Application Deployment Manager for Multi-Platform Infrastructure Adaptation
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Solution Overview
Problem
Existing application deployment processes require significant effort and time to convert applications from one infrastructure platform to another, as they are often written to conform to specific platform requirements, leading to complex and time-consuming rewrites during different lifecycle stages.
Innovation Solution
A deployment manager selects an infrastructure model based on the current lifecycle stage of the application and initiates an application environment using a combination of an application model and an infrastructure model, enabling automated deployment on multiple platforms by provisioning the necessary components and communication protocols.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If applications are written to conform to specific platform requirements, then the application can run natively on that platform, but converting the application to another platform involves complex and time-consuming rewrites
Solution Approach 1:
The patent introduces a translation layer that acts as an intermediary between the application and the infrastructure platform. This translation layer handles platform-specific requirements and conversions, allowing the application to run on multiple platforms without requiring complex rewrites for each platform. The translation layer absorbs the conversion complexity while maintaining application simplicity.
Solution Approach 2:
The patent creates a universal application interface that can interact with multiple different infrastructure platforms through a common set of abstractions. By designing the application to work with platform-agnostic interfaces, the system enables single application code to deploy across diverse platforms, reducing conversion complexity while maintaining broad platform adaptability.
2Productivity
If applications are rewritten to conform to different platform requirements during different lifecycle stages, then the application can be optimized for each stage, but the process is complex and time-consuming
Solution Approach 1:
The patent performs platform conversion and optimization in advance during the development phase, creating platform-specific optimized versions before deployment. This preliminary action allows the application to be pre-adapted for different infrastructure platforms, eliminating the need for time-consuming rewrites during later lifecycle stages and improving overall deployment efficiency.
Solution Approach 2:
The patent divides the application into modular components that can be independently optimized for different platforms. By segmenting the application logic from platform-specific implementations, the system enables selective optimization for different infrastructure platforms without requiring complete rewrites, thereby reducing conversion time while maintaining productivity.
3Adaptability or versatility
If manual conversion processes are used to adapt applications to different infrastructure platforms, then customization is possible, but the process requires significant effort and time
Solution Approach 1:
The patent implements automated self-service mechanisms that perform platform conversion and adaptation without requiring manual intervention. The system automatically detects the target infrastructure platform, selects appropriate conversion rules, and applies optimizations automatically. This self-service approach maintains high platform compatibility while dramatically reducing the effort required for deployment.
Solution Approach 2:
The patent uses parameter-based configuration to adapt the application to different platforms. Instead of manual conversion, the system changes runtime parameters and configuration settings based on the target infrastructure platform. This approach enables automatic platform compatibility while minimizing deployment effort, as the same application code can adapt to different platforms through parameter adjustment rather than structural rewriting.
Data Source
AI summary
A computing device includes a storage device and a controller. The storage device is to store an application model and infrastructure models. The application model defines a first application and specifies a first communication protocol. The controller is to: determine a current lifecycle stage of the first application defined by the application model; select, from the plurality of infrastructure models, a first infrastructure model based on the current lifecycle stage of the first application; initiate a first application environment based on the selected first infrastructure model and the first communication protocol specified in the application model; and deploy the first application on the first application environment using the first communication protocol.