Automated Virtual Machine Storage Selection
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Solution Overview
Problem
Manual intervention in selecting storage locations for virtual machines is unwieldy and error-prone, especially in large virtual infrastructures with numerous datastores.
Innovation Solution
A system that automatically selects a storage location for virtual machines based on pre-defined levels of service, using storage profiles that define metrics such as latency and cost, allowing for efficient provisioning without user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual intervention is used to select storage locations, then administrators can make informed decisions, but the process becomes unwieldy and error-prone in large infrastructures
Solution Approach 1:
The system performs automatic storage location selection without requiring administrator intervention. The virtualization infrastructure autonomously evaluates datastores against service level requirements and selects appropriate storage locations, eliminating manual effort while maintaining reliable decision-making through automated policy enforcement.
Solution Approach 2:
Service level requirements and storage policies are pre-configured before virtual machine provisioning. The system prepares evaluation criteria and datastore characteristics in advance, enabling rapid automatic selection during VM creation without ad-hoc manual analysis.
2Ease of operation
If automatic selection is implemented, then operational complexity is reduced, but the system must accurately evaluate multiple service level metrics
Solution Approach 1:
The evaluation system is segmented into distinct components: service level requirement definitions, datastore characteristic measurements, compliance evaluation logic, and selection algorithms. This modular architecture manages complexity by separating concerns while enabling comprehensive multi-metric evaluation.
Solution Approach 2:
The system evaluates multiple service level parameters (latency, cost, availability, performance) and transforms them into comparable compliance metrics. By standardizing diverse parameters into uniform evaluation criteria, the system handles complexity while maintaining automated operation.
3Productivity
If storage profiles with multiple metrics are used, then resource allocation is optimized, but the configuration and management becomes more complex
Solution Approach 1:
Storage profiles serve multiple functions simultaneously: they define service level requirements, establish evaluation criteria, store policy rules, and guide selection decisions. This multi-functionality consolidates what would otherwise be separate configuration systems into a unified profile framework.
Solution Approach 2:
Storage profiles are pre-configured with all necessary service level metrics and evaluation rules before provisioning operations. This preliminary setup eliminates the need for complex runtime configuration decisions, enabling efficient automated resource allocation based on pre-established criteria.
Data Source
AI summary
A computer-implemented method for automatically selecting a virtual machine storage location. The method includes receiving a selection of a level of service of a storage system for provisioning of a virtual machine; and responsive to receiving the selection of the level of service, automatically selecting a storage location for the virtual machine. The storage location is one of a plurality of storage locations compliant with the selected level of service.