Cloud-Definition Language for Automated Deployment and Performance Prediction

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Solution Overview

Problem

Current cloud-deployment systems lack end-to-end automation and accurate prediction of performance characteristics such as throughput and response time, requiring manual generation of orchestration templates by skilled designers, which is time-consuming and complex, especially for complex computing environments.

Innovation Solution

An automated cloud-deployment system that uses cloud-definition language (CDL) to represent the cloud-computing environment's topology, inferring performance characteristics from empirical data and generating orchestration templates for automated deployment, enabling prediction of response time and throughput as functions of workload.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Reliability

If manual generation of orchestration templates is used, then deployment reliability can be maintained through expert design, but deployment time and complexity increase significantly

Engineering Contradiction:

Improvedeployment reliabilityVSAvoiddeployment time

Core Design Contradiction:

ReliabilityVSLoss of time

Solution Approach 1:

The system performs preliminary actions by automatically generating orchestration templates from high-level cloud definition language (CDL) specifications before actual deployment begins. This pre-computation of deployment configurations eliminates the need for manual template creation during the deployment process, thereby reducing deployment time while maintaining reliability through automated validation.

Inventive Principle:

Principle #10Preliminary action

Solution Approach 2:

The patent introduces an intermediary orchestration template that serves as a bridge between high-level CDL specifications and low-level deployment configurations. This intermediary layer automatically translates business requirements into detailed deployment steps, eliminating the need for manual expert intervention while ensuring deployment reliability through structured template validation.

Inventive Principle:

Principle #24Intermediary (Mediator)

2Manufacturing precision

If manual generation of orchestration templates is used, then deployment accuracy can be ensured through expert knowledge, but device complexity and operational difficulty increase

Engineering Contradiction:

Improvedeployment accuracyVSAvoidtemplate generation complexity

Core Design Contradiction:

Manufacturing precisionVSDevice complexity

Solution Approach 1:

The system enables self-service by allowing automated generation of orchestration templates from simple CDL specifications without requiring manual intervention from expert designers. The automated template generator inherently handles the complexity of translating high-level requirements into detailed deployment configurations, ensuring accuracy while eliminating manual operational difficulty.

Inventive Principle:

Principle #25Self-service

Solution Approach 2:

The patent replaces the manual mechanical process of expert template creation with an automated computational system. The orchestration template generator automatically performs the complex task of translating CDL specifications into deployment templates, substituting human expert knowledge with algorithmic processing that maintains accuracy while reducing operational complexity.

Inventive Principle:

Principle #28Mechanics substitution (Replace mechanical system)

3Productivity

If automated deployment systems are implemented, then deployment speed increases, but ability to accurately predict performance characteristics decreases

Engineering Contradiction:

Improvedeployment speedVSAvoidperformance prediction accuracy

Core Design Contradiction:

ProductivityVSMeasurement precision

Solution Approach 1:

The system incorporates feedback mechanisms by automatically generating performance predictions and resource requirement estimates as part of the orchestration template creation process. These predictions are integrated into the automated deployment workflow, allowing the system to maintain high deployment speed while providing accurate performance forecasts through automated analysis of the CDL specifications and historical data.

Inventive Principle:

Principle #23Feedback

4Extent of automation

If end-to-end automation is implemented, then operational efficiency improves, but system complexity increases

Engineering Contradiction:

Improveautomation levelVSAvoidsystem complexity

Core Design Contradiction:

Extent of automationVSDevice complexity

Solution Approach 1:

The patent implements a universal orchestration template generator that handles multiple deployment scenarios and cloud configurations through a single automated system. This multi-functional approach enables end-to-end automation across diverse cloud environments while managing system complexity through standardized processing workflows that can adapt to different deployment requirements without requiring separate manual procedures for each scenario.

Inventive Principle:

Principle #6Universality (Multi-functionality)

Data Source

PatentUS10540188B2Automated deployment and performance evaluation of a virtualized-computing environment

Publication Date: 2020.01.21 KYNDRYL INC

AI summary

A virtual-computing environment definition language automates the deployment of a virtualized computing environment. A set of basic requirements of a planned virtual computing environment is described in the definition language to provide a concise, textual representation of the planned environment's architecture. This representation also predicts the planned environment's performance characteristics as a function of expected workloads, such as expected numbers of concurrent users or expected numbers of concurrent transactions. The definition-language representation is then translated into an orchestration template from which virtual resources are provisioned and the virtual-computing environment deployed.