Intelligent Solution Execution via Wrapper-Based Runtime Adaptation
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Solution Overview
Problem
Current systems fail to seamlessly integrate and deploy solutions written in various programming languages across different runtime environments, leading to inefficiencies and labor-intensive processes in collaboration and integration between teams.
Innovation Solution
The Solutions Repository (SR) and intelligent solution execution method enable seamless integration and deployment of solutions by packaging and deploying them in a way that is consumable across different products, languages, and frameworks, and by intelligently determining where and how to execute the solution based on the deployment platform and runtime environment.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If solutions are developed using different programming languages and runtime environments, then users can leverage their preferred language strengths, but integration and collaboration between teams becomes problematic and inefficient
Solution Approach 1:
The patent introduces a solution repository and wrapper mechanism as an intermediary layer between solutions written in different programming languages and runtime environments. The wrapper translates and adapts solutions from various languages (Python, Scala, R, Apache Spark) into a unified execution format, enabling seamless integration without requiring users to convert their code or learn new languages. This mediator resolves the contradiction by maintaining language diversity while achieving integration simplicity.
Solution Approach 2:
The solution repository is designed as a universal platform that can store, manage, and execute solutions written in multiple programming languages and runtime environments. It provides multi-functional capabilities including solution packaging, version control, dependency management, and cross-language execution, allowing a single system to handle diverse solution types without requiring separate integration mechanisms for each language pair.
2Adaptability or versatility
If solutions are converted from one programming platform to another, then integration becomes possible, but the process becomes inefficient and time consuming
Solution Approach 1:
Instead of converting solutions from one programming platform to another, the system creates wrappers that copy and encapsulate the original solution code along with its runtime environment requirements. The wrapper contains all necessary information about the solution's dependencies, execution context, and translation rules, allowing the solution to be executed in a different environment without modifying the original code. This copying approach eliminates time-consuming conversion while achieving platform compatibility.
3Device complexity
If solutions are redeveloped in a common programming platform, then integration is simplified, but the process becomes labor-intensive and skill-mismatched
Solution Approach 1:
The system segments the integration problem into two independent parts: the solution code itself and the execution environment. By separating these concerns, solutions can remain in their original programming languages while the execution environment is standardized through wrappers. This segmentation eliminates the need for labor-intensive redevelopment in a common language, as users can maintain their solutions in their preferred languages while the wrapper handles environment standardization.
4Adaptability or versatility
If teams custom engineer integration solutions, then specific integration needs are met, but performance overhead and inefficiencies increase
Solution Approach 1:
The system performs preliminary actions by pre-packaging solutions with their execution context, dependencies, and translation rules in a standardized wrapper format. This preliminary preparation eliminates the need for teams to custom-engineer integration logic for each solution, as the wrapper already contains all necessary integration information. The pre-configured wrappers enable efficient execution without the performance overhead of custom integration engineering.
Data Source
AI summary
A deployment platform, computer-readable medium, and computer-implemented method for intelligent execution of a solution on a computer network, including receiving an instruction to execute a solution in a local runtime environment on the deployment platform, the solution including solution code written in a solution language, determining, by a helper program on the deployment platform, whether the solution is executable on the deployment platform based on the solution language and either launching, by the helper program, the solution on the deployment platform when the solution is executable on the deployment platform or launching, by the helper program, the solution on a remote platform on the computer network that is configured to execute the solution when the solution is not executable on the deployment platform, the helper program being configured to communicate with the launched solution to enable the launched solution to interface with the local runtime environment on the deployment platform.