Intelligent Fault Analysis with AIOps Technology - He, Yuhang; Pan, Yiming; Wang, Yong; Du, Shuqian; Xin, Qi (Journal of Theory and Practice of Engineering Science, 2024)
With the deep integration of artificial intelligence (AI) and operation and maintenance management, AIOPS (Artificial Intelligence operation and maintenance), as an emerging technology in the field of operation and maintenance management, has gradually attracted wide attention. AIOPS is committed to improving the efficiency and quality of traditional operations management through the introduction of automation and intelligent technology, and has become a hot topic in the industry. The development of AIOPS is inseparable from the identification of patterns and anomalies in data, which requires the application of machine learning, deep learning and other technologies. The rise of AIOPS is also due to the development of big data, cloud computing and container technology. These new technologies make traditional operation and maintenance monitoring means and processing methods powerless. Traditional troubleshooting methods can no longer meet the needs of large-scale and complex system monitoring and problem positioning. Therefore, this paper combines the implementation process and case analysis of AIOps system on intelligent fault analysis under the background of artificial intelligence, so as to analyze the development prospects and improvement suggestions of AIOps.