--A Brief Discussion on AIOps
On December 23, 2022, our hospital invited Dr. Liu Liangyuan to give a lecture on "A Brief Discussion on AIOps".
Teacher Liu Liangyuan, with a Bachelor's degree in Mathematics and Applied Mathematics from Soochow University and a PhD in Statistics from Shanghai University of Finance and Economics, joined China Mobile Hangzhou R&D Center after graduation and currently serves as a Technical Leader at Cisco Hangzhou R&D Center. Five years of AIOps development experience. In Chinese science and mathematics Journal of Multivariate Analysis、 Journal of Statistical Planning and Inference I have published papers in journals and have published 4 patents since I started working. Has won multiple group level awards such as China Mobile Group Technology Innovation Third Prize, Cisco Collab Hacks Red Level Prize, Quality Recognition Program Winner, etc. In this forum, Teacher Liu Liangyuan systematically introduced the background and application scenarios of AIOps.
At the beginning of the forum, Teacher Liu Liangyuan first introduced the background of AIOps and introduced the basic concepts of AIOps by analyzing the shortcomings of traditional Ops. With the expansion of enterprise business, IT systems have become increasingly complex, which has increased the demand for AIOps. AIOps combines traditional monitoring tools with streaming telemetry technology and uses artificial intelligence to analyze them. Artificial intelligence can analyze each data source and associate multiple anomalies to automatically identify problems, while also providing detailed information on how to solve the problem. Therefore, if AIOps can be used correctly, it can not only provide more visibility into potential issues, but also eliminate many manual troubleshooting and repair tasks.
Afterwards, Teacher Liu Liangyuan provided a detailed introduction to the application areas and specific scenarios of AIOps through a series of examples. AIOps mainly integrates and analyzes IT infrastructure APM、NPM、 Log and digital experience monitoring data are used to improve the efficiency of IT operation and maintenance processes. By using a complete AIOps solution that combines data collection, data analysis, and machine learning, IT Ops teams can support many specific application scenarios. For example, real-time monitoring of time-series data, semantic understanding of user feedback, resource management, user churn models, installation and maintenance quality checks, etc.
During the questioning session, students actively and enthusiastically raised questions about statistics related work, the ability requirements for AIOps, AIOps algorithms and business focus, etc. Teacher Liu Liangyuan patiently answered each question, and the students also benefited greatly. Through this industry forum, students have gained a deeper understanding of AIOps.
Author: Liu Wenyu
Image provided by: Liu Wenyu
