Dynamic Computing Resource Allocation Service
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Solution Overview
Problem
Existing systems face challenges in efficiently managing and allocating computing resources across distributed networks, particularly in ensuring that requests for computing capacity are fulfilled with appropriate parameters and priorities, while also allowing for reallocation based on changing demands.
Innovation Solution
A rule-based allocation system that considers multiple parameters such as priority, resource specifications, location, and availability time, enabling late-binding allocation of computing resources like servers or virtual machines, which can be reallocated as needed to higher priority requests.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual allocation of computing resources is used, then flexibility in handling individual requests is improved, but tracking and ensuring proper consideration of all parameters across multiple requests becomes difficult
Solution Approach 1:
The system implements automated tracking and monitoring of computing resource requests, allocating resources based on priority levels and parameters. The allocation service maintains records of requests and their fulfillment status, providing feedback loops that ensure proper consideration of all parameters while reducing manual tracking burden.
2Productivity
If computing resources are allocated to meet current demands, then resource utilization is improved, but the ability to reallocate resources to higher priority requests becomes limited
Solution Approach 1:
The system employs dynamic resource allocation where computing resources are not permanently assigned but continuously reevaluated based on changing priority levels and demands. The allocation service can reallocate resources from lower priority to higher priority requests, maintaining optimal resource utilization while adapting to varying operational needs.
3Ease of operation
If multiple requests with different priorities are processed manually, then individual request considerations are improved, but the complexity of managing multiple parameters increases
Solution Approach 1:
The allocation service acts as an intermediary between multiple requests and computing resources, automatically managing priority levels and parameters. This intermediary system handles the complexity of coordinating multiple requests with different requirements, reducing the burden on manual management while ensuring proper consideration of each request's specific parameters.
Data Source
AI summary
Disclosed are various embodiments relating to fulfillment of requests for computing capacity. Multiple requests for allocating computing resources for customers are obtained. Each request specifies an availability time at which the computing resource is to be made available to the customer, a device parameter to select a type of computing device to provide the computing resource, a location parameter to select a location where the computing resource is to be physically located, and/or other parameters. The computing resources are allocated to the customers according to one or more allocation rules, the availability times, device parameters, location parameters, and/or other parameters.