Cloud Node Resource Allocation Balancing
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Solution Overview
Problem
The challenge in cloud platforms is the generation of resource fragments due to unbalanced resource allocation, leading to reduced resource utilization rates, as existing methods either prioritize idle or saturated nodes without effectively addressing resource imbalance.
Innovation Solution
A method that involves determining a target node by calculating current resource allocation ratios and limits across multiple nodes to deploy newly added hosts, thereby balancing resource allocation and reducing fragment generation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If resource allocation is performed without considering balance across nodes, then deployment simplicity is improved, but resource utilization rate deteriorates due to fragment generation
Solution Approach 1:
The system performs preliminary calculation of resource allocation ratios and determination of target nodes before deploying newly added hosts. By pre-calculating the resource allocation state and identifying appropriate target nodes in advance, the system ensures balanced resource distribution from the outset, preventing fragment generation while maintaining deployment efficiency
Solution Approach 2:
The system continuously monitors and calculates resource allocation ratios across nodes, using this feedback information to dynamically determine optimal target nodes for new host deployment. This closed-loop approach ensures that resource allocation decisions are based on current system state, maintaining balance and preventing fragment accumulation
2Speed
If hosts are deployed to nodes with available resources without balance consideration, then deployment speed is improved, but resource allocation balance deteriorates leading to fragment generation
Solution Approach 1:
Before deploying hosts, the system pre-calculates resource allocation ratios and identifies target nodes that will maintain or improve allocation balance. This preliminary planning enables rapid deployment to pre-selected optimal nodes without requiring iterative adjustments, maintaining both speed and balance
Solution Approach 2:
The system uses resource allocation ratios as key parameters to determine target nodes. By changing the deployment decision based on these calculated ratio parameters, the system ensures that hosts are allocated to nodes where it will maintain balanced resource distribution, preventing fragment generation while enabling fast deployment
Data Source
AI summary
Embodiments of the present disclosure provide a resource processing method of a cloud platform and a related computing device. The cloud platform includes a plurality of nodes, and each node includes a first resource and a second resource. The method is performed by the computing device and/or a host manager in the cloud platform, and includes: obtaining a current first resource allocation ratio and a current second resource allocation ratio of each of the plurality of nodes; obtaining a first resource limit and a second resource limit that are required by a newly added host; determining, among the plurality of modes, a target node according to the current first resource allocation ratio and the current second resource allocation ratio of each node, the first resource limit, and the second resource limit; and deploying the newly added host in the target node.