Multi-Cloud Infrastructure Provisioning with Auto Scaling

Anandha Kumar, Vishak (2024) Multi-Cloud Infrastructure Provisioning with Auto Scaling. Masters thesis, Dublin, National College of Ireland.

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Abstract

This paper presents an implementation strategy for provisioning and auto-scaling multi-cloud infrastructure across AWS and Azure, leveraging Infrastructure-as-Code (IaC) with Terraform. The framework integrates auto-scaling policies across both cloud platforms, enabling seamless resource scaling based on real-time demand. Businesses have taken it upon themselves to adopt multi-cloud strategies as cloud environments get more complex and the demand for more reliable and dynamic information technology architecture increases. This study examines the challenges and benefits of implementing a multi-cloud infrastructure that includes Microsoft Azure and Amazon Web Services (AWS). Businesses now confront several difficulties, including the possibility that a certain cloud provider may render them incapable of operating, as well as the provision of fault tolerance. It is only fitting that a reliable self-service environment that naturally satisfies the provisioning and auto-scaling requirements of multi-cloud needs be created in situations like these, where resources are limited and must be used to satisfy conflicting demands. In terms of its overall importance, the value of such research demonstrates that it improves recovery management, increases fault tolerance, and can increase cost efficiency through resource usage. Here, we demonstrate a specific auto-scaling approach that actively scales resources based on real-time demand by combining Azure Virtual Machine Scale Sets and AWS ECT Auto Scaling Groups. Additionally, single view capabilities with features like Prometheus and Grafana provide the foundation for enhancing performance and costs within the company by assisting in understanding resource utilization and reaction time behaviour. But I simply use the Cloud watch for monitoring.

Item Type:	Thesis (Masters)
Supervisors:	Name Email Salahuddin, Jawad UNSPECIFIED
Subjects:	Q Science > QA Mathematics > Electronic computers. Computer science T Technology > T Technology (General) > Information Technology > Electronic computers. Computer science Q Science > QA Mathematics > Computer software > Computer Security T Technology > T Technology (General) > Information Technology > Computer software > Computer Security
Divisions:	School of Computing > Master of Science in Cyber Security
Depositing User:	Ciara O'Brien
Date Deposited:	18 Jul 2025 09:19
Last Modified:	18 Jul 2025 09:19
URI:	https://norma.ncirl.ie/id/eprint/8188

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