A Survey On Log Research Of AIOps: Methods and Trends

• Published in: Mobile networks and applications Vol. 26; no. 6; pp. 2353 - 2364
• Main Authors: Zhaoxue, Jiang, Tong, Li, Zhenguo, Zhang, Jingguo, Ge, Junling, You, Liangxiong, Li
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.12.2021; Springer Nature B.V
• Subjects: Artificial intelligence; Cloud computing; Communications Engineering; Computer Communication Networks; Electrical Engineering; Engineering; Internet of Things; IT in Business; Mobile computing; Networks; Trends; Log analysis; Log enhancement; Log parsing; AIOps
• ISSN: 1383-469X; 1572-8153
• DOI: 10.1007/s11036-021-01832-3

With the development of Artificial Intelligence (AI), Internet of Things (IoT), cloud computing, new-generation mobile communication, etc., digital transformation is changing the technical architecture of IT systems. It brings more requirements for performance and reliability. The traditional human-dependent development and maintenance methods are overwhelmed, and need to transform to Artificial Intelligence for IT Operations (AIOps). As one of the most useful data resources in IT system, the log plays an important role in AIOps. There are many research on enhancing log quality, analyzing log structure, understanding system behavior, helping users to mine the effective information in logs. Based on the characteristics of logs and different strategies, this paper reviews and categorizes the existing works around the three key processes in the log processing framework of log enhancement, log parsing, and log analysis in academia, and establishes evaluation indicators for comparison and summary. Finally, we discussed the potential directions and future development trends.