• Deborah Mbula
• William Oloishuro
• Wilson Cheruiyot

Cloud computing can be most easily understood as the model by which you access shared resources in an easy and convenient manner over the Internet. It traces back to 1960 when it was predicted that computation might be used as a utility. Today, the cloud provides its users with a plethora of resources at their disposal. The most common usage of it is in file sharing, social network, storage, and also to avail better performance. To overcome these complexity and security a storage controller with an integrated component called cloud is being used. Cloud is used not only in storing the data but also as an efficient and flexible alternative to computer. Cloud Computing is a model for enabling on demand network access to a shared pool of configuration that can be rapidly released. Although researched in academia for decades, Machine learning is progressively moving into business computing use, credit to both the proliferation of low-priced cloud computing and gigantic amounts of data. As the growth of cloud computing increases many users interact with each other and traffic degree throughput issues are arising. The cloud computing growth is hampered by these traffic degree throughput issues. There are risks of data loss, slow updates and synchronization. A scaling neural networks for machine learning is needed for managing the degree of traffic that throughput updates of the cloud out to hundreds of thousands of servers to reaping seamless user results. This paper reviews deep learning neural networks implemented for flexible cloud server scalability.

"A Review of Flexible Cloud Server Scalability Using Machine Learning ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.10, Issue 11, page no.c263-c267, November-2023, Available :http://www.jetir.org/papers/JETIR2311236.pdf

"A Review of Flexible Cloud Server Scalability Using Machine Learning ", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.10, Issue 11, page no. ppc263-c267, November-2023, Available at : http://www.jetir.org/papers/JETIR2311236.pdf