
International Journal on Science and Technology
E-ISSN: 2229-7677
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Impact Factor: 9.88
A Widely Indexed Open Access Peer Reviewed Multidisciplinary Bi-monthly Scholarly International Journal
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Volume 16 Issue 2
2025
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Best Practices for Configuring and Optimizing Virtual Machines in Microsoft Azure
Author(s) | AzraJabeen Mohamed Ali |
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Country | United States |
Abstract | As businesses increasingly migrate to cloud computing platforms, optimizing virtual machine (VM) configurations in Microsoft Azure has become essential for maximizing performance, cost-efficiency, and security. This paper explores best practices for configuring and optimizing Azure virtual machines to meet the diverse needs of enterprises. The study covers critical aspects, including selecting the appropriate VM size and type, optimizing storage performance, configuring networking settings for low latency and high throughput, and leveraging Azure's built-in monitoring tools to track and adjust resources in real-time. Additionally, it examines strategies for ensuring high availability, improving disaster recovery capabilities, and enhancing security through the use of Azure-specific features such as Azure Security Center and virtual networks. Furthermore, this research provides insights into the integration of automation tools for seamless VM provisioning and scaling, ultimately improving operational efficiency and reducing manual errors. The findings aim to provide IT professionals and organizations with a comprehensive framework for deploying and maintaining highly optimized virtual machine environments in Azure, ensuring better resource utilization, lower costs, and improved performance for mission-critical workloads. |
Field | Engineering |
Published In | Volume 16, Issue 2, April-June 2025 |
Published On | 2025-04-15 |
Cite This | Best Practices for Configuring and Optimizing Virtual Machines in Microsoft Azure - AzraJabeen Mohamed Ali - IJSAT Volume 16, Issue 2, April-June 2025. DOI 10.71097/IJSAT.v16.i2.3726 |
DOI | https://doi.org/10.71097/IJSAT.v16.i2.3726 |
Short DOI | https://doi.org/g9fmwk |
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