AI for Cloud Ops Transformation and Innovation
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© 2024 by IJCTT Journal
Volume-72 Issue-4
Year of Publication : 2024
Authors : Vishal Diyora
DOI :  10.14445/22312803/IJCTT-V72I4P118

How to Cite?

Vishal Diyora, "AI for Cloud Ops Transformation and Innovation," International Journal of Computer Trends and Technology, vol. 72, no. 4, pp. 140-144, 2024. Crossref, https://doi.org/10.14445/22312803/IJCTT-V72I4P118

Abstract
This paper examines the role of Artificial Intelligence (AI) in Cloud Operations (CloudOps), exploring how AI and Machine Learning (ML) are revolutionizing the field of cloud computing. It highlights the ways in which AI enhances CloudOps by optimizing resource utilization, improving security measures, and driving innovative solutions in cloud management. The research focuses on the deployment of ML for data analysis, the effectiveness of real-time monitoring, and the implementation of predictive analytics for efficient scaling, latency management, and stringent security enforcement.
The paper also addresses the critical challenges associated with the integration of AI into CloudOps, including issues of trust and reliability in AI systems, and the ethical considerations in AI deployment. It underscores the importance of transparent and accountable AI systems that align with ethical standards and regulatory compliance.
This study is particularly beneficial for IT professionals, cloud operation managers, and organizations looking to integrate AI into their cloud infrastructure. It offers valuable insights for those seeking to understand the potential benefits and challenges of AI in CloudOps. Academics and researchers in the fields of cloud computing and AI will find this paper a useful resource for understanding the current state and prospects of AI in cloud management. By highlighting both the advancements and the hurdles in the field, this paper serves as a comprehensive guide for anyone interested in the intersection of AI and CloudOps and its implications for the future of digital transformation in enterprises.

Keywords
Artificial Intelligence (AI), Autonomous Decision-Making, Cloud Computing Efficiency, Cloud Operations (CloudOps), Cloud Security.

Reference

[1] Brien Posey, Reducing Latency with EC2 Placement Groups, AWS Insider.net, 2017. [Online]. Available: https://awsinsider.net/articles/2017/06/12/ec2-placement-groups.aspx
[2] Enterprise Cloud Index, Nutanix. [Online]. Available: https://www.nutanix.com/enterprise-cloud-index
[3] What Is Shadow IT?, Cisco. [Online]. Available: https://www.cisco.com/c/en/us/products/security/what-is-shadow-it.html
[4] Raj Pathak, Ensure Security and Compliance, Linkedin. [Online]. Available: https://www.linkedin.com/pulse/securing-cloud-ai-machine-learning-raj-pathak
[5] Will Kelly, Rein in Services to Avoid Wasted Cloud Spend, TechTarget, 2023. [Online]. Available: https://www.techtarget.com/searchcloudcomputing/tip/Rein-in-services-to-avoid-wasted-cloud-spend/
[6] Responsible AI Practices, AI, Google. [Online]. Available: https://ai.google/responsibility/responsible-ai-practices/
[7] What is a Data Lake?, AWS, Amazon. [Online]. Available: https://aws.amazon.com/what-is/data-lake/