Autonomic Virtual Machine Scaling via Cloud OS Thresholds

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Solution Overview

Problem

Current cloud computing environments require manual intervention by system administrators to scale virtual machines, leading to slow and complex processes that can result in poor user experience due to inadequate handling of varying workloads.

Innovation Solution

Implementing an autonomic scaling mechanism within the cloud computing environment, where the cloud operating system deploys and manages virtual machines based on predetermined thresholds, automatically adding or removing instances to adjust to workload demands without human governance.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Extent of automation

If manual scaling by system administrator is used, then control over hardware infrastructure is maintained, but scaling speed and complexity increase

Engineering Contradiction:

Improvescaling automationVSAvoidscaling process complexity

Core Design Contradiction:

Extent of automationVSDevice complexity

Solution Approach 1:

The cloud computing environment performs scaling operations autonomously by monitoring workload characteristics and automatically deploying or terminating virtual machine instances based on predefined thresholds, eliminating the need for manual administrator intervention and reducing operational complexity

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The system continuously monitors workload characteristics of running virtual machines and uses this feedback to trigger automatic scaling decisions, creating a closed-loop control system that adapts to changing demand without human intervention

Inventive Principle:

Principle #23Feedback

2Reliability

If manual scaling is used, then hardware control is maintained, but user experience quality deteriorates

Engineering Contradiction:

Improveservice reliabilityVSAvoidscaling response time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system pre-configures scaling thresholds and virtual machine templates before workload changes occur, enabling immediate automatic scaling actions when triggers are detected without waiting for manual approval or configuration

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The scaling system operates continuously by constantly monitoring workload characteristics and maintaining an active pool of available virtual machine templates, ensuring uninterrupted scaling capability regardless of when workload changes occur

Inventive Principle:

Principle #20Continuity of useful action

Data Source

PatentUS8572612B2Autonomic scaling of virtual machines in a cloud computing environment

Publication Date: 2013.10.29 DAEDALUS BLUE LLC

AI summary

Autonomic scaling of virtual machines in a cloud computing environment, the cloud computing environment including virtual machines (‘VMs’), the VMs installed upon cloud computers disposed within a data center, also including a cloud operating system and a data center administration server operably coupled to the VMs, including deploying, by the cloud operating system, an instance of a VM, flagging the instance of a VM for autonomic scaling; monitoring, by the cloud operating system, one or more operating characteristics of the instance of the VM; deploying, by the cloud operating system, an additional instance of the VM if a value of an operating characteristic exceeds a first predetermined threshold value, including executing a portion of the data processing workload on the additional instance of the VM; and terminating operation of the additional instance of the VM if a value of an operating characteristic declines below a second predetermined threshold value.