Workload matchmaking in the cloud: Finding the Right VM Fit

Shanmugavadivelu, Priyadarshni (2025) Workload matchmaking in the cloud: Finding the Right VM Fit. World Journal of Advanced Engineering Technology and Sciences, 15 (3). pp. 187-195. ISSN 2582-8266

[thumbnail of WJAETS-2025-0932.pdf] Article PDF
WJAETS-2025-0932.pdf - Published Version
Available under License Creative Commons Attribution Non-commercial Share Alike.

Download ( 543kB)

Abstract

This article explores the multifaceted discipline of workload-to-VM matchmaking in cloud environments, presenting a comprehensive framework for optimizing the alignment between application requirements and infrastructure capabilities. The article examines the diverse landscape of specialized virtual machines offered by major cloud providers, each designed to excel in specific dimensions of computational performance. Through systematic workload profiling methodologies, organizations can develop empirical understanding of their applications' resource consumption patterns, creating the foundation for informed VM selection decisions. The article investigates benchmarking strategies that provide quantitative performance data alongside price-performance analysis frameworks that balance technical capabilities with financial considerations. The ongoing nature of optimization is addressed through exploration of cloud-native tools and continuous improvement strategies that adapt infrastructure as workloads evolve. By synthesizing technical analysis with business context, this article equips cloud practitioners with methodologies to enhance application performance, maximize resource utilization, and achieve sustainable cost optimization in increasingly complex cloud environments.

Item Type: Article
Official URL: https://doi.org/10.30574/wjaets.2025.15.3.0932
Uncontrolled Keywords: Workload-Vm Optimization; Cloud Resource Profiling; Performance Benchmarking; Price-Performance Analysis; Continuous Infrastructure Optimization
Depositing User: Editor Engineering Section
Date Deposited: 16 Aug 2025 12:50
Related URLs:
URI: https://eprint.scholarsrepository.com/id/eprint/4392