Virtual Machine Pool Demand Management via Dynamic Thresholds

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Solution Overview

Problem

Managing virtual machine (VM) pool demand is challenging due to fluctuating resource requirements caused by changes in user numbers, resource usage, and business needs, making it difficult to determine when additional VMs or resources are needed to meet demand effectively.

Innovation Solution

A method and system that analyze VM usage data over time to determine demand, compare it to a threshold, and automatically request or provision additional VMs or resources based on trended demand forecasts, using a database to store and manage VM usage data and a VM monitoring tool to monitor and adjust resource allocation.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Adaptability or versatility

If a fixed pool of virtual machines is provisioned, then infrastructure cost is reduced, but the system cannot meet fluctuating demand effectively

Engineering Contradiction:

Improvedemand adaptabilityVSAvoidVM pool size

Core Design Contradiction:

Adaptability or versatilityVSQuantity of substance

Solution Approach 1:

The patent implements dynamic VM pool management where the system automatically adjusts the number of available VMs based on real-time demand monitoring. The pool transitions from a static fixed size to a dynamic size that expands during high demand periods and contracts during low demand periods, resolving the contradiction between adaptability and resource quantity

Inventive Principle:

Principle #15Dynamics

Solution Approach 2:

The system employs self-service automation through demand monitoring tools and automatic provisioning mechanisms. When demand thresholds are exceeded, the system automatically provisions additional VMs without manual intervention, and similarly deallocates VMs when demand decreases, enabling the pool to self-regulate its size according to actual needs

Inventive Principle:

Principle #25Self-service

2Reliability

If additional virtual machines are continuously provisioned to meet peak demand, then demand coverage is improved, but resource utilization efficiency decreases

Engineering Contradiction:

Improvedemand coverageVSAvoidresource utilization efficiency

Core Design Contradiction:

ReliabilityVSProductivity

Solution Approach 1:

The patent applies partial action by provisioning VMs only when and where needed based on actual demand thresholds. Instead of continuously maintaining maximum capacity, the system provisions additional VMs partially - only when demand exceeds predefined thresholds - thereby maintaining demand coverage while avoiding the waste of continuously running excess VMs during low utilization periods

Inventive Principle:

Principle #16Partial or excessive action

Solution Approach 2:

The system dynamically changes the parameter of VM pool size based on demand conditions. By monitoring utilization metrics and adjusting the pool size parameter in response to threshold crossings, the system ensures demand coverage is maintained when needed while optimizing resource utilization efficiency by reducing pool size during lower demand periods

Inventive Principle:

Principle #35Parameter changes

3Measurement precision

If manual monitoring and provisioning of virtual machines is performed, then control precision is maintained, but operational complexity increases

Engineering Contradiction:

Improvedemand measurement accuracyVSAvoidsystem complexity

Core Design Contradiction:

Measurement precisionVSDevice complexity

Solution Approach 1:

The patent implements feedback mechanisms where demand monitoring tools continuously measure VM pool utilization and provide this information to the provisioning system. This closed-loop feedback enables accurate demand measurement while automating the provisioning response, maintaining measurement precision without requiring manual monitoring complexity

Inventive Principle:

Principle #23Feedback

Solution Approach 2:

The system introduces intermediary automation components - demand monitoring tools and automatic provisioning systems - that mediate between raw demand data and provisioning actions. These intermediaries handle the complexity of continuous monitoring and decision-making, providing accurate demand measurement while shielding operators from operational complexity through automation

Inventive Principle:

Principle #24Intermediary (Mediator)

4Productivity

If virtual machine provisioning is delayed until demand exceeds capacity, then resource efficiency is improved, but service responsiveness deteriorates

Engineering Contradiction:

Improveresource efficiencyVSAvoidprovisioning speed

Core Design Contradiction:

ProductivityVSSpeed

Solution Approach 1:

The patent implements preliminary action by establishing demand thresholds that trigger proactive provisioning before capacity is completely exhausted. When monitoring tools detect that demand is approaching threshold levels, the system initiates VM provisioning in advance, ensuring service responsiveness is maintained while avoiding the waste of continuously over-provisioning resources

Inventive Principle:

Principle #10Preliminary action

Data Source

PatentUS10169070B1Managing dedicated and floating pool of virtual machines based on demand

Publication Date: 2019.01.01 UNITED SERVICES AUTOMOBILE ASSOCIATION (USAA)

AI summary

Methods, systems, and computer readable and executable medium embodiments for managing virtual machine pool demand are described herein. One method for managing virtual machine pool demand includes determining a demand for a number of virtual machines in a pool using data received, identifying the demand for the number of virtual machines in the pool is outside a threshold number, and sending a request for an additional virtual machine to a user to manage demand of the pool.