Graph Model Bottleneck Detection in Monolith Decomposition
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Solution Overview
Problem
Modernizing monolithic software applications to improve performance and scalability is challenging due to the complexity of identifying and addressing resource bottlenecks, which can hinder migration to cloud-based deployments and lead to inefficiencies in resource usage.
Innovation Solution
An application modernization system constructs a graph model of the software application based on application artifacts, generates application profile metrics, and applies weights to identify and prioritize bottlenecks, enabling efficient decomposition into scalable subunits.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If monolithic software applications are modernized to improve performance and scalability, then the application can handle more users and requests, but the complexity of identifying and addressing resource bottlenecks increases
Solution Approach 1:
The patent segments the monolithic application into modular components with distinct responsibilities. Each component is independently analyzed for bottlenecks using graph models that represent application artifacts and their relationships. This segmentation allows targeted modernization of specific components rather than requiring complete system redesign, thereby improving performance while managing complexity through localized analysis.
Solution Approach 2:
The patent introduces graph models as intermediary representations between the application artifacts and the bottleneck analysis process. These graph models serve as mediators that automatically capture dependencies, data flows, and resource usage patterns, eliminating the need for manual complexity in identifying bottlenecks while enabling systematic performance optimization.
2Adaptability or versatility
If monolithic applications are decomposed into subunits, then scalability is improved, but the process becomes more complex and difficult to manage
Solution Approach 1:
The patent applies segmentation by automatically dividing the monolithic application into scalable subunits based on graph model analysis of application artifacts. The system identifies natural boundaries and dependencies to create modular components that can be independently deployed and scaled, achieving adaptability while the automated analysis process manages the complexity of decomposition.
Solution Approach 2:
The patent performs preliminary analysis using graph models to map application artifacts and identify decomposition opportunities before actual decomposition occurs. This preliminary action includes weighting graph elements based on resource usage metrics, allowing the system to plan and execute decomposition in an optimized sequence that reduces management complexity while maximizing scalability benefits.
3Loss of energy
If resource bottlenecks are identified and addressed, then efficiency in resource usage improves, but the analysis and prioritization process becomes more complex
Solution Approach 1:
The patent replaces manual bottleneck analysis with automated graph-based analysis that processes application artifacts and generates weighted models. This substitution eliminates the need for complex manual assessment while systematically identifying resource usage patterns and bottlenecks, thereby improving resource efficiency without proportionally increasing analysis complexity.
Solution Approach 2:
The patent changes the parameters of analysis by introducing weighted graph models that incorporate multiple resource usage metrics (CPU, memory, I/O, network). By transforming raw artifact data into weighted representations, the system automatically prioritizes bottlenecks based on their impact on resource efficiency, making the analysis process more systematic and less complex while improving resource optimization outcomes.
Data Source
AI summary
Techniques are described for identifying resource bottlenecks in decomposing monolithic software applications as part of software modernization processes. An application modernization system constructs a graph model of a software application based on an analysis of application artifacts associated with the software application. The graph model includes nodes representing independent application components, and further includes edges representing identified dependency relationships among the application components. An application modernization system further generates application profile metrics associated with the identified dependencies, and weights derived from the metrics are applied to the nodes and/or the edges of the graph model to generate a weighted graph model that identifies the resource bottlenecks among the application components and the identified dependency relationships. The weighted graph model is transmitted to a computing device for display to a user.