Predictive Analytics and Auto Remediation using Artificial Inteligence and Machine learning in Cloud Computing Operations

Authors: Shally Garg

DOI: https://doi.org/10.5281/zenodo.14950959

Short DOI: https://doi.org/g86q3x

Country: USA

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Abstract: This study investigated the application of Predictive analytics and auto-remediation in cloud computing operations. AI/ML algorithms analyze historical data to forecast future trends and potential issues, enabling proactive resource management and automated responses. This approach minimizes downtime, reduces manual effort, and optimizes resource allocation. However, successful implementation requires careful consideration of data quality, model accuracy, explainability, security, and human oversight. Future trends like XAI, real-time analytics, and AIOps promise even greater automation and efficiency in cloud operations.

Keywords: Predictive Analytics, Auto-Remediation, Cloud Computing, Aiops, Machine Learning, Deep Learning, Forecasting, Root Cause Analysis, Incident Management, Automation, Cloud Monitoring, Performance Optimization, Cost Optimization, Resource Management, Capacity Planning, Scalability, Efficiency, Cloud Security, Incident Response, Troubleshooting, Self-Healing, Predictive Maintenance

Paper Id: 232190

Published On: 2019-03-04

Published In: Volume 7, Issue 2, March-April 2019

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