Automatic log file analysis enables early detection of relevant incidents such as system
failures. In particular, self-learning anomaly detection techniques capture patterns in log …

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 …

Most cloud applications use a large number of smaller sub-components (called
microservices) that interact with each other in the form of a complex graph to provide the …

Due to the sheer size of software logs, developers rely on automated techniques for log
analysis. One of the first and most important steps of automated log analysis is log …

Log parsing transforms log messages into structured formats, serving as the prerequisite
step for various log analysis tasks. Although a variety of log parsing approaches have been …

Artificial Intelligence for IT operations (AIOps) aims to combine the power of AI with the big
data generated by IT Operations processes, particularly in cloud infrastructures, to provide …

Logs, being run-time information automatically generated by software, record system events
and activities with their timestamps. Before obtaining more insights into the run-time status of …

System logs are a valuable source of information for monitoring and maintaining the security
and stability of computer systems. Techniques based on Deep Learning and Natural …

Logs as semi-structured text are rich in semantic information, making their comprehensive
understanding crucial for automated log analysis. With the recent success of pre-trained …

Logs are crucial to the management and maintenance of software systems. In recent years,
log analysis research has achieved notable progress on various topics such as log parsing …