AI-Driven Cost Optimization in SAP Cloud Environments: A Technical Research Paper
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064


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Research Paper | Information Technology | India | Volume 11 Issue 4, April 2022 | Popularity: 5.2 / 10


     

AI-Driven Cost Optimization in SAP Cloud Environments: A Technical Research Paper

Harikrishna Madathala, Balaji Barmavat, Krupa Satya Prakash Karey, Balamuralikrishnan


Abstract: This research paper explores the application of artificial intelligence (AI) techniques for cost optimization in SAP cloud environments. As organizations increasingly migrate their SAP workloads to the cloud, managing and optimizing cloud expenditure becomes crucial. This study investigates how AI can be leveraged to analyze data, recommend optimal resource allocation, determine appropriate instance sizing, and develop dynamic scaling strategies to reduce cloud costs. The research combines theoretical frameworks with practical methodologies, addressing the challenges and limitations of implementing AI-driven cost optimization in SAP cloud deployments. The findings indicate that AI-powered solutions can significantly enhance cost efficiency in SAP cloud environments, paving the way for more sustainable and economical cloud operations.


Keywords: SAP Cloud, Cost Optimization, Artificial Intelligence, Machine Learning, Cloud Computing, Resource Allocation, Predictive Analytics, Dynamic Scaling, Cloud Economics


Edition: Volume 11 Issue 4, April 2022


Pages: 1404 - 1412


DOI: https://www.doi.org/10.21275/SR241017125233


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Harikrishna Madathala, Balaji Barmavat, Krupa Satya Prakash Karey, Balamuralikrishnan, "AI-Driven Cost Optimization in SAP Cloud Environments: A Technical Research Paper", International Journal of Science and Research (IJSR), Volume 11 Issue 4, April 2022, pp. 1404-1412, https://www.ijsr.net/getabstract.php?paperid=SR241017125233, DOI: https://www.doi.org/10.21275/SR241017125233

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