AI-Agent Driven Test Environment Setup and Teardown for Scalable Cloud Applications

Abstract

The increasing complexity of cloud-native and distributed applications has intensified the need for efficient, scalable, and automated testing environments. Traditional manual or script-based test environment setup and teardown processes often struggle to keep pace with rapid deployment cycles and dynamic infrastructure changes. This paper proposes an AI-agent–driven framework that automates the provisioning, configuration, and dismantling of test environments in cloud ecosystems. Leveraging machine learning for resource optimization and intelligent orchestration, the AI agents dynamically allocate computing resources, configure application dependencies, and execute teardown procedures to minimize cost and idle time. The framework supports integration with popular CI/CD pipelines, enabling seamless scaling for multi-tenant and high-availability applications. Experimental evaluations demonstrate significant reductions in environment setup time, operational overhead, and infrastructure costs, while improving testing reliability and repeatability. The proposed approach offers a robust, adaptive solution for organizations aiming to accelerate development cycles without compromising quality in scalable cloud application testing.