Using AI for Real-Time Cloud-Based System Monitoring

This paper aims to discuss the application of the real-time cloud-based system-monitoring system with the help of artificial intelligence while describing its advantages, limitations, and possible developments. Due to the increase in cloud solution sophistication, AI solutions provide approaches for a massive co-scale scalability and the capacity to discover and dodge severe issues efficiently while improving overall efficiency. The critical capabilities of AI are, for example, anomaly detection, predictive analytics and automatic response. However, there are some issues that include; data availability issues, model bias issues, and the problems associated with model integration in order to support deployment of the AI ML. The paper explores prospects of AI in the monitoring of clouds with focus on; enhanced prediction mechanisms, edge computing and explainable AI.