Automated Server Cluster Selection for VM Deployment
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Solution Overview
Problem
In virtualized environments, efficiently deploying virtual machines (VMs) across multiple server clusters while optimizing finite resources such as CPU and memory is challenging, as exceeding these limits can impact performance and lead to undesired consequences like service outages.
Innovation Solution
An automated server cluster selection process is implemented, where a VM deployment manager considers available CPU, memory, and network bandwidth resources, along with administrator-defined parameters like maximum host failures and resource allocation ratios, to efficiently select and provision VMs across multiple server clusters, ensuring optimal resource utilization and high availability.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If VMs are deployed across multiple server clusters to optimize resource utilization, then resource efficiency improves, but the complexity of selecting the appropriate cluster increases
Solution Approach 1:
The system automatically evaluates multiple server clusters and selects the most suitable one for VM deployment based on predefined criteria (CPU availability, memory capacity, network bandwidth, host failure tolerance). This self-service mechanism eliminates manual intervention, resolving the complexity of multi-cluster selection while maximizing resource utilization efficiency.
Solution Approach 2:
The patent transforms the complex multi-cluster selection problem into a parameter-based evaluation system. By quantifying cluster characteristics (CPU, memory, network, failure tolerance) and comparing them against VM requirements, the system dynamically selects optimal clusters through parameter matching, simplifying the decision process while improving resource allocation efficiency.
2Reliability
If resource allocation is optimized to prevent service outages, then system reliability improves, but the complexity of monitoring and managing resources increases
Solution Approach 1:
The system performs preliminary evaluation of server clusters before VM deployment by assessing CPU availability, memory capacity, network bandwidth, and host failure tolerance. This advance preparation ensures that VMs are placed on clusters capable of maintaining service availability, preventing outages before they occur while managing complexity through automated pre-checks.
Solution Approach 2:
The patent implements a feedback mechanism where the system continuously monitors cluster resource status and performance metrics. Based on this feedback, the system dynamically adjusts VM placement decisions to maintain service availability, automatically responding to changing conditions without increasing operational complexity.
Data Source
AI summary
A device receives a virtual machine (VM) to be deployed, and identifies multiple network device clusters for possible VM deployment. The device applies a weighting parameter to at least one of the multiple network device clusters to favor selection of the at least one of the multiple network device clusters over other network device clusters. The device receives user selection of one or more network device clusters from the multiple network device clusters to generate a disabled group of network device clusters and an enabled group of network device clusters, wherein the disabled group of network device clusters excludes at least one of the multiple network device clusters. The device selects a network device cluster, from the enabled group of network device clusters, for deployment of the VM based on the weighting parameter applied to the at least one of the multiple network device clusters.