Dr. Migrate: An AI-Driven Framework for Optimized VMware-to-Azure Cloud Migration

Cloud migration presents several challenges, including complex dependency mapping, cost optimization, and risk mitigation. Dr. Migrate is an AI-driven migration tool that automates these processes to streamline transitions from on-premises environments to Microsoft Azure. This paper explores Dr. Migrate’s architecture, methodology, and role in structured cloud migration planning and execution. The tool facilitates application dependency mapping, applies the Six R migration strategy for workload classification, and organizes wave-based phased migration planning. Additionally, it conducts total cost of ownership (TCO) analysis, manages inventory categorization, and enables performance-based rightsizing. The execution phase of cloud migration, including pre-migration testing, cutover strategies, and post-migration validation, is also discussed in detail. The benefits of using Dr. Migrate, such as improved migration timelines, cost savings, and enhanced planning accuracy, are examined alongside potential challenges, including bandwidth constraints and legacy system modernization. The paper concludes with insights into how Dr. Migrate significantly reduces migration complexity and explores future enhancements, such as AI-driven automation, that can further improve cloud transformation processes.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2024-12-10
DOI
https://doi.org/10.5281/zenodo.15054589
Primary Topic
Cloud Computing and Resource Management
Type
article
Field-Weighted Citation Impact
0.00
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article

Dr. Migrate: An AI-Driven Framework for Optimized VMware-to-Azure Cloud Migration

Zenodo (CERN European Organization for Nuclear Research)
Cloud Computing and Resource Management
article

Dr. Migrate: An AI-Driven Framework for Optimized VMware-to-Azure Cloud Migration

article en

Abstract

Cloud migration presents several challenges, including complex dependency mapping, cost optimization, and risk mitigation. Dr. Migrate is an AI-driven migration tool that automates these processes to streamline transitions from on-premises environments to Microsoft Azure. This paper explores Dr. Migrate’s architecture, methodology, and role in structured cloud migration planning and execution. The tool facilitates application dependency mapping, applies the Six R migration strategy for workload classification, and organizes wave-based phased migration planning. Additionally, it conducts total cost of ownership (TCO) analysis, manages inventory categorization, and enables performance-based rightsizing. The execution phase of cloud migration, including pre-migration testing, cutover strategies, and post-migration validation, is also discussed in detail. The benefits of using Dr. Migrate, such as improved migration timelines, cost savings, and enhanced planning accuracy, are examined alongside potential challenges, including bandwidth constraints and legacy system modernization. The paper concludes with insights into how Dr. Migrate significantly reduces migration complexity and explores future enhancements, such as AI-driven automation, that can further improve cloud transformation processes.

Zenodo (CERN European Organization for Nuclear Research)
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Cloud Computing and Resource Management
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