Dynamic Server Testing Interval Adjustment
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Solution Overview
Problem
Current server operation and maintenance processes lack a systematic approach to setting interval times for testing, leading to resource wastage, increased server pressure, and inefficient operations due to arbitrary or uniformly set testing intervals.
Innovation Solution
A method and system that dynamically adjust interval times for server testing based on current performance metrics, involving data acquisition, analysis, and weight determination to allocate tasks and set optimal testing intervals, reducing unnecessary polling and improving task execution efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If testing interval time is set arbitrarily or uniformly for all servers, then the testing process is simple to implement, but resource wastage increases and server performance deteriorates due to unnecessary polling or insufficient monitoring
Solution Approach 1:
The patent implements dynamic adjustment of testing interval time based on real-time server performance metrics. The system continuously monitors CPU usage, memory consumption, disk I/O, and network traffic, then automatically adjusts the testing interval accordingly. When server load is high, the testing interval is extended to reduce resource consumption; when load is low, the interval is shortened to improve monitoring precision. This dynamic mechanism resolves the contradiction by making the system adaptive rather than static.
Solution Approach 2:
The patent changes the parameter of testing interval time from a fixed uniform value to a variable value that depends on server performance parameters. By establishing a mapping relationship between performance metrics (CPU usage rate, memory usage rate, disk I/O rate, network traffic) and testing interval time, the system optimizes the interval dynamically. This parameter change approach allows the system to balance between monitoring precision and resource consumption.
2Ease of manufacture
If testing interval time is set uniformly for all servers, then the implementation is straightforward, but server pressure increases when task execution amount is large and performance is poor
Solution Approach 1:
The patent applies different testing interval times to different servers based on their individual performance characteristics. Instead of using a uniform interval for all servers, the system evaluates each server's CPU usage, memory consumption, disk I/O, and network traffic separately, then assigns optimized interval times tailored to each server's load conditions. This local quality approach ensures that servers under heavy pressure receive longer intervals to reduce stress, while servers with lighter loads maintain shorter intervals for better monitoring.
3Measurement precision
If testing interval time is set too small, then monitoring precision is improved, but operation efficiency decreases due to meaningless testing and resource consumption increases
Solution Approach 1:
The system dynamically adjusts the testing interval based on real-time server performance to achieve optimal monitoring precision without sacrificing operation efficiency. When server performance is stable, the interval is extended; when performance fluctuates significantly, the interval is shortened. This dynamic adjustment ensures monitoring precision is maintained only when necessary, thereby preserving operation efficiency.
Solution Approach 2:
The patent establishes a functional relationship between performance parameters and testing interval time. By analyzing metrics such as CPU usage rate, memory usage rate, disk I/O rate, and network traffic, the system determines the appropriate testing interval. This parameter-based approach ensures that monitoring precision is optimized according to actual server conditions rather than using a fixed small interval that would waste resources.
Data Source
AI summary
A method and a system for determining interval time for testing of a server, and a device and a storage medium are provided. The method includes: evenly dividing multiple servers into multiple groups of servers, and performing multiple rounds of testing on each group of servers; calculating performance values of each group of servers in each round of testing according to a weight corresponding to each influencing factor, and packaging and writing the performance values and interval time corresponding to the performance values in a database; and collecting, at every other preset time, current values corresponding to influencing factors in an actual running process of a server, calculating a current performance value of the server based on the current values according to the weight corresponding to the respective one of the one or more influencing factors, and determining, from the database, interval time corresponding to the current performance value.