Year: 2024
Type: article
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.
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4405765525