Composable Infrastructure Workload Deployment via Resource Allocation Master List
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Solution Overview
Problem
Current computing systems face inefficiencies in managing and reallocating resources for workloads due to limitations in identifying and utilizing available resource devices effectively, leading to suboptimal performance and compliance with security and data compliance rules.
Innovation Solution
A method and system that utilize a resource allocation master list to identify and allocate available resource devices based on workload specifications, monitor latency, and ensure compliance by initiating configuration and redeployment as needed, while maintaining security and data compliance through virtual certificates and ledger entries.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If resource devices are allocated based on traditional methods, then workload deployment is achieved, but resource utilization efficiency is suboptimal
Solution Approach 1:
The system performs preliminary actions by maintaining a resource allocation master list that pre-identifies and catalogs available resource devices before workload deployment requests arrive. This advance preparation enables rapid matching of workloads to suitable resources without ad-hoc searching, thereby improving resource utilization efficiency and reducing resource wastage through proactive resource management.
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring the status of resource devices and updating the resource allocation master list in real-time. This feedback loop ensures that the system has current information about resource availability and performance, enabling informed allocation decisions that optimize resource utilization and prevent resource wastage.
2Productivity
If resource devices are identified and allocated manually, then deployment is achieved, but system complexity and time consumption increase
Solution Approach 1:
The resource allocation master list is prepared in advance, containing pre-identified available resource devices with their specifications and status. When a workload deployment request arrives, the system can immediately query this pre-prepared list and perform rapid matching based on workload specifications, eliminating the time-consuming process of manual resource identification and significantly improving deployment efficiency.
Solution Approach 2:
The system enables self-service deployment by allowing workload requests to automatically query the resource allocation master list and receive suitable resource allocations without manual intervention. The management module autonomously performs the matching and allocation process based on predefined criteria, reducing both system complexity and time consumption associated with manual resource management.
3Reliability
If resource allocation is performed without centralized tracking, then simplicity is maintained, but compliance with security and data rules cannot be ensured
Solution Approach 1:
The resource allocation master list serves multiple functions simultaneously: it tracks resource availability, stores resource specifications, enables compliance verification, and supports allocation decisions. This multi-functional approach ensures security and data rule compliance without requiring separate complex tracking systems, as the master list becomes a universal repository that handles both operational and compliance requirements in a unified manner.
4Productivity
If available resource devices are not systematically identified, then system simplicity is maintained, but resource utilization efficiency decreases
Solution Approach 1:
The system performs preliminary identification and cataloging of available resource devices by maintaining the resource allocation master list, which pre-stores information about resource status, specifications, and availability. This advance organization enables efficient resource utilization without requiring complex real-time identification systems, as the groundwork is already laid out in the master list for rapid querying and matching.
Solution Approach 2:
The resource allocation master list acts as an intermediary data structure that simplifies the complexity of resource identification. Instead of directly querying complex resource management systems or performing real-time analysis, the system uses the master list as a simplified interface that pre-processes and organizes resource information, making resource identification straightforward while maintaining high utilization efficiency.
Data Source
AI summary
A method for managing data includes obtaining, by a management module, a redeployment request, wherein the redeployment request specifies a first workload and workload specifications for a second workload, and in response to the redeployment request: identifying, using a resource allocation master list, a plurality of resource devices, wherein each resource device in the plurality of resource devices is in an available status, selecting, from the plurality of resource devices, a first resource device based on the workload specifications, initiating a configuration of the first resource device, and updating the resource allocation master list to specify an allocation of the first resource device to the second workload.