Disaggregated Hardware Resource Discovery via Self-Describing Plugins
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Solution Overview
Problem
Data centers lack an automated solution to discover and manage the capabilities of disparate hardware components, as each type typically requires custom management applications and APIs, making it difficult to manage arbitrary hardware resources added or removed from the system.
Innovation Solution
Implementing a controller that queries a service processor to discover capabilities and obtain a uniform resource locator (URL) for additional information, allowing for the retrieval of management application plugins to manage and advertise the capabilities of hardware resources, using a self-describing RESTful API that facilitates identification, status querying, and monitoring.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If custom management applications and APIs are used for each hardware component type, then the hardware can be managed with specific capabilities, but the system complexity increases and automation becomes difficult
Solution Approach 1:
The patent implements a universal management application that can discover, identify, and manage multiple types of hardware components through a single interface. The system uses a common architecture with pluggable drivers that allow one management application to handle diverse hardware (storage devices, processors, memory) without requiring custom applications for each component type, thus reducing system complexity while maintaining adaptability.
Solution Approach 2:
The patent introduces an intermediary layer consisting of drivers and abstraction interfaces between the management application and hardware components. These drivers translate hardware-specific operations into standardized commands, allowing the management system to interact with various hardware types through a unified interface, thereby reducing complexity while preserving hardware-specific capabilities.
2Reliability
If manual discovery and configuration methods are used for hardware components, then system stability is maintained, but productivity decreases and automation is limited
Solution Approach 1:
The patent implements self-service capabilities where hardware components automatically advertise their presence and capabilities through standardized interfaces. The management system automatically discovers these components, identifies their types, and configures appropriate drivers without manual intervention, enabling automated resource provisioning while maintaining system stability through consistent discovery and configuration processes.
Solution Approach 2:
The patent establishes feedback mechanisms where hardware components report their status, capabilities, and health information back to the management system through standardized interfaces. This automated feedback loop enables the system to monitor hardware state, detect changes, and dynamically adjust resource allocation and management policies, improving productivity while maintaining reliability through continuous monitoring.
3Productivity
If a standardized discovery interface is implemented, then automation and productivity improve, but the ability to handle specialized hardware capabilities may be reduced
Solution Approach 1:
The patent segments the hardware management system into modular components: a standardized discovery interface, type-specific drivers, and capability abstraction layers. The standardized interface handles common discovery tasks, while specialized drivers handle hardware-specific capabilities. This segmentation allows automated discovery for standard operations while preserving support for specialized hardware through modular driver extensions.
Solution Approach 2:
The patent implements a dynamic driver loading mechanism where drivers are selected and loaded based on the discovered hardware type. The system starts with a standardized interface, discovers hardware characteristics, and then dynamically loads appropriate specialized drivers to handle specific capabilities. This dynamic adaptation allows the system to maintain high automation for common tasks while providing specialized support when needed.
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AI summary
Examples are described for computing resource discovery and management for a system of configurable computing resources that may include disaggregate physical elements such as central processing units, storage devices, memory devices, network input/output devices or network switches. In some examples, these disaggregate physical elements may be located within one or more racks of a data center.