On-Demand Computing Cluster Allocation via Self-Service Portal
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Solution Overview
Problem
Users face challenges in accessing large computing resources for tasks like data enrichment jobs, as they are often not readily available on personal or enterprise-issued systems, and the allocation of shared computing resources within enterprises can be cumbersome and delayed.
Innovation Solution
A system that allows users to define and allocate clusters of computing resources on-demand through a user interface, enabling access to computing resources from their local workspace, with options for one-time or recurring use, and automatically deallocating resources after task completion.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If computing resources are allocated through enterprise IT personnel based on usage footprint and term, then resource allocation follows established policies, but the process is cumbersome and adds delay
Solution Approach 1:
The system pre-configures computing resource templates with defined usage footprints and terms, allowing users to select from pre-approved configurations. This preliminary preparation enables rapid deployment while maintaining policy compliance, as the templates are预先 designed to meet enterprise requirements.
Solution Approach 2:
Users can independently allocate computing resources through self-service portals without requiring IT personnel intervention. The system automatically validates requests against enterprise policies and provisions resources accordingly, eliminating manual approval delays while ensuring policy adherence.
2Reliability
If computing resources are reserved in advance for users, then resources are available when needed, but the reservation process is cumbersome and resources may remain idle
Solution Approach 1:
The system dynamically provisions computing resources based on real-time user requests rather than maintaining static reservations. Resources are allocated on-demand and automatically released when tasks complete, providing reliability without requiring complex advance reservation processes or risking idle resource consumption.
3Reliability
If enterprises maintain excess computing resources for peak demand, then resource availability is ensured, but resource utilization efficiency decreases
Solution Approach 1:
The system creates a shared computing resource pool that serves multiple users and workloads simultaneously. Computing resources are dynamically allocated to different users based on demand, allowing the same physical infrastructure to fulfill multiple functions and serve peak demands across different user groups without requiring each user to maintain dedicated excess capacity.
4Ease of operation
If users access computing resources on personal systems, then flexibility is improved, but access to large computing resources is limited
Solution Approach 1:
The system introduces a virtualization layer that bridges user personal systems and enterprise computing resources. Users can launch and manage computing clusters remotely through web interfaces or command-line tools, maintaining operational flexibility while accessing large-scale computing capacity that would be impossible to provision on personal devices.
Data Source
AI summary
The present disclosure relates to a flexible computing resource cluster allocation system and method, wherein a user who needs to complete a task which requires an amount of computing power, may define a cluster of computing resources to complete the task via a local workspace. Clusters may be created in a computing platform (related to the enterprise or provided by a third party) according to the defined configuration details. A cluster may be created for a single task which is to be completed one time. After the task is complete, the resources that make up the cluster may be de-allocated automatically, and therefore returned to the platform to be available to be reallocated to another user. A user may also create recurring task that requires a certain amount of computing resources on a repeating basis.