A survey on automated log analysis for reliability engineering

S He, P He, Z Chen, T Yang, Y Su, MR Lyu - ACM computing surveys …, 2021 - dl.acm.org
Logs are semi-structured text generated by logging statements in software source code. In
recent decades, software logs have become imperative in the reliability assurance …

Anomaly detection and failure root cause analysis in (micro) service-based cloud applications: A survey

J Soldani, A Brogi - ACM Computing Surveys (CSUR), 2022 - dl.acm.org
The proliferation of services and service interactions within microservices and cloud-native
applications, makes it harder to detect failures and to identify their possible root causes …

Robust anomaly detection for multivariate time series through stochastic recurrent neural network

Y Su, Y Zhao, C Niu, R Liu, W Sun, D Pei - Proceedings of the 25th ACM …, 2019 - dl.acm.org
Industry devices (ie, entities) such as server machines, spacecrafts, engines, etc., are
typically monitored with multivariate time series, whose anomaly detection is critical for an …

Logbert: Log anomaly detection via bert

H Guo, S Yuan, X Wu - 2021 international joint conference on …, 2021 - ieeexplore.ieee.org
Detecting anomalous events in online computer systems is crucial to protect the systems
from malicious attacks or malfunctions. System logs, which record detailed information of …

[PDF][PDF] Loganomaly: Unsupervised detection of sequential and quantitative anomalies in unstructured logs.

W Meng, Y Liu, Y Zhu, S Zhang, D Pei, Y Liu, Y Chen… - IJCAI, 2019 - nkcs.iops.ai
Recording runtime status via logs is common for almost computer system, and detecting
anomalies in logs is crucial for timely identifying malfunctions of systems. However …

Unsupervised detection of microservice trace anomalies through service-level deep bayesian networks

P Liu, H Xu, Q Ouyang, R Jiao, Z Chen… - 2020 IEEE 31st …, 2020 - ieeexplore.ieee.org
The anomalies of microservice invocation traces (traces) often indicate that the quality of the
microservice-based large software service is being impaired. However, timely and …

Experience report: Deep learning-based system log analysis for anomaly detection

Z Chen, J Liu, W Gu, Y Su, MR Lyu - arXiv preprint arXiv:2107.05908, 2021 - arxiv.org
Logs have been an imperative resource to ensure the reliability and continuity of many
software systems, especially large-scale distributed systems. They faithfully record runtime …

[HTML][HTML] System log clustering approaches for cyber security applications: A survey

M Landauer, F Skopik, M Wurzenberger, A Rauber - Computers & Security, 2020 - Elsevier
Log files give insight into the state of a computer system and enable the detection of
anomalous events relevant to cyber security. However, automatically analyzing log data is …

An empirical investigation of practical log anomaly detection for online service systems

N Zhao, H Wang, Z Li, X Peng, G Wang, Z Pan… - Proceedings of the 29th …, 2021 - dl.acm.org
Log data is an essential and valuable resource of online service systems, which records
detailed information of system running status and user behavior. Log anomaly detection is …

Fault management in software-defined networking: A survey

Y Yu, X Li, X Leng, L Song, K Bu… - … Surveys & Tutorials, 2018 - ieeexplore.ieee.org
Software-defined networking (SDN) has emerged as a new network paradigm that promises
control/data plane separation and centralized network control. While these features simplify …