Cloud Network Cost Catalog for Virtual Machine Deployment
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Solution Overview
Problem
In hybrid cloud environments, users are unaware of cheaper virtual machine image availability across different cloud providers, leading to increased operational costs, and lack the ability to analyze virtual machine images across multiple providers for cost-effective migration.
Innovation Solution
A system that identifies virtual machine images across multiple cloud networks, generates a catalog with mapping information including cost and feature tags, and analyzes this data to recommend the least cost cloud network for deploying virtual machine instances, thereby reducing operational costs.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If users deploy virtual machine instances on cloud networks without analyzing cost options across multiple providers, then deployment simplicity is maintained, but operational costs increase
Solution Approach 1:
The system performs preliminary analysis of virtual machine image availability and costs across multiple cloud networks before deployment decisions are made. By pre-generating catalogs and analyzing cost data in advance, the system enables informed deployment choices without adding complexity to the actual deployment process, thus reducing operational costs while maintaining ease of operation
Solution Approach 2:
The patent introduces an intermediary system that acts as a mediator between users and multiple cloud networks. This intermediary analyzes cost data, generates catalogs of available virtual machine images across different providers, and provides recommendations, thereby simplifying the user's task while optimizing for cost efficiency
2Loss of energy
If users analyze virtual machine images across multiple cloud providers to find cheaper options, then operational costs are reduced, but system complexity increases
Solution Approach 1:
The system performs self-service by automatically analyzing virtual machine image availability, generating catalogs, and identifying cost-effective deployment options across multiple cloud networks without requiring user intervention. This automation reduces operational costs while the systematic approach manages complexity internally rather than exposing it to users
Solution Approach 2:
The patent creates a universal catalog system that can analyze and compare virtual machine images across multiple different cloud providers through a single interface. This multi-functional approach consolidates what would otherwise require multiple separate analysis processes into one unified system, reducing operational costs while managing complexity through standardization
3Loss of energy
If comprehensive catalogs of virtual machine images across multiple cloud networks are generated and analyzed, then cost optimization is achieved, but information processing requirements increase
Solution Approach 1:
The system extracts only the essential information needed for cost optimization from comprehensive catalogs of virtual machine images across multiple cloud networks. By selectively extracting relevant cost data, availability information, and compatibility details while filtering out unnecessary information, the system achieves cost optimization without being overwhelmed by excessive information processing requirements
Data Source
AI summary
Virtual machine images available across a plurality of cloud networks may be identified. A catalog of the virtual machine images may be generated. The catalog may comprise, for each virtual machine image, a mapping information, comprising: a name of a virtual machine image, a name of a virtual machine instance based on the virtual machine image, a name of a cloud network providing the virtual machine image, a cost of deploying the virtual machine instance on the cloud network, a tag identifying a feature of the virtual machine image, and an identification tag assigned to the virtual machine image. For a given virtual machine instance, the catalog of the virtual machine images may be analyzed to identify a least cost cloud network.