Virtualization Assessment Engine for Application Deployment Planning
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Solution Overview
Problem
Data centers often over-provision computing hardware due to inadequate planning, leading to inefficient deployment of software applications and resulting in significant increases in power, cooling, and space requirements, known as server or virtual sprawl.
Innovation Solution
A virtualization assessment engine determines the optimal hardware characteristics and deployment plan for target applications, considering technical and business requirements, to efficiently distribute and deploy applications across available hardware, ensuring compatibility and resource utilization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If computing hardware is over-provisioned in data centers, then software applications can be deployed without resource constraints, but hardware costs and resource inefficiencies increase significantly
Solution Approach 1:
The patent applies preliminary action by performing comprehensive assessment and analysis of application requirements, hardware capabilities, and compatibility relationships before deployment. The system pre-calculates optimal deployment configurations, identifies suitable hardware targets, and plans resource allocation in advance, avoiding the need for excessive hardware provisioning while ensuring applications can be deployed without constraints.
2Ease of operation
If computing hardware is consolidated in specialized data centers, then efficiency and ease of management improve, but power, cooling, and space requirements increase due to server sprawl
Solution Approach 1:
The patent implements universality by creating a multi-functional assessment and deployment system that simultaneously evaluates application requirements, analyzes hardware capabilities, checks compatibility constraints, optimizes resource allocation, and generates deployment plans. This integrated approach enables efficient consolidation of applications onto fewer hardware resources, reducing power consumption while maintaining ease of management through automated decision-making.
3Speed
If software applications are deployed without careful planning, then deployment speed is fast, but server or virtual sprawl occurs leading to increased resource requirements
Solution Approach 1:
The patent applies self-service by enabling the deployment system to automatically assess application requirements, analyze hardware compatibility, optimize resource allocation, and generate deployment plans without manual intervention. This automated self-service approach maintains fast deployment speed while preventing server sprawl through intelligent, algorithm-driven decision-making that efficiently packs applications onto appropriate hardware.
4Ease of manufacture
If hardware characteristics are not carefully selected for target applications, then provisioning is simple and fast, but application compatibility and performance suffer
Solution Approach 1:
The patent implements feedback by creating an assessment engine that continuously evaluates application requirements against hardware capabilities, checks compatibility constraints, and uses this feedback information to optimize hardware selection and deployment configurations. This feedback-driven approach ensures high application compatibility and performance while maintaining provisioning simplicity through automated, intelligent decision-making.
Data Source
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AI summary
According to one example, there is provided a method of deploying applications in a computer system. The method comprises obtaining, for each of a plurality of computer applications, a set of application characteristics, assigning, based on the obtained characteristics, each of the plurality of applications to one of a set of predetermined application models, and determining, based in part on the obtained characteristics and in part on application model compatibility data, a set of hardware characteristics, a virtual server distribution plan, and an application distribution plan.