• Mr. Bhushan Hiralal Patil
• Mr. Mohan Nikam
• Mr.arunvel A

Cloud computing has an emerged as an important relevenceto improve resource utilization, efficiency, flexibility,However, cloud platforms cause performance degradations due to their virtualization layer and may not be appropriate for the requirements of highperformance applications, such as machine learning. The Research tacklesthe problem of improving network performance in containerbasedcloud instances to create a viable alternative to runnetwork intensive machine learning applications.Our approach consistsof deploying container based machine learning based apps viaLXC (Linux Container) cloud instances to increase the available bandwidth & performance. soto evaluate the efficiency of this approach and the overheadadded by the container-based cloud environment, we ran a set of experiments to measure throughput, latency, bandwidthutilization, and completion times. The outcomes proves that thisapproach adds minimum overhead in cloud environment as wellas increases throughput and reduces latency.moreover, our approach demonstrates a suitable alternative for running ml applications.Containers are a lightweight virtualization solution to replace virtual machines for deploying cloud applications as they are less resource and time consuming. Easy deployment of applications on containers is done using FlexTuner which helps user to analyzeapplications with various network topologies improving transfer rate of large data sets which are required for machinelearning models.

Cloud Computing, Containers; virtualization, machine learning, Network Performance, Link Aggregation, Container-Based Cloud. Container Network , Performance

"Building cloud native Machine learning based applications", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.127-133, June-2019, Available :http://www.jetir.org/papers/JETIR1906602.pdf

"Building cloud native Machine learning based applications", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp127-133, June-2019, Available at : http://www.jetir.org/papers/JETIR1906602.pdf