Autonomous cloud migration: Leveraging reinforcement learning for intelligent transformation

The emergence of autonomous cloud migration frameworks powered by reinforcement learning marks a transformative advancement in enterprise digital transformation. As organizations increasingly adopt cloud technologies, the complexity of migration processes demands more sophisticated solutions than traditional manual approaches. Reinforcement learning-based systems offer intelligent automation that optimizes resource allocation, enhances security measures, and streamlines migration workflows. These frameworks leverage advanced pattern recognition, dynamic workload management, and adaptive control mechanisms to ensure seamless transitions while maintaining operational stability. The integration of artificial intelligence and edge computing capabilities further enhances these systems, enabling real-time decision-making and proactive risk mitigation across complex cloud environments.

Authors

Publication Details

Journal
World Journal of Advanced Research and Reviews
Published
2025-04-29
DOI
https://doi.org/10.30574/wjarr.2025.26.1.1504
Primary Topic
Impact of AI and Big Data on Business and Society
Type
article
Field-Weighted Citation Impact
0.00
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article

Autonomous cloud migration: Leveraging reinforcement learning for intelligent transformation

Krupal Gangapatnam
World Journal of Advanced Research and Reviews
Impact of AI and Big Data on Business and Society
article

Autonomous cloud migration: Leveraging reinforcement learning for intelligent transformation

Krupal Gangapatnam
article en

Abstract

The emergence of autonomous cloud migration frameworks powered by reinforcement learning marks a transformative advancement in enterprise digital transformation. As organizations increasingly adopt cloud technologies, the complexity of migration processes demands more sophisticated solutions than traditional manual approaches. Reinforcement learning-based systems offer intelligent automation that optimizes resource allocation, enhances security measures, and streamlines migration workflows. These frameworks leverage advanced pattern recognition, dynamic workload management, and adaptive control mechanisms to ensure seamless transitions while maintaining operational stability. The integration of artificial intelligence and edge computing capabilities further enhances these systems, enabling real-time decision-making and proactive risk mitigation across complex cloud environments.

World Journal of Advanced Research and ReviewsVol. 26(1)
Openalex Percentile: Top 90%
Impact of AI and Big Data on Business and Society
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