Resource Pool Manager for Data Center Capacity Visibility
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Solution Overview
Problem
Business users in data centers face challenges in understanding system-specific capacity, performance, and health metrics across scattered hardware resources, requiring an efficient way to map these into high-level business views without needing to know the details of hardware or hypervisors.
Innovation Solution
A method involving a central data collector that aggregates hardware information from various devices, assigns unique identifiers, and maps this information to business resources, using a distributed model to create logical groupings and track assets, enabling administrators to manage resources and capacity effectively.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If hardware information is collected and mapped from scattered devices throughout the data center, then business users can obtain high-level business views of capacity and performance, but the complexity of managing and organizing hardware identifiers and information increases
Solution Approach 1:
The patent introduces a resource pool manager as an intermediary component that sits between the scattered hardware resources and the business users. This manager collects hardware information from various devices, organizes it into a unified resource pool view, and presents it to business users through a standardized interface. The intermediary abstracts the complexity of individual hardware devices while maintaining visibility into their capacity and performance, thus resolving the contradiction between information visibility and system complexity.
Solution Approach 2:
The patent segments the data center infrastructure into distinct resource pools (compute, storage, network) with each pool managing specific hardware types. This segmentation allows business users to view and manage resources in logical groupings rather than as a monolithic complex system. Each resource pool maintains its own identifier mapping and information organization, reducing the overall complexity while preserving comprehensive hardware visibility.
2Loss of information
If detailed hardware information is made visible to business users, then they can understand capacity and performance metrics, but they may become overwhelmed by technical details of hardware and hypervisors
Solution Approach 1:
The patent applies local quality by providing different levels of information abstraction to different user groups. Business users receive high-level resource pool views with capacity and performance metrics presented in business terms. Technical details about specific hardware devices, hypervisors, and configuration parameters are available only to administrators who need them. This localized information quality ensures business users understand capacity metrics without being overwhelmed by technical hardware details.
Solution Approach 2:
The patent adds an abstraction dimension between the physical hardware layer and the business user interface. Instead of presenting raw hardware identifiers and technical specifications directly to business users, the system creates a virtual resource pool layer that translates hardware metrics into business-relevant capacity and performance information. This dimensional transformation allows business users to understand and work with resource metrics without needing to comprehend underlying hardware complexity.
3Ease of operation
If resource pools aggregate hardware resources from multiple devices, then administrators can easily add, remove, and reorganize resources, but the difficulty of detecting and measuring individual hardware asset status increases
Solution Approach 1:
The patent implements preliminary action by assigning unique identifiers to hardware assets and pre-establishing their relationships with resource pools before resources are dynamically allocated or moved. When hardware devices are added to the data center, they are pre-registered with the resource pool manager, which stores their identifier mappings and capacity characteristics in advance. This preliminary identification and relationship establishment simplifies subsequent resource management operations and maintains accurate tracking of individual assets even as they move between pools.
Solution Approach 2:
The patent implements feedback mechanisms where the resource pool manager continuously monitors and collects status information from individual hardware assets within each resource pool. This feedback loop maintains real-time visibility into the health, capacity, and performance of individual devices while they are aggregated in logical pools. The system correlates individual asset status with pool-level metrics, enabling administrators to easily manage resources at the pool level while simultaneously tracking and detecting the status of individual hardware assets through automated monitoring and reporting.
Data Source
AI summary
Techniques for mapping and managing resources are presented. Hardware capacity and information is collected over multiple processing environments for hardware resources. The information is mapped to logical business resources and resource pools. Capacity is rolled up and managed within logical groupings and the information gathering is managed via in-memory and on-file caching techniques.