Ring Topology Interface for Datacenter Entity Visualization
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Solution Overview
Problem
Existing systems fail to effectively monitor and visualize the complex relationships between physical and virtual entities in modern datacenters, lacking the capability to understand new architectures and interconnections, which hinders comprehensive monitoring and troubleshooting.
Innovation Solution
A datacenter management system that uses a ring topology user interface to represent virtual and physical entities, along with a natural language search engine and collaboration features, to visualize and manage datacenter entities, and a data collection and analytics engine to capture and analyze performance and configuration data, enabling detailed visualization and search capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If existing monitoring systems are used to track datacenter entities, then basic monitoring is provided, but the systems fail to effectively visualize complex relationships between physical and virtual entities
Solution Approach 1:
The system segments the complex datacenter environment into distinct entity types (physical entities, virtual entities, logical entities) and represents them as separate nodes in a graph structure. This segmentation allows the system to manage and visualize complex relationships by breaking them down into manageable entity-node relationships rather than attempting to display all connections in a single complex view.
Solution Approach 2:
The patent transitions from traditional flat monitoring views to a multi-dimensional graph visualization where entities are represented as nodes and relationships as edges in a ring topology. This dimensional change enables the system to display complex interconnections between physical and virtual entities across multiple layers (infrastructure layer, virtualization layer, management layer) simultaneously, providing comprehensive relationship visualization without overwhelming complexity.
2Adaptability or versatility
If traditional monitoring approaches are used, then simple entity tracking is achieved, but the systems cannot understand new architectures and relationships
Solution Approach 1:
The graph-based entity relationship system provides a universal framework that can represent multiple entity types (physical servers, virtual machines, storage devices, network components) and their relationships within a single unified model. This multi-functional approach allows the system to adapt to various datacenter architectures and configurations while maintaining consistent monitoring and visualization capabilities across different entity types and relationship structures.
Solution Approach 2:
The system dynamically adapts to changing datacenter architectures by allowing entities and relationships to be added, removed, or modified in the graph structure. As new virtualization technologies, storage architectures, or network configurations are introduced, the system automatically updates the entity relationship model to reflect these changes, maintaining accurate representation without requiring complete system reconfiguration.
3Loss of information
If comprehensive data collection is implemented, then detailed entity information is captured, but the complexity of searching and analyzing this data increases
Solution Approach 1:
The graph structure serves as an intermediary between comprehensive data collection and user-friendly search capabilities. By organizing collected entity data into a structured graph with defined nodes and edges, the system enables efficient traversal and query operations. Users can search for specific entities or relationships without dealing with the full complexity of the underlying data, as the graph structure provides natural pathways for navigation and analysis.
Solution Approach 2:
The system segments the large volume of collected entity data into discrete, manageable nodes and relationships within the graph structure. This segmentation allows for targeted queries and analysis of specific entity types or relationship patterns without requiring processing of the entire dataset, thereby maintaining ease of operation while preserving comprehensive information.
Data Source
AI summary
A computerized visualization system includes a computer system management system that provides modeling of a computer system having physical entities and virtual entities and a computer display screen having rendered thereon an arrangement of active icons corresponding to physical and virtual entities included in the computer system, the icons being arranged in concentric circular rings having arc segments corresponding to physical host computers.