Application Manager for Software Environment Optimization
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Solution Overview
Problem
Current software application environments often fail to meet performance requirements due to unforeseen user traffic and technological changes, leading to suboptimal performance and potential system crashes, as they are not dynamically adaptable to changing conditions or new technologies.
Innovation Solution
An application manager system that tests various technology product combinations, builds alternative model application environments, and recommends optimal configurations based on performance metrics, ensuring the software application environment can handle increased traffic and leverage new technologies.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If the application environment is designed based on expected performance criteria, then the application can meet initial performance requirements, but the environment cannot adapt to changing user traffic or technological changes
Solution Approach 1:
The system performs preliminary actions by building multiple alternative model application environments before actual deployment. These models are pre-configured with different technology product combinations and pre-tested to evaluate their performance characteristics. When traffic patterns change or new technologies emerge, the system can quickly select from these pre-prepared models without needing to redesign the entire environment, thus achieving both adaptability and reliability.
Solution Approach 2:
The system implements dynamics by enabling the application environment to transition between different pre-configured models based on changing conditions. The performance evaluation system continuously monitors actual performance metrics and compares them against predicted metrics for different models. When a model better suited to current conditions is identified, the system can dynamically switch to that configuration, making the environment adaptable while maintaining reliability through validated model selections.
2Adaptability or versatility
If the application environment uses a fixed set of technology products, then the initial deployment is straightforward, but the environment cannot leverage new and emerging technology products
Solution Approach 1:
The system segments the application environment into multiple alternative models, each representing a different combination of technology products. This segmentation allows the environment to be evaluated and switched between different configurations without redesigning the entire system. Each model can independently incorporate new technology products while maintaining the overall system structure, thus enabling technology integration without excessive complexity.
Solution Approach 2:
The performance evaluation system serves multiple functions: it evaluates existing models, predicts performance of alternative models, monitors actual performance, and recommends optimizations. This multi-functionality allows the system to handle technology product updates and new integrations through a single unified framework, reducing the complexity that would otherwise arise from managing multiple separate configuration and evaluation processes.
3Reliability
If the application is designed for a specific user capacity, then the initial design is simple, but the environment cannot handle unexpected increases in user traffic
Solution Approach 1:
The system performs preliminary action by pre-building multiple alternative model application environments with different scaling capabilities. These models are configured to handle various user traffic levels and are pre-evaluated for their performance characteristics. When unexpected traffic increases occur, the system can quickly identify and switch to a model designed for higher capacity, ensuring reliable handling of variable traffic without requiring complex real-time scaling decisions.
4Productivity
If performance testing is conducted only on the current application environment, then the evaluation is simple, but alternative configurations cannot be assessed for better performance
Solution Approach 1:
The system creates copies of the current application environment in the form of alternative model environments. Each model is a replicated version that can be independently tested and evaluated without affecting the production system. This copying approach allows comprehensive performance testing of multiple configurations while maintaining a single source of truth for the actual application, thus enabling performance optimization without proportionally increasing testing complexity.
Data Source
AI summary
A system is configured to obtain information relating to a current application environment and a plurality of model application environments of a software application. The system runs the software application using the current application environment and each of the model application environments. The system collects a plurality of performance metrics related to performance of the software application in the current application environment and each of the model application environments while running in the simulated environment. The system assigns a score to each performance metric and determines a model application environment that yielded a higher score for a performance metric as compared to the score of the performance metric in the current application environment. The system recommends at least one technology product used for a corresponding technology component associated with the performance metric in the determined model application environment.