Cloud Migration Framework: Transitioning from On-Premises to Azure Cloud for Improved System Reliability and Scalability

This article examines the transition from on-premises IT infrastructure to the Microsoft Azure cloud platform, aimed at enhancing the reliability, flexibility, and scalability of information systems. The purpose of the study is to analyze the migration process from an on-premises network to the Microsoft Azure cloud platform. The article explores the stages of migration, including the assessment of the current infrastructure, the design of an architecture based on cloud technologies, and the implementation of monitoring tools and process automation. The methodology is based on theoretical principles, practical recommendations, and examples of successful migrations. The findings demonstrate that transitioning to the Azure platform improves system availability and reliability through its distributed infrastructure and automated resource management tools. Cloud technologies enable organizations to scale computing power flexibly, adapting to changing demands. Azure also offers integration with other cloud services, expanding the functional capabilities of the ecosystem. This article will be useful for IT professionals, IT managers, cloud solution architects, and developers interested in efficient migration and optimization of IT structures. The conclusion emphasizes that a well-planned cloud transition can reduce operational costs, improve system resilience, and enhance the competitiveness of IT systems, thereby supporting organizational goals.

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Publication Details

Journal
The American Journal of Applied Sciences
Published
2025-02-01
DOI
https://doi.org/10.37547/tajas/volume07issue02-02
Citations
1
Primary Topic
Economic and Technological Systems Analysis
Type
article
Field-Weighted Citation Impact
2.76
Controls
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article

Cloud Migration Framework: Transitioning from On-Premises to Azure Cloud for Improved System Reliability and Scalability

1 citations
The American Journal of Applied Sciences
Economic and Technological Systems Analysis
2.76
article

Cloud Migration Framework: Transitioning from On-Premises to Azure Cloud for Improved System Reliability and Scalability

article en
1 citations

Abstract

This article examines the transition from on-premises IT infrastructure to the Microsoft Azure cloud platform, aimed at enhancing the reliability, flexibility, and scalability of information systems. The purpose of the study is to analyze the migration process from an on-premises network to the Microsoft Azure cloud platform. The article explores the stages of migration, including the assessment of the current infrastructure, the design of an architecture based on cloud technologies, and the implementation of monitoring tools and process automation. The methodology is based on theoretical principles, practical recommendations, and examples of successful migrations. The findings demonstrate that transitioning to the Azure platform improves system availability and reliability through its distributed infrastructure and automated resource management tools. Cloud technologies enable organizations to scale computing power flexibly, adapting to changing demands. Azure also offers integration with other cloud services, expanding the functional capabilities of the ecosystem. This article will be useful for IT professionals, IT managers, cloud solution architects, and developers interested in efficient migration and optimization of IT structures. The conclusion emphasizes that a well-planned cloud transition can reduce operational costs, improve system resilience, and enhance the competitiveness of IT systems, thereby supporting organizational goals.

The American Journal of Applied SciencesVol. 7(2)
TU Wien (AT)
Industry, innovation and infrastructure
Openalex Percentile: Top 13%
Economic and Technological Systems Analysis
2.76
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Cloud Migration Framework: Transitioning from On-Premises to Azure Cloud for Improved System Reliability and Scalability · The American Journal of Applied Sciences (2025) | TGRS Research Map | TGRS