Virtual Machine Cost Efficiency Analysis System
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Solution Overview
Problem
IT managers in private clouds face challenges in determining which virtual machines (VMs) to run internally and which to move to public clouds to optimize costs, as they need to compare the cost efficiency of VMs against industry averages and receive recommendations for cost-effective resource allocation.
Innovation Solution
The system computes a cost efficiency metric for each VM in a private cloud by comparing its costs with similar VMs in the same cloud, public clouds, and benchmark private clouds, using clustering and market share data to identify cost-effective relocation opportunities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If VMs are run in a private cloud to maintain control and security, then reliability and security are improved, but cost efficiency deteriorates
Solution Approach 1:
The system continuously monitors and compares the cost efficiency of VMs running in the private cloud against public cloud pricing and benchmark private cloud data. This feedback mechanism generates actionable recommendations that allow IT managers to optimize cost efficiency while maintaining the security and control benefits of private cloud infrastructure.
Solution Approach 2:
The system changes the parameter of cost efficiency by comparing multiple factors including private cloud VM costs, public cloud equivalent costs, and benchmark private cloud costs. This multi-parameter analysis enables dynamic decision-making about VM placement to optimize cost efficiency without compromising security or control.
2Loss of energy
If VMs are moved to public cloud to reduce costs, then cost efficiency is improved, but control and security are worsened
Solution Approach 1:
The system segments the cloud infrastructure into private cloud, public cloud, and benchmark private cloud components. This segmentation allows IT managers to selectively migrate specific VMs to public cloud based on cost efficiency analysis while keeping critical VMs in the private cloud to maintain control and security, thus resolving the contradiction between cost efficiency and reliability.
3Measurement precision
If comprehensive cost comparison data is collected from multiple clouds and benchmarks, then measurement precision is improved, but device complexity is worsened
Solution Approach 1:
The system introduces an intermediary cost efficiency analysis platform that automatically collects, normalizes, and compares pricing data from private cloud, public cloud, and benchmark private cloud sources. This intermediary handles the complexity of multi-source data integration and processing, providing precise cost efficiency measurements without burdening IT managers with the underlying system complexity.
Data Source
AI summary
Methods and systems to compute cost efficiency of virtual machines (“VMs”) running in a private cloud are described. Methods and systems compute a cost efficiency value for each VM in the private cloud based on cost of the VM in the private cloud, cost of similar VMs in the private cloud, price of similar VM running in the public cloud, and the cost of similar VMs running in one or more private clouds in the same geographical area. When the cost efficiency of a VM is greater than a cost efficiency threshold, the methods generate an alert and recommendations for moving the VM to a lower cost public cloud.