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logpai/awesome-log-analysis: A list of awesome research on log analysis, anomaly ...

原作者: [db:作者] 来自: 网络 收藏 邀请

开源软件名称(OpenSource Name):

logpai/awesome-log-analysis

开源软件地址(OpenSource Url):

https://github.com/logpai/awesome-log-analysis

开源编程语言(OpenSource Language):


开源软件介绍(OpenSource Introduction):

Awesome Log Analysis

A curated list of awesome publications and researchers on log analysis, anomaly detection, fault localization, and AIOps.

Researchers

China (& HK SAR)
Michael R. Lyu, CUHK Dongmei Zhang, Microsoft Pengfei Chen, SYSU Dan Pei, Tsinghua
Pinjia He, CUHK-Shenzhen
USA
Yuanyuan Zhou, UCSD Tao Xie, UIUC Dawson Engler, Stanford Ben Liblit, Wisconsin–Madison
Canada
Ding Yuan, Toronto University Ahmed E. Hassan, Queen's University Weiyi Shang, Concordia University Zhen Ming (Jack) Jiang, York University
Wahab Hamou-Lhadj, Concordia University
UK
Europe
Australia
Ingo Weber, CSIRO

Conferences and Journals

Logs are a type of valuable data generated from many sources such as software, systems, networks, devices, etc. They have also been used for a number of tasks related to reliability, security, performance, and energy. Therefore, the research of log analysis has attracted interests from different research areas.

Datasets

Loghub

Papers

Surveys & Tutorials & Magazines

  1. [ACM Computing Survey] A Survey on Automated Log Analysis for Reliability Engineering
  2. [Blog] What is AIOps? Artificial Intelligence for IT Operations Explained
  3. [Book'14] I Heart Logs
  4. [Book'12] Logging and Log Management: The Authoritative Guide to Understanding the Concepts Surrounding Logging and Log Management, by Anton A. Chuvakin, Kevin J. Schmidt, Christopher Phillips.
  5. [Thesis] Log Engineering: Towards Systematic Log Mining to Support the Development of Ultra-large Scale Systems
  6. [IST'20] A Systematic Literature Review on Automated Log Abstraction Techniques
  7. [IEEE Software'16] Operational-Log Analysis for Big Data Systems: Challenges and Solutions

Logging

Log Compression

Log Parsing

Log Mining

Anomaly Detection

Failure Prediction

Failure Diagnosis

Others

License

This repo is under the MIT license.




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