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 …

In order to meet stringent performance requirements, system administrators must effectively
detect undesirable performance behaviours, identify potential root causes, and take …

Software systems often record important runtime information in system logs for
troubleshooting purposes. There have been many studies that use log data to construct …

With the growth of software systems, logs have become an important data to aid system
maintenance. Log-based anomaly detection is one of the most important methods for such …

Logs are widely used by large and complex software-intensive systems for troubleshooting.
There have been a lot of studies on log-based anomaly detection. To detect the anomalies …

Anomaly detection plays an important role in management of modern large-scale distributed
systems. Logs, which record system runtime information, are widely used for anomaly …

Modern society is increasingly moving toward complex and distributed computing systems.
The increase in scale and complexity of these systems challenges O&M teams that perform …

Surprisingly, console logs rarely help operators detect problems in large-scale datacenter
services, for they often consist of the voluminous intermixing of messages from many …

Driven by the emerging business models (eg, digital sales) and IT technologies (eg, DevOps
and Cloud computing), the architecture of software is shifting from monolithic to microservice …

Multivariate time series are used in many science and engineering domains, including
health-care, astronomy, and high-performance computing. A recent trend is to use machine …