(untitled) (International Journal of Engineering & Extended Technologies Research (IJEETR), 2021)
This paper explores cost optimization strategies for DevOps deployments in cloud environments by leveraging machine learning (ML) techniques. With the growing adoption of cloud services, managing costs while maintaining high performance and reliability has become critical. This study investigates various ML algorithms and their applications in predicting resource needs, automating scaling, and optimizing workloads. The findings demonstrate that integrating ML into DevOps practices can significantly reduce operational costs and improve efficiency