Dynamic Solution Stack Generation for Cloud Service Deployment
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Existing cloud computing solutions often require complex and time-consuming development, testing, and maintenance of monolithic solution stacks, which are cumbersome due to the integration of base services with stack services, making it difficult for cloud users to deploy services without knowledge of prerequisite base services.
Innovation Solution
A solution stack generator dynamically composites stack services and decoupled base services to create a solution stack model, configuring base services according to stack service requirements and life cycles, allowing cloud users to focus on configuring stack services without needing to manage base services.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If monolithic solution stacks are used to integrate base services and stack services, then service functionality is complete, but system complexity and maintenance difficulty increase
Solution Approach 1:
The patent segments the monolithic solution stack into separate base services and stack services. Base services are independent, reusable components that can be shared across multiple stack services. This segmentation reduces system complexity by allowing independent development, deployment, and maintenance of base services while preserving complete functionality through composition.
Solution Approach 2:
The patent creates universal base services that can be reused across multiple different stack services. Instead of having dedicated services for each stack service, a single base service can serve multiple purposes and be instantiated by different stack services, reducing overall system complexity and improving maintainability.
2Reliability
If base services are integrated with stack services in monolithic stacks, then service requirements are met, but deployment time and user effort increase
Solution Approach 1:
The patent implements preliminary action by pre-configuring and validating base services independently before they are composed into stack services. Base services are developed, tested, and registered in a service repository in advance, so that when stack services need them, they can be quickly retrieved and composed without time-consuming integration work.
Solution Approach 2:
The system enables self-service deployment where the composition engine automatically discovers, retrieves, and composes base services with stack services based on declared dependencies. This automation eliminates manual configuration and integration efforts, significantly reducing deployment time while ensuring service requirements are met.
3Ease of operation
If cloud users must manage both base services and stack services, then complete control is achieved, but ease of operation decreases
Solution Approach 1:
The patent introduces a composition engine and service repository as intermediaries between cloud users and the services. Users simply declare their stack service requirements, and the composition engine automatically handles the complex tasks of discovering, retrieving, configuring, and composing the appropriate base services. This intermediary layer shields users from management complexity while maintaining complete control over service composition.
Solution Approach 2:
The system implements self-service where base services automatically configure themselves and compose with stack services based on declared dependencies and requirements. The composition engine autonomously manages the service lifecycle, including automatic configuration, validation, and deployment, eliminating the need for users to manually manage base services while ensuring proper integration.
Data Source
AI summary
Embodiments of the present disclosure dynamically generate solution stacks. In one embodiment, a request to deploy a service in a cloud computing environment is received. A service repository is queried for data that describes one or more requirements of the service. One or more prerequisite services are identified based, at least in part, on the requirements of the service. A solution stack model is dynamically generated from (i) a stack service model of the service and (ii) the one or more prerequisite services, wherein the solution stack model is based, at least in part, on the requirements of the service.