Cloud Application Deployment Portability via Automated Provisioning
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Solution Overview
Problem
Manual deployment of applications in cloud computing is time-consuming and requires extensive administrative effort, as it involves multiple sequential steps to provision and instantiate infrastructure, limiting scalability and efficiency.
Innovation Solution
A system that utilizes a deployment manager and portability manager to automate the deployment of applications by analyzing application requirements and matching them with cloud infrastructure capabilities, enabling automated provisioning and lifecycle management across heterogeneous cloud environments, including workload management and scaling.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual deployment steps are used to provision and instantiate infrastructure, then deployment control and customization are improved, but administrative time and operational complexity increase significantly
Solution Approach 1:
The deployment manager enables self-service automation by automatically analyzing application requirements, matching them with infrastructure capabilities, and executing deployment without manual intervention. The system provisions and instantiates infrastructure resources autonomously based on application models and policy constraints, eliminating the need for administrators to manually perform sequential deployment steps.
Solution Approach 2:
The deployment manager acts as an intermediary between the application model and the cloud infrastructure. It receives deployment requests, correlates application requirements with infrastructure capabilities, and automatically executes the deployment process. This intermediary layer abstracts the complex manual steps from users while maintaining precise control over the deployment process.
2Manufacturing precision
If manual deployment steps are used to provision and instantiate infrastructure, then deployment precision and control are improved, but productivity and scalability deteriorate
Solution Approach 1:
The system automatically performs deployment with high precision by analyzing application models, correlating requirements with infrastructure capabilities, and executing provisioning and instantiation steps without manual intervention. This self-service automation maintains deployment precision while enabling scalable operations across multiple applications and environments simultaneously.
Solution Approach 2:
The deployment manager performs preliminary analysis of application requirements and infrastructure capabilities before execution. By pre-correlating application models with available resources and policy constraints, the system ensures precise deployment decisions are made in advance, enabling scalable and efficient deployment operations.
3Measurement precision
If deployment is linked to full knowledge of deployed infrastructure, then deployment accuracy is improved, but device complexity and operational difficulty increase
Solution Approach 1:
The deployment manager serves as an intermediary that automatically correlates application requirements with infrastructure capabilities without requiring users to have full knowledge of the deployed infrastructure. It analyzes application models, matches them with available resources, and executes deployment accurately while abstracting away the complexity of infrastructure details from the user.
Solution Approach 2:
The system performs self-service infrastructure analysis and matching, automatically gathering and correlating infrastructure capability information without requiring manual input or deep user knowledge. This enables deployment accuracy while eliminating the need for users to understand complex infrastructure details.
4Productivity
If automated deployment is implemented, then productivity and scalability are improved, but extent of automation and system complexity increase
Solution Approach 1:
The deployment manager acts as an intermediary that automates the deployment process by correlating application models with infrastructure capabilities and executing provisioning and instantiation automatically. This intermediary layer handles the automation complexity internally while presenting a simplified interface to users, enabling high productivity without exposing users to automation complexity.
Solution Approach 2:
The deployment manager provides universal automation capabilities that handle multiple deployment scenarios, application types, and infrastructure configurations through a single unified system. This multi-functional approach enables automated deployment across diverse environments while managing automation complexity through standardized processes and policies.
Data Source
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AI summary
A system (100) includes a portability manager (160) to provide portability instructions to specify a change in deployment of a given application (110) on a cloud infrastructure (130). A deployment manager (120) controls deployment or lifecycle management of the given application (110) on the cloud infrastructure (130) in response to the portability instructions and based on matching cloud infrastructure resources to application requirements for the given application (110).