Data Center Resource Heat Maps for Complex Monitoring
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Solution Overview
Problem
Managing network-based services is complex due to the large number of computing resources and components involved, making it difficult to visualize and correlate resources with large-scale events effectively.
Innovation Solution
A system and method for monitoring resource usage in data centers using heat maps that correlate quantitative metrics and grouping metrics, allowing users to visualize resource utilization and performance across distributed environments, enabling real-time monitoring and troubleshooting.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the number of computing resources and components in a data center increases to provide more network-based services, then service capacity and versatility improve, but system complexity and difficulty of visualization increase
Solution Approach 1:
The patent segments the complex data center infrastructure into hierarchical groups (data centers, availability zones, regions, accounts, organizations) that can be independently managed and visualized. This segmentation allows administrators to break down the overwhelming complexity into manageable segments while maintaining the ability to view the entire system through aggregated views.
Solution Approach 2:
The patent introduces a visual dimension through heat maps that overlay quantitative metrics (CPU utilization, memory usage, network traffic) onto the hierarchical structure of data center resources. This transforms abstract numerical data into spatial visual patterns, adding a visual dimension that makes complex multi-dimensional data comprehensible at a glance.
2Adaptability or versatility
If the number of resources in a data center increases to enhance service capabilities, then resource availability improves, but the ability to visualize and correlate resources with large-scale events deteriorates
Solution Approach 1:
The patent employs color-coded heat maps where different colors represent different ranges of quantitative metrics (e.g., green for low utilization, yellow for moderate, red for high). This color-coding system allows administrators to rapidly detect patterns, anomalies, and correlations across thousands of resources by visual inspection, transforming invisible numerical relationships into visible color patterns.
Solution Approach 2:
The patent merges multiple data dimensions (hierarchical structure, quantitative metrics, temporal trends) into a single integrated visual interface. The heat map combines structural hierarchy with performance metrics and event correlations in one view, allowing administrators to see relationships between resources and large-scale events without switching between multiple tools or screens.
3Measurement precision
If detailed monitoring of individual resources is implemented, then measurement precision improves, but system-wide visibility and correlation capability deteriorate
Solution Approach 1:
The patent creates a universal visualization interface that serves multiple functions simultaneously: it provides detailed monitoring of individual resources, aggregate views of system-wide status, correlation of events across hierarchies, and drill-down capability from overview to detail. This multi-functional interface eliminates the need to switch between different monitoring tools for different purposes.
Solution Approach 2:
The patent implements dynamic visualization where the level of detail displayed adapts based on user interaction. Administrators can drill down from high-level aggregate views to individual resource details, and the system dynamically adjusts the amount of information presented. This dynamic adaptation allows the same interface to provide both system-wide visibility and detailed monitoring precision as needed.
Data Source
AI summary
A system and method are disclosed for monitoring usage of resources (e.g., hosts, instances, applications, etc.) in a datacenter. Customers, developers and system administrators can collect and track metrics, gain insight, and react to keep applications and businesses running smoothly by providing system-wide visibility into resource utilization, application performance, and operational health. Users can programmatically retrieve monitoring data and view heat maps to assist in troubleshooting, spotting trends, and taking automated action based on the state of a cloud environment. Users can further monitor resources in real-time, so that metrics such as CPU utilization, latency, memory usage, transaction volumes, error rates, etc. can be visualized.