Cloud Intelligence and AIOps Integration: A Framework for Autonomous IT Operations in Modern Cloud Environments

This article examines the integration of Cloud Intelligence and AIOps (Artificial Intelligence for IT Operations) in modern cloud engineering environments, focusing on converging AI-driven decision systems and workflow orchestration. The article analyzes how this integration enhances operational efficiency, system resilience, and cost optimization in cloud infrastructures while maintaining robust security and compliance standards. This article comprehensively examines automated resource management, predictive analytics, and self-healing capabilities, demonstrating how Cloud Intelligence transforms traditional IT operations into autonomous, adaptive systems. The findings reveal that implementing AIOps significantly improves incident response times, reduces manual intervention, and enables proactive maintenance through advanced anomaly detection and federated learning approaches. Furthermore, the article highlights the critical role of real-time data integration and dynamic workflow orchestration in achieving optimal cloud performance and reliability. This article contributes to the growing knowledge in cloud engineering by providing a structured framework for implementing Cloud Intelligence solutions. It offers insights into the future evolution of AI-driven cloud operations.

Authors

Publication Details

Journal
International Journal For Multidisciplinary Research
Published
2024-12-25
DOI
https://doi.org/10.36948/ijfmr.2024.v06i06.33643
Citations
1
Primary Topic
Big Data and Business Intelligence
Type
article
Field-Weighted Citation Impact
0.53
Controls
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article

Cloud Intelligence and AIOps Integration: A Framework for Autonomous IT Operations in Modern Cloud Environments

Sushil Prabhu Prabhakaran -
1 citations
International Journal For Multidisciplinary Research
Big Data and Business Intelligence
0.53
article

Cloud Intelligence and AIOps Integration: A Framework for Autonomous IT Operations in Modern Cloud Environments

Sushil Prabhu Prabhakaran -
article en
1 citations

Abstract

This article examines the integration of Cloud Intelligence and AIOps (Artificial Intelligence for IT Operations) in modern cloud engineering environments, focusing on converging AI-driven decision systems and workflow orchestration. The article analyzes how this integration enhances operational efficiency, system resilience, and cost optimization in cloud infrastructures while maintaining robust security and compliance standards. This article comprehensively examines automated resource management, predictive analytics, and self-healing capabilities, demonstrating how Cloud Intelligence transforms traditional IT operations into autonomous, adaptive systems. The findings reveal that implementing AIOps significantly improves incident response times, reduces manual intervention, and enables proactive maintenance through advanced anomaly detection and federated learning approaches. Furthermore, the article highlights the critical role of real-time data integration and dynamic workflow orchestration in achieving optimal cloud performance and reliability. This article contributes to the growing knowledge in cloud engineering by providing a structured framework for implementing Cloud Intelligence solutions. It offers insights into the future evolution of AI-driven cloud operations.

International Journal For Multidisciplinary ResearchVol. 6(6)
Industry, innovation and infrastructure
Openalex Percentile: Top 23%
Big Data and Business Intelligence
0.53
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