Virtual Machine Pattern Management for Resource Optimization
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Solution Overview
Problem
Modern computing systems face inefficiencies due to poorly organized virtual machines, leading to suboptimal resource utilization and performance degradation, as users often create virtual machines haphazardly without proper management.
Innovation Solution
A method for managing virtual machine patterns by identifying resource utilization and requirements, consolidating applications onto optimized virtual machine patterns with appropriate resource allocations, using a rules engine to select the most efficient deployment configurations.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If virtual machines are created easily and haphazardly, then the ease of operation is improved, but the device complexity and resource utilization deteriorate
Solution Approach 1:
The system automatically analyzes resource utilization patterns, identifies consolidation opportunities, and executes virtual machine migrations without manual intervention. The pattern management module continuously monitors and self-optimizes the virtual machine deployment, eliminating the need for complex manual management while maintaining ease of operation.
Solution Approach 2:
The system dynamically changes deployment parameters by identifying patterns in resource utilization and automatically adjusting virtual machine placements. By monitoring CPU, memory, storage, and network usage patterns, the system transforms static deployments into dynamic, optimized configurations that adapt to changing conditions.
2Ease of operation
If virtual machines are created haphazardly, then the ease of operation is improved, but the resource utilization deteriorates
Solution Approach 1:
The system continuously monitors resource utilization metrics from virtual machines and uses this feedback to identify consolidation patterns. The pattern management module analyzes utilization data, detects optimization opportunities, and automatically executes migrations to improve resource efficiency while maintaining operational simplicity.
Solution Approach 2:
The system autonomously optimizes resource utilization by automatically analyzing patterns and executing consolidations without requiring manual intervention. This self-service approach maintains ease of operation while continuously improving resource efficiency through automated pattern recognition and deployment optimization.
3Ease of operation
If virtual machines are created haphazardly, then the ease of operation is improved, but the performance deteriorates
Solution Approach 1:
The system automatically monitors performance metrics, identifies degradation patterns, and executes corrective migrations without manual intervention. This self-service approach maintains ease of operation while continuously optimizing system performance through automated pattern recognition and deployment adjustments.
Solution Approach 2:
The system dynamically adjusts deployment parameters by monitoring performance patterns and automatically migrating virtual machines to optimize resource allocation. This transforms static, haphazard deployments into dynamic, performance-optimized configurations that adapt to changing system conditions.
4Ease of operation
If virtual machines are created haphazardly, then the ease of operation is improved, but the loss of time in management increases
Solution Approach 1:
The system autonomously performs management tasks including pattern analysis, optimization identification, and virtual machine migration without requiring manual intervention. This eliminates time-consuming manual management activities while maintaining ease of operation, as the system handles optimizations automatically.
Solution Approach 2:
The system continuously monitors and pre-identifies optimization patterns before they become critical issues. By proactively analyzing resource utilization and preparing optimization recommendations, the system reduces the time required for reactive management interventions.
Data Source
AI summary
Managing virtual machine patterns, including: identifying resource utilization of each virtual machine within a first virtual machine pattern having a first group of resources; determining resource requirements of one or more applications executing on one or more virtual machines within the first virtual machine pattern; based on the resource utilization and the determined resource requirements, identifying a second virtual machine pattern having a second group of resources; and deploying at least one of the one or more applications executing on the one or more virtual machines within the first virtual machine pattern onto one or more virtual machines of the second virtual machine pattern.


