Hypervisor Selection for Virtual Machine Image Deployment
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Solution Overview
Problem
Current VM image placement methods in cloud computing environments lack efficiency in matching applications with suitable hypervisors based on characteristics, leading to suboptimal performance and stability.
Innovation Solution
A method and system for selecting a hypervisor by determining application characteristics, creating a VM image, and deploying it to a hypervisor with similar attributes, utilizing a hypervisor selection module to identify and direct the deployment within a cloud computing cluster.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If VM images are deployed to hypervisors without characteristic matching, then deployment speed is improved, but performance and stability deteriorate
Solution Approach 1:
The system performs preliminary analysis of application characteristics and hypervisor profiles before deployment, creating matching criteria in advance. This allows the deployment process to quickly identify suitable hypervisors without compromising performance, as the matching logic is prepared beforehand rather than computed during deployment execution.
Solution Approach 2:
The invention changes the deployment approach from random or simple resource-based allocation to characteristic-based matching by analyzing and comparing application requirements with hypervisor capabilities. This parameter-based selection ensures that VM images are deployed to hypervisors with compatible characteristics, improving performance while maintaining deployment efficiency through automated comparison algorithms.
2Device complexity
If VM images are deployed without hypervisor selection based on characteristics, then deployment complexity is reduced, but resource utilization efficiency deteriorates
Solution Approach 1:
The system enables self-service deployment by automatically analyzing application characteristics, comparing them with hypervisor profiles, and selecting appropriate targets without manual intervention. This automation maintains low deployment complexity while significantly improving resource utilization efficiency, as the system autonomously optimizes placement decisions based on characteristic matching.
Solution Approach 2:
The invention implements feedback mechanisms where deployment decisions are based on analyzed characteristics of both applications and hypervisors. The system continuously evaluates matching criteria and adjusts deployment choices accordingly, ensuring optimal resource utilization while keeping the process automated and simple to operate.
3Adaptability or versatility
If applications are deployed to heterogeneous hypervisor environments, then system versatility is improved, but performance optimization deteriorates
Solution Approach 1:
The system applies local quality by matching specific application characteristics with corresponding hypervisor capabilities rather than using uniform deployment rules. This allows each application to be deployed to a hypervisor with locally optimized characteristics, maintaining performance optimization while supporting diverse application types and hypervisor environments through customized matching criteria.
Data Source
AI summary
Embodiments of the present invention provide a method, system and computer program product for selecting a hypervisor for hosting a virtual machine (VM) image. In an embodiment of the invention, a method of selecting a hypervisor for hosting a VM image can include selecting an application for inclusion in a VM image, determining characteristics of the application and creating a VM image with the selected application. The method also can include identifying a hypervisor hosting a different VM image with an application having in common at least a portion of the determined characteristics. Finally, the method can include deploying the created VM image to the identified hypervisor. Of note, the deployment of the created VM image can be to an identified hypervisor in a node of a cloud computing cluster.