Predictive Analysis of Client Applications on Multi-cloud to Optimize Cost

Khan, Muhammad Osama (2023) Predictive Analysis of Client Applications on Multi-cloud to Optimize Cost. Masters thesis, Dublin, National College of Ireland.

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Abstract

A key challenge for enterprises in the era led by cloud services is maintaining client application efficiency in costs, especially on multi-cloud platforms. In this paper, a predictive analytical approach for cost-effective application operation across AWS, Azure, and GCP platforms is introduced. Four-year billing patterns for client applications were predicted through data collection and simulation on actual billing patterns from e-commerce event data. This innovative approach not only predicts these prices but also takes it a step further by incorporating a cost optimization technique that deliberately makes use of the most cost-effective offerings among the three cloud providers. This approach will increase the efficiency of resource allocation and reduce operational costs in multi-cloud systems by up to 34%. Additionally, businesses may continuously improve their cloud plans, ensuring continued alignment with their financial goals, by evaluating and comparing the predicted data with actual operational bills on a monthly basis. In the rapidly changing computing environment, this agility, together with the insights provided by the study, opens the way for more economically and environmentally sound cloud implementation.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Lugones, Diego UNSPECIFIED
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Cloud computing H Social Sciences > HF Commerce > Electronic Commerce
Divisions:	School of Computing > Master of Science in Cloud Computing
Depositing User:	Tamara Malone
Date Deposited:	20 Sep 2024 13:12
Last Modified:	20 Sep 2024 13:12
URI:	https://norma.ncirl.ie/id/eprint/7063

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