Advances and challenges in log analysis

By Adam J. Oliner, Archana Ganapathi, Wei Xu. Communications of the ACM, 2011

340 citations recorded by the source corpus.

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

Twenty Security Considerations for Cloud-Supported Internet of Things (2016, neutral): “In general, log analysis in large complex distributed systems still presents many unsolved challenges [61].”
Knowledge-Defined Networking (2016, background): “, see [15] and the references therein) and, in the context of the KDN architecture, it can also be used in networking.”
Tools and Benchmarks for Automated Log Parsing (2018, background): “Despite the tremendous value buried in logs, how to analyze them effectively is still a great challenge [7].”
A Survey on Automated Log Analysis for Reliability Engineering (2020, background): “Thus, logging relies heavily on human expertise [58, 71, 146, 149, 160].”
Experience Report: System Log Analysis for Anomaly Detection (2016, methodology): “Log analysis has been widely employed to improve the reliability of software systems in many aspects [35], such as anomaly detection [10], [28], [47], failure diagnosis [17], [31], [38], program verification [11], [42], and performance prediction [16].”
Anatomy of Threats to the Internet of Things (2019, background): “Few of these challenges may include: What does the cloud provider must record? If the log is decentralized then there would be variations in what is recorded on different systems, and resultantly there would be different interpretations of the logged data [96].”