Research on Stress Testing Automation of AI Server for High Concurrency Scenarios

Xingcheng Ren

doi:10.70393/6a696574.343131

OPEN ACCESS |Research Article ||10 April 2026

Research on Stress Testing Automation of AI Server for High Concurrency Scenarios

Xingcheng Ren

Quanta Manufacturing Nashville LLC

xrenwork@yahoo.com

Quanta Manufacturing Nashville LLC, US, xrenwork@yahoo.com.

* Corresponding Author¹: Xingcheng Ren, E-Mail: xrenwork@yahoo.com

Publication

Accepted 2026 April 10 ; Published 2026 April 10

Journal of Intelligence and Engineering Technology, 2026, 1(2), Pending.

Abstract

Traditional stress testing methods are difficult to simulate the complexity and dynamics in real business scenarios, resulting in distorted test results and low efficiency. In order to solve the above problems, this paper proposes an automated framework for stress testing of AI servers facing high concurrency scenarios. The framework adopts the design concept of hierarchical decoupling and intelligent decision-making, and consists of four modules: intelligent load generation layer, system resources and performance monitoring layer, dynamic tuning and control center, root cause analysis and report generation layer. Among them, the intelligent load generation layer supports mixed simulation of multi-modal AI loads, the dynamic tuning and control center realizes dynamic optimization of test parameters based on reinforcement learning (RL) algorithm, and the root cause analysis and report generation layer automatically locates performance bottlenecks and generates reports by unsupervised learning and time series correlation analysis. The experimental results show that the framework can effectively find the potential bottlenecks of the system, improve the test efficiency, and shorten the fault diagnosis cycle, which provides strong support for the performance optimization of AI server.

Keywords

Stress Testing , AI Server , High Concurrency Scenarios , Reinforcement Learning .

Metadata

DOI:

10.70393/6a696574.343131

ARK:

ark:/40704/JIET.v1n2a02

Pages: 7-12

References: 22

Disciplines: Intelligent Systems

Subjects: Other

Cite This Article

APA Style

Ren, X. (2026). Research on stress testing automation of ai server for high concurrency scenarios. Journal of Intelligence and Engineering Technology, 1(2), 7-12. https://doi.org/10.70393/6a696574.343131

Acknowledgments

Not Applicable.

FUNDING

Not Applicable.

INSTITUTIONAL REVIEW BOARD STATEMENT

Not Applicable.

DATA AVAILABILITY STATEMENT

Not Applicable.

INFORMED CONSENT STATEMENT

Not Applicable.

CONFLICT OF INTEREST

Not Applicable.

AUTHOR CONTRIBUTIONS

Not application.

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