Virtual Machine Reclassification via Resource Metrics Analysis
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Solution Overview
Problem
Cloud computing environments face inefficiencies in virtual machine usage, as actual usage by end users is not always optimized, leading to a desire to reclassify virtual machines based on resource consumption metrics to improve efficiency and utilization.
Innovation Solution
A virtual machine management tool analyzes resource consumption metrics to identify opportunities for reclassification, locating target virtual machines that can better support existing ones, and reassigning or reclassifying them to optimize user operation patterns and metrics, providing data for administrators to determine reclassification plans.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If virtual machines are reclassified based on code analysis of resources, then resource utilization efficiency is improved, but system complexity increases
Solution Approach 1:
The system performs automated code analysis on virtual machine resources to identify reclassification opportunities, allowing the system to self-optimize without requiring manual administrator intervention for each analysis step, thereby improving efficiency while managing complexity through automation
Solution Approach 2:
The system analyzes resource consumption metrics and usage patterns, then uses this feedback information to identify and execute reclassification opportunities, creating a closed-loop system that continuously improves resource utilization based on observed performance data
2Productivity
If virtual machines are reclassified to target virtual machines, then operational performance is enhanced, but migration time and effort increase
Solution Approach 1:
The system performs code analysis and identifies reclassification opportunities in advance, preparing migration plans before actual migration is needed, which reduces the time required when migration is executed and allows performance enhancement without urgent time pressure
Solution Approach 2:
The system creates target virtual machines as copies or templates before migrating source virtual machines, allowing for pre-validation and testing of the migration process, which reduces risks and potential rework time while enhancing operational performance
3Measurement precision
If code analysis is performed on virtual machine resources, then reclassification accuracy is improved, but computational overhead increases
Solution Approach 1:
The system extracts and analyzes only the necessary code elements and resource metrics required for reclassification decisions, rather than performing comprehensive analysis of all virtual machine components, thereby improving reclassification accuracy while minimizing unnecessary computational overhead
Solution Approach 2:
The system dynamically adjusts analysis parameters and depth based on virtual machine characteristics and current system load, allowing for high-precision analysis when needed while reducing computational overhead during normal operations, thus balancing accuracy with resource consumption
Data Source
AI summary
Embodiments relate to systems and methods for reclassifying a set of virtual machines in a cloud-based network. The systems and methods can analyze virtual machine data to determine performance metrics associated with the set of virtual machines, as well as target data to determine a set of target machines to which the set of virtual machines can be reassigned or reclassified. In embodiments, benefits of reassigning any of the set of virtual machines to any of the set of target virtual machines can be determined. Based on the benefits, the systems and methods can reassign or reclassify appropriate virtual machines to appropriate target virtual machines.