International Journal For Multidisciplinary Research

E-ISSN: 2582-2160   •   Impact Factor: 9.24

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Azure Migrate: A Comprehensive Framework for Discovery, Assessment, and Dependency Analysis in VMware-to-Azure Cloud Transitions

Author(s) Venkata Raman Immidisetti
Country United States
Abstract The rapid adoption of cloud computing has necessitated structured methodologies for migrating VMware workloads to Microsoft Azure. This paper examines Azure Migrate as a comprehensive solution for discovery, assessment, and migration of on-premises workloads. Through its agentless discovery mechanism, Azure Migrate provides real-time visibility into infrastructure while minimizing disruptions. Its dependency analysis ensures seamless workload transitions by identifying interdependencies, reducing operational risks, and maintaining business continuity. The platform’s assessment framework extends to SQL Server, web applications, and large-scale VMware deployments, offering insights into resource utilization, cost estimation, and performance optimization. Additionally, automated migration workflows and integration with Azure-native services enhance efficiency, ensuring a smooth transition. This study highlights Azure Migrate as a scalable and structured framework that simplifies cloud adoption through continuous discovery, predictive analytics, and intelligent workload placement. By bridging on-premises VMware environments with modern cloud infrastructures, Azure Migrate empowers organizations to execute data-driven, cost-effective, and efficient cloud migration strategies.
Keywords Cloud migration, Azure Migrate, VMware to Azure, dependency analysis, workload assessment, agentless discovery, enterprise cloud transformation.
Field Engineering
Published In Volume 2, Issue 1, January-February 2020
Published On 2020-01-08
DOI https://doi.org/10.36948/ijfmr.2020.v02i05.41113
Short DOI https://doi.org/g9dm6k
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E-ISSN 2582-2160
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