Performance testing is essential for contemporary software systems because it ensures reliability and user satisfaction (while keeping operational costs under control). Conventional performance testing activities still require expert knowledge, laborious scripting, and substantial time investment within modern DevOps workflows. Recent advances in generative and agentic AI create the opportunity to automate these processes. This work-in-progress paper explores the use of agentic AI to support end-to-end automation of software performance testing. We present an initial prototype that coordinates multiple specialized agents to extract contextual information from existing project artifacts, generate realistic performance test scenarios, execute tests using an established performance testing framework, and provide structured interpretations of the resulting metrics. We report early results from exploratory case studies of microservice-based systems from the DeathStarBench benchmark suite, which suggest that agentic workflows can autonomously produce executable performance tests and meaningful performance reports with limited human intervention, even when available context is incomplete or partially misleading. Such results illustrate the feasibility of agent-based performance testing and motivate a broader research agenda on AI-augmented performance engineering.
- An Agent-Based Approach to Automating Software Performance Testing (Work In Progress Paper)
- E Binder - Free University of Bozen-BolzanoXiaozhou Li - Free University of Bozen-BolzanoAndrea Alexander Janes - Free University of Bozen-Bolzano
- ICPE Companion '26: Companion of the 17th ACM/SPEC International Conference on Performance Engineering, pp.55-61
- 9798400723261
- the 17th ACM/SPEC International Conference on Performance Engineering (Florence, 04/05/2026–08/05/2026)
- ACM
New York - Online
- 7
- 979-8-4007-2326-1
(UNIBZ)97834424
991007330263101241 - WOS:001863210900010
- 2-s2.0-105044311948
- Open Access
- Faculty of Engineering
- English
- Conference proceeding
- Binder E, Li X, Janes A