AI-Powered Monitoring: Next-Generation Observability Solutions for Cloud Infrastructure

Authors

  • Sandeep Pochu Senior DevOps Engineer Author
  • Sai Rama Krishna Nersu Software Developer Author
  • Srikanth Reddy Kathram Sr. Technical Project Manager Author

DOI:

https://doi.org/10.60087/Japmi.Vol.02.Issue.01.Id.010

Keywords:

AI-Powered Monitoring, Next-Generation Observability, Cloud Infrastructure, Observability Solutions, Intelligent Monitoring, Cloud-Native Observability, Infrastructure Monitoring

Abstract

The paper proposes an advanced observability solution integrating AI-driven tools with Prometheus and Grafana for real-time system monitoring. It evaluates the impact on reducing downtime and improving predictive maintenance in cloud environments, marking a significant leap in operational efficiency.In the rapidly evolving landscape of cloud infrastructure, maintaining system reliability, performance, and scalability is more challenging than ever. Traditional monitoring approaches often struggle to keep pace with the dynamic and complex nature of modern cloud environments. This paper explores AI-powered monitoring, a transformative approach that leverages artificial intelligence and machine learning to deliver next-generation observability solutions. By analyzing vast amounts of data in real-time, AI-driven observability tools offer unparalleled insights into system behavior, enabling proactive detection of anomalies, predictive maintenance, and automated remediation. These innovations not only enhance system reliability but also empower organizations to optimize resource utilization and reduce operational costs. Through case studies and performance metrics, this paper demonstrates the critical role of AI in redefining monitoring strategies for cloud-native infrastructures, paving the way for a more resilient and efficient digital future.

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Published

2024-12-25

How to Cite

AI-Powered Monitoring: Next-Generation Observability Solutions for Cloud Infrastructure. (2024). Journal of AI-Powered Medical Innovations (International Online ISSN 3078-1930), 2(1), 140-152. https://doi.org/10.60087/Japmi.Vol.02.Issue.01.Id.010

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