Cloud Stress Testing with Adaptive Parameter Control
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Solution Overview
Problem
Current stress testing methods in cloud computing lack accuracy and efficiency in evaluating the capacity of business systems under maximum load, impacting capacity analysis and evaluation.
Innovation Solution
A method and apparatus for stress testing in cloud services that initiates a stress testing request based on preset configuration information, acquires monitoring data, and determines query capacity information, allowing for precise and efficient evaluation of a business system's performance and capacity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If stress testing is performed on cloud business systems, then capacity evaluation is achieved, but testing accuracy and efficiency are insufficient
Solution Approach 1:
The patent dynamically adjusts stress testing parameters including traffic volume, concurrency levels, and test duration based on system response characteristics. The testing system modifies these parameters in real-time to optimize both measurement precision and testing efficiency, transitioning from static to adaptive parameter control.
Solution Approach 2:
The system implements continuous feedback mechanisms by monitoring system performance metrics during stress testing and using this information to adjust subsequent test configurations. This closed-loop approach improves capacity evaluation accuracy while maintaining testing efficiency through intelligent parameter optimization.
2Measurement precision
If comprehensive monitoring data is collected during stress testing, then evaluation accuracy improves, but testing complexity increases
Solution Approach 1:
The patent extracts and focuses on collecting only the most critical performance monitoring data relevant to capacity evaluation, such as response time, throughput, and resource utilization metrics. By filtering out redundant information, the system maintains high evaluation accuracy while reducing overall system complexity.
Solution Approach 2:
The monitoring system is designed with multi-functional capabilities that allow a single unified monitoring framework to collect, analyze, and process multiple types of performance data simultaneously. This universal approach reduces complexity compared to having separate specialized monitoring systems for each metric.
Data Source
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AI summary
A method and apparatus for stress testing are provided, relates to the field of cloud computing technology. An embodiment of the method includes: initiating a stress testing request to a business system in a cloud service based on preset stress testing configuration information, the stress testing configuration information including at least one test traffic; acquiring monitoring data of the performance of the business system responding to the stress testing request; and determining query capacity information of the business system based on the preset stress testing configuration information and the monitoring data of the performance.