Virtual Machine Cloud Infrastructure Management: Determining Differences between Azure Regions within the Same VM Size

Purpose: This article delves into the problem of selecting the most suitable IT infrastructure while opting for one of the leading cloud providers, specifically Microsoft Azure. The primary goal is to tackle a couple of business problems: are certain regions more advantageous for hosting infrastructure than others within the same VM sizes? Are there noticeable variations with the same sizes of VMs? Can we enhance the process of choosing infrastructure? Design/Methodology/Approach: The study employs CoreMark benchmarking to assess CPU performance across Microsoft Azure virtual machines, focusing on configurations with upto 16 CPUs due to subscription and cost constraints. It acknowledges potential regional performance variability not captured by standard benchmarks and uses Infrastructure as Code (IaC) with Bicep templates to automate VM deployment and testing. This approach provides a comprehensive understanding of VM performance and pricing within a specific Azure region. Findings: The results involve the automation of tests for different Virtual Machines (VMs) in Microsoft Azure using native Infrastructure as Code (IaC), all within the context of business decision-making. We will simplify the challenges related to VM series pricing and discuss how Infrastructure Management and IaC serves as efficient tools driving the testing process seamlessly across diverse Azure Regions. Practical Implications: The study aids businesses in optimizing resource allocation and choosing appropriate Azure regions by analyzing VM performance and cost trade-offs while considering regional variability. It uses Infrastructure as Code (IaC) for efficient VM deployment and benchmarking, enhancing cloud resource management and operational efficiency. Originality/Value: The study offers unique insights by integrating CoreMark benchmarking with regional performance considerations, highlighting potential discrepancies not captured by standard benchmarks. Its use of Infrastructure as Code (IaC) for automation provides a novel approach to efficiently manage and deploy cloud resources, adding significant value to cloud optimization strategies.