Dynamic Application Management Across Multi-Cloud Environments
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
In multi-cloud computing environments, decomposing and orchestrating applications across multiple cloud platforms is cumbersome due to differences in standards, compliance, security, and cost considerations, requiring significant manual effort and leading to sub-optimal hosting costs and data management challenges.
Innovation Solution
The implementation of dynamic application management techniques using code-markers that allow software components to be executed on different clouds based on user-defined policies, enabling dynamic scheduling and orchestration without re-deployment, and facilitating quick testing and optimization of decomposition and orchestration settings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If software components are moved between multiple cloud platforms using traditional methods, then cloud infrastructure utilization is achieved, but significant manual engineering effort is required for refactoring, testing and release management
Solution Approach 1:
The patent introduces a cloud platform adapter as an intermediary layer between the application and multiple cloud platforms. This adapter handles platform-specific differences, authentication, and configuration, allowing software components to be moved between clouds without significant refactoring. The adapter absorbs the complexity of cloud platform variations, reducing manual engineering effort while maintaining multi-cloud capability.
Solution Approach 2:
The patent creates a universal deployment framework that can operate across multiple cloud platforms through a common interface. The cloud platform adapter is designed to be multi-functional, supporting various cloud providers (AWS, Azure, GCP, etc.) through standardized configurations. This universality allows the same software components to be deployed to different clouds without platform-specific modifications.
2Adaptability or versatility
If cloud infrastructures use different standards, then cloud platform diversity is achieved, but moving software components between platforms demands significant manual effort
Solution Approach 1:
The cloud platform adapter serves as a mediator that translates between different cloud platform standards and the application's unified interface. It handles authentication protocols, resource naming conventions, and configuration formats specific to each cloud provider, allowing the application to interact with diverse cloud infrastructures through a standardized interface without requiring manual refactoring.
Solution Approach 2:
The patent applies local quality by making each cloud platform adapter instance specialized for its target platform while maintaining a unified overall architecture. Each adapter contains platform-specific logic and configurations tailored to its cloud environment, allowing the system to accommodate diverse cloud standards without compromising the simplicity of the core application.
3Adaptability or versatility
If applications are decomposed into multiple jobs or functions, then flexibility in cloud hosting is achieved, but significant manual engineering effort is required for testing and release management
Solution Approach 1:
The patent implements automated CI/CD pipelines that continuously build, test, and deploy software components across cloud platforms. Once the initial setup is complete, the system automatically handles subsequent deployment cycles, eliminating the need for manual testing and release management. The cloud platform adapter and deployment framework work together to streamline the entire release process, reducing time loss while maintaining flexibility.
4Extent of automation
If code-markers are used to identify software components, then dynamic scheduling across clouds is enabled, but code modification is required
Solution Approach 1:
The patent uses code-markers as metadata parameters that can be added to software components to specify their deployment characteristics. These markers contain parameters such as target cloud platform, resource requirements, and scheduling preferences. By changing these parameters, the system can dynamically schedule and deploy components to appropriate cloud platforms without modifying the core business logic, making the code modification effort minimal and focused only on deployment attributes.
Data Source
AI summary
Techniques for dynamic application management are provided. For example, an apparatus comprises at least one processing platform configured to: execute a portion of an application program in a first virtual computing element, wherein the application program comprises at least one portion of marked code; receive a request for execution of the portion of marked code; determine, based at least in part on the portion of marked code, one or more cloud platforms on which to execute the portion of marked code; and cause the portion of marked code identified in the request to be executed on the one or more cloud platforms.