Traffic-Based Stress Modeling for Accurate API Stress Tests
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Solution Overview
Problem
Current stress testing methods require high technical expertise and are subject to human subjectivity, leading to inaccurate performance results due to manual construction of stress models, which do not accurately reflect the actual performance of the tested product.
Innovation Solution
Automatically generate a stress model based on traffic information of the to-be-tested object, using API request sequences to match a stress target, reducing the need for manual intervention and ensuring the model accurately represents the object's stress capacity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual stress model construction is used based on test person's understanding of service logic, then the stress testing process can be performed, but the testing accuracy deteriorates due to subjectivity and cognitive limitations
Solution Approach 1:
The system performs self-service by automatically generating stress models through analyzing actual traffic data of the service. The traffic analysis module collects real traffic information, and the stress model generation module automatically creates stress models based on this data, eliminating the need for manual construction by test persons and thereby removing subjectivity and cognitive limitations.
Solution Approach 2:
The patent replaces the manual mechanical process of stress model construction with an automated information processing system. Instead of relying on human understanding and manual creation of stress models, the system uses traffic analysis modules and automated generation algorithms to substitute the human element, thereby improving accuracy by eliminating human subjectivity.
2Ease of operation
If manual stress model construction is used, then the stress testing can be performed, but the technical level requirement increases significantly
Solution Approach 1:
The system makes stress testing self-service by automating the stress model generation process. The traffic analysis module automatically analyzes service traffic patterns, and the stress model generation module automatically creates appropriate stress models without requiring test persons to have deep understanding of service logic, thereby reducing technical level requirements.
Solution Approach 2:
The patent introduces traffic analysis modules and automated generation modules as intermediaries between the service being tested and the stress testing process. These intermediary modules handle the complex analysis and model generation tasks, shielding users from technical complexity while enabling stress testing capability.
3Measurement precision
If automated stress model generation based on traffic information is used, then testing accuracy improves by eliminating human subjectivity, but the system complexity increases
Solution Approach 1:
The patent segments the stress testing system into distinct functional modules: a traffic analysis module that collects and analyzes traffic information, and a stress model generation module that creates stress models based on analyzed data. This segmentation allows each module to perform its specific function independently, improving accuracy while managing complexity through modular design.
Solution Approach 2:
The patent introduces traffic analysis modules as intermediaries between the service being tested and the stress testing execution. These intermediary modules automatically analyze traffic patterns and generate stress models, eliminating human subjectivity and improving accuracy. The modular intermediary structure manages system complexity by encapsulating complex analysis logic within dedicated components.
Data Source
AI summary
A stress testing method includes obtaining traffic information of a to-be-tested object; generating, based on the traffic information of the to-be-tested object, a stress model matching a stress target, where the stress model includes at least one group of application programming interface (API) request sequences, each group of API request sequences includes at least one API request, and the stress target indicates an upper limit of stress that the to-be-tested object is capable of bearing; and then performing stress testing on the to-be-tested object based on the stress model.