Application Deployment Management via Maturity and Usage Frequency Analysis
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Solution Overview
Problem
Existing IT systems fail to consider application maturity and usage frequency when deploying applications on IT resources, leading to inefficient resource allocation and configuration.
Innovation Solution
A management program that determines the maturity level of an application, generates configurations based on IT resources, allocates appropriate resources, and deploys applications accordingly, while also resizing applications based on maturity and usage frequency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If applications are deployed without considering maturity level and usage frequency, then deployment speed is improved, but resource utilization efficiency deteriorates
Solution Approach 1:
The system performs preliminary classification of applications into maturity levels (experimental, internal, candidate, production) and usage frequency categories (low, medium, high) before deployment. This advance categorization enables the selection of pre-defined configuration templates that match the application's characteristics, eliminating the need for complex real-time analysis during deployment while ensuring optimal resource allocation.
Solution Approach 2:
The system changes configuration parameters based on the determined maturity level and usage frequency. Different parameter sets are applied: experimental applications receive isolated network configurations with minimal resources, internal applications get standard configurations, candidate applications receive enhanced configurations, and production applications with high usage frequency are allocated premium resources and high-availability configurations.
2Ease of operation
If IT resources are allocated without considering application maturity, then allocation simplicity is improved, but system reliability deteriorates
Solution Approach 1:
The system segments IT resource allocation into distinct categories based on application maturity levels. Each segment (experimental, internal, candidate, production) has its own dedicated resource pools and configuration templates. This segmentation ensures that critical production applications receive guaranteed resources with high availability, while non-critical experimental applications use isolated resources, thereby maintaining system reliability without complex manual allocation processes.
Solution Approach 2:
The system introduces an intermediary classification mechanism that automatically determines the appropriate resource allocation based on application maturity and usage frequency. This intermediary layer translates application characteristics into specific resource allocation decisions, eliminating the need for complex manual evaluation while ensuring that reliability requirements are met through automated, consistent allocation rules.
3Speed
If application configurations are standardized without considering maturity level, then configuration speed is improved, but adaptability to different application needs deteriorates
Solution Approach 1:
The system implements dynamic configuration selection based on the determined maturity level and usage frequency of each application. Rather than using a single static configuration template for all applications, the system automatically selects from multiple pre-defined templates (experimental, internal, candidate, production) that are optimized for different application needs. This dynamic approach maintains fast configuration deployment while adapting resource allocation, network settings, and scalability parameters to match each application's specific requirements.
Data Source
AI summary
Methods and apparatuses described herein are directed to a management program that manages IT infrastructures and deploys applications on them while taking the maturity level of the applications into consideration. Example implementations also involve a management program that modifies configurations of IT resources while considering the maturity level and usage frequency of the application during application resizing.