Automated Server Configuration Optimization for Dynamic Loads
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Solution Overview
Problem
Server optimization in systems of multiple interdependent servers is complex due to numerous configuration parameters and varying loads, making it impractical for administrators to manually determine and adjust optimal configurations for each load scenario.
Innovation Solution
A system with executable instructions that analyzes configuration sources, determines and tests configuration settings against various load levels, identifies optimal settings, and automatically applies the best configuration for upcoming loads by simulating and recording performance metrics, allowing for dynamic reconfiguration based on expected load levels.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Manufacturing precision
If manual configuration testing is performed for each load scenario, then optimal configuration can be determined, but administrative time and effort increase dramatically
Solution Approach 1:
The system performs self-configuration by automatically testing different configuration settings against various load levels and selecting optimal configurations without requiring administrator intervention for each test iteration
Solution Approach 2:
The system pre-determines optimal configurations for multiple load levels in advance through automated testing, so that when a specific load occurs, the pre-optimal configuration can be quickly applied without time-consuming manual testing
2Productivity
If reconfiguration is performed for each changing load, then system performance is optimized, but system stability decreases due to frequent changes
Solution Approach 1:
The system dynamically adjusts configuration settings based on current load conditions by selecting from pre-determined optimal configurations, allowing the system to adapt to changing loads while maintaining stability through automated, consistent decision-making
3Stability of the object's composition
If a single configuration is used for all load levels, then system stability is maintained, but performance decreases under varying load conditions
Solution Approach 1:
The system changes configuration parameters based on load conditions by selecting from multiple pre-determined optimal configurations, each optimized for specific load levels, thus maintaining both stability through systematic selection and performance through parameter optimization
4Measurement precision
If comprehensive configuration testing is performed, then optimal settings are identified, but device complexity increases
Solution Approach 1:
The system creates virtual copies or simulations of the server environment to perform comprehensive configuration testing without affecting the production system, allowing thorough testing while isolating complexity to the testing environment
Data Source
AI summary
A computer readable storage medium includes executable instructions for facilitating automatic server optimization in a system. The executable instructions include instructions to accept a set of initialization parameters, analyze a set of one or more configuration sources, determine a set of configuration settings, receive a series of load levels, and select a load level. The set of configuration settings are tested against the load level. An optimal configuration setting for the load level is identified. The optimal configuration setting is recorded.