Content area

Abstract

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.

Details

Title
A Survey On Log Research Of AIOps: Methods and Trends
Author
Jiang, Zhaoxue 1   VIAFID ORCID Logo  ; Li, Tong 2 ; Zhang, Zhenguo 1 ; Ge, Jingguo 2 ; You, Junling 2 ; Li, Liangxiong 2 

 Chinese Academy of Sciences, Institute of Information Engineering, Beijing, China (GRID:grid.9227.e) (ISNI:0000000119573309); University of Chinese Academy of Sciences, School of Cyber Security, Beijing, China (GRID:grid.410726.6) (ISNI:0000 0004 1797 8419) 
 Chinese Academy of Sciences, Institute of Information Engineering, Beijing, China (GRID:grid.9227.e) (ISNI:0000000119573309) 
Pages
2353-2364
Publication year
2021
Publication date
Dec 2021
Publisher
Springer Nature B.V.
ISSN
1383469X
e-ISSN
15728153
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2628405348
Copyright
© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2022.