This study examines the efficiency of automated testing in container orchestration using Kubernetes as an example. Modern IT environments require rapid, reliable, and scalable application deployment, made possible by advancements in containerization technologies and CI/CD automation. The research is based on an analysis of existing studies. The paper explores the theoretical foundations of container orchestration, including Kubernetes architecture, and the principles of automated testing, encompassing unit, integration, performance, and security testing. Practical aspects of integrating testing into CI/CD processes are presented, with a focus on rolling updates, blue-green, and canary deployments, which help minimize the risk of deploying defective code and reduce downtime. The study also discusses future developments in the field, emphasizing AI/ML integration for failure prediction, improved multi-cluster management, and enhanced security measures. The findings demonstrate that implementing automated testing improves the reliability and efficiency of container orchestration, playing a crucial role in optimizing modern IT infrastructures. The information provided in this study will be of interest to researchers in DevOps, automated testing, and container orchestration, as it contributes to a deeper theoretical understanding and practical optimization of quality assurance processes in distributed systems amid ongoing digital transformation.

automated testing, containerization, container orchestration, Kubernetes, CI/CD

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