Logs generated by large-scale software systems provide crucial information for engineers to
understand the system status and diagnose problems of the systems. Log parsing, which …

Widely adopted for their scalability and flexibility, modern microservice systems present
unique failure diagnosis challenges due to their independent deployment and dynamic …

DevOps has emerged as one of the most rapidly evolving software development paradigms.
With the growing concerns surrounding security in software systems, the DevSecOps …

Automated system log anomaly detection plays a crucial role in ensuring service reliability.
Existing methods incompletely utilize structured log entries, resulting in the loss of key …

Performance diagnosis systems are defined as detecting abnormal performance
phenomena and play a crucial role in cloud applications. An effective performance …

Log data is a crucial resource for recording system events and states during system
execution. However, as systems grow in scale, log data generation has become increasingly …

To ensure the stability and reliability of microservice systems, timely and accurate anomaly
detection is of utmost importance. Recently, considering the lack of labels in real-world …

Most existing large distributed systems have poor observability and cannot use the full
potential of machine learning-based behavior analysis. The system logs, which contain the …

The adoption of lightweight container technology enables the cross-architecture deployment
of tiny machine learning (TinyML) models, while the implementation of container escape …

Modern systems generate a massive amount of logs to detect and diagnose system faults,
which incurs expensive storage costs and runtime overhead. After investigating real-world …