VM Placement Optimization via Resource Utilization Analysis
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Solution Overview
Problem
The challenge in cloud computing environments is the difficulty in efficiently assigning virtual machines to hosts due to varying resource consumption patterns and capacities, leading to suboptimal load balancing and increased infrastructure costs, which requires an automated process for optimal resource management.
Innovation Solution
An infrastructure management system and method that determines a new placement of virtual machines on hosts by analyzing resource utilization data, estimating guest operating system overhead, and iteratively refining placements to meet a threshold requirement, ensuring balanced resource consumption across hosts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If virtual machines are manually assigned to hosts, then assignment can be performed with simple processes, but the complexity and time consumption increase with the size and rate of change of resource consumption
Solution Approach 1:
The system enables automated self-service assignment where the infrastructure management system automatically determines optimal virtual machine to host assignments based on resource consumption patterns, eliminating the need for manual intervention while adapting to changing resource demands
Solution Approach 2:
The patent replaces manual mechanical assignment processes with an automated computational system that uses resource utilization data and algorithms to determine optimal placements, substituting human operation with automated mechanical/electronic systems
2Device complexity
If virtual machines are assigned to hosts without automated optimization, then infrastructure management is simpler, but load balancing and resource utilization become suboptimal
Solution Approach 1:
The system continuously monitors resource utilization data from virtual machines and hosts, using this feedback to dynamically adjust and optimize assignments, ensuring that load balancing and resource utilization improve based on actual system conditions
Solution Approach 2:
The system changes assignment parameters dynamically based on resource consumption patterns, adjusting which virtual machines are assigned to which hosts according to varying resource demands and available capacity, thereby optimizing productivity without permanent system complexity
3Productivity
If resource consumption patterns are not analyzed, then assignment processes are faster, but placement optimization and cost reduction are compromised
Solution Approach 1:
The system performs preliminary analysis of resource consumption patterns before making assignments, pre-processing resource utilization data to identify trends and requirements, enabling both accurate optimization and efficient execution of assignments
Data Source
AI summary
A system and method for reconfiguring a computing environment comprising a consumption analysis server, a placement server, an infrastructure management client and a data warehouse in communication with a set of data collection agents and a database. The consumption analysis server operates on measured resource utilization data to yield a set of resource consumptions in regularized time blocks, collects host and virtual machine configurations from the computing environment and determines available capacity for a set of target hosts. The placement server assigns a set of target virtual machines to the target set of hosts in a new placement. In one mode of operation the new placement is nearly optimal. In another mode of operation, the new placement is “good enough” to achieve a threshold score based on an objective function of resource capacity headroom. The new placement is implemented in the computing environment.