Dynamic Weighted Variables for VM Provisioning
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Solution Overview
Problem
Current techniques for determining where to provision virtual machines in cloud computing environments are inadequate, leading to inefficient load balancing and requiring manual intervention by administrators to ensure resource availability.
Innovation Solution
A system that dynamically assigns weights to resources within virtual machine clusters based on utilization thresholds, allowing for automated identification of available clusters for provisioning, using a provision manager, resource determiner, availability analyzer, and availability reporter to ensure proper resource allocation.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If current techniques are used to determine where to provision virtual machines based on virtual machine memory configuration and server capacity, then provisioning can be performed, but load balancing is inaccurate and requires manual intervention
Solution Approach 1:
The system changes the parameters used for provisioning decisions from simple memory configuration and server capacity to a comprehensive set of weighted variables including resource utilization metrics, availability thresholds, and dynamic weighting factors. This allows automated provisioning while achieving accurate load balancing by continuously evaluating multiple parameters rather than relying on static configurations
Solution Approach 2:
The system implements feedback mechanisms by continuously monitoring resource utilization across clusters and using this information to dynamically adjust provisioning decisions. The availability analyzer evaluates current cluster states and feeds this information back into the provisioning process, enabling both automation and accuracy through iterative optimization
2Reliability
If administrators manually disable, analyze and enable multiple servers to ensure load balancing, then load balancing can be achieved, but productivity and efficiency are reduced
Solution Approach 1:
The system enables self-service provisioning by automatically performing the functions that previously required manual administrator intervention. The provision manager autonomously evaluates cluster availability, selects appropriate targets for provisioning, and executes the provisioning process without human involvement, thereby maintaining reliable load balancing while dramatically improving productivity
Solution Approach 2:
The system replaces the mechanical manual process of disabling, analyzing, and enabling servers with an automated software-based provisioning system. This substitution eliminates the need for physical or manual intervention while maintaining the essential function of achieving load balancing across the infrastructure
3Ease of operation
If simple resource metrics are used for provisioning decisions, then the process is simple, but resource availability assessment is inaccurate
Solution Approach 1:
The system achieves a universal approach by creating a multi-functional evaluation framework that simultaneously considers multiple resource types (compute, storage, network), multiple clusters, and multiple weighting scenarios. This universal framework maintains ease of operation through standardized processes while improving measurement precision by comprehensively assessing all relevant resources across the entire infrastructure
Data Source
AI summary
Systems, methods and computer program products for provisioning a virtual machine are disclosed. A request to provision a virtual machine is received. Resources are identified and utilization of the resources determined for each cluster of the plurality of virtual machine clusters, the resources comprising internet protocol (IP) addresses, memory and CPUs. The availability of clusters is analyzed based on the determined resource utilization for each cluster. The analysis includes assigning dynamic weights to resources of each cluster and calculating an availability of each cluster. A cluster availability report is output indicating an availability status for each virtual machine cluster. A system for provisioning a virtual machine includes a provision manager, a resource determiner, an availability analyzer and an availability reporter.