the tree, the system displays the child nodes for each parent in sorted order based on values of the performance metric associated with the child nodes.