Monolith to Microservice Transformation via User Intent
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Solution Overview
Problem
Current approaches for transforming monolithic applications into microservices are predominantly bottom-up driven, lacking user intent-based guidance, which leads to difficulties in standardization, misalignment of functionality, and inefficient team assignment, especially during the transition to cloud or distributed computing environments.
Innovation Solution
A system that analyzes user intent through natural language processing to map software artifacts into microservices, allowing for the transformation of monolithic applications into a distributed computing environment by clustering functionalities based on user-defined intent, thereby reducing iteration and improving standardization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If bottom-up driven approaches are used to detect microservice boundaries from implementation structure, then microservice recommendations can be generated automatically, but the transformation lacks user intent alignment and standardization
Solution Approach 1:
The patent inverts the traditional bottom-up approach by implementing a top-down methodology where user intent and business domain concepts drive the microservice decomposition process. Instead of deriving microservices solely from code structure analysis, the system starts with high-level business requirements and domain models, then systematically transforms them into microservice boundaries, ensuring alignment with user intent while maintaining automation through AI-assisted code mapping.
Solution Approach 2:
The patent applies preliminary action by first establishing domain-driven design models and user intent specifications before performing code transformation. The system pre-defines microservice boundaries based on business domain concepts and user requirements, then uses AI to map existing code artifacts to these pre-determined boundaries, ensuring standardization is built into the transformation process from the outset rather than applied as an afterthought.
2Manufacturing precision
If domain driven design concepts are applied to portfolio of applications, then standardization is improved, but it cannot be easily overlayed on monolith code for modernization
Solution Approach 1:
The patent introduces an intermediary layer of domain-driven design models that bridge the gap between existing monolithic code and target microservice architecture. This intermediary representation uses standardized domain concepts and business rules that can be applied across multiple applications, enabling standardization without requiring direct manipulation of complex monolith code structures. The AI system acts as a mediator to translate between code artifacts and domain models.
Solution Approach 2:
The patent segments the transformation process into distinct phases: (1) analyzing existing code structure, (2) creating domain-driven design models, (3) defining user intent specifications, (4) mapping code to domain models, and (5) generating microservice recommendations. This segmentation allows domain-driven design concepts to be applied systematically to individual components rather than attempting to overlay them on the entire monolith codebase at once, reducing transformation complexity.
3Manufacturing precision
If green field development is used to avoid existing implementation structure influence, then new microservices can be created cleanly, but resource consumption and time increase
Solution Approach 1:
The patent uses copying by creating idealized microservice templates and domain model patterns that represent best practices, then systematically applying these templates to existing code through AI-assisted mapping. Rather than writing microservices from scratch (green field development) or directly refactoring complex existing code, the system copies proven patterns and adapts them to the specific application context, achieving high quality microservices with improved efficiency.
Solution Approach 2:
The patent applies parameter changes by transforming code artifacts through systematic parameter mappings between the source monolith structure and target microservice structure. The AI system identifies and transforms key parameters such as service boundaries, data access patterns, and deployment units, allowing existing implementation structure to be leveraged while achieving clean microservice architecture. This approach maintains productivity by working with parameter transformations rather than complete rewrites.
Data Source
AI summary
According to one embodiment of the present invention, a system transforms an application for a distributed computing environment. The system comprises one or more memories, and at least one processor coupled to the one or more memories. The system analyzes a description of user intent to extract information for transforming the application. The extracted information indicates functionalities for the distributed computing environment. A plurality of software artifacts of the application are mapped to the functionalities. The plurality of software artifacts form different groups of software artifacts. Remaining software artifacts of the application are assigned into the different groups based on a remaining software artifact corresponding to a mapped software artifact of a group. The different groups correspond to microservices for the distributed computing environment. The microservices for the distributed computing environment are presented based on the different groups.