Root cause analysis (RCA) in large-scale microservice systems is a critical and challenging
task. To understand and localize root causes of unexpected faults, modern observability …

Due to the large amount and high complexity of trace data, microservice trace analysis tasks
such as anomaly detection, fault diagnosis, and tail-based sampling widely adopt machine …

In distributed systems and microservice applications, tracing is a crucial observability signal
employed for comprehending their internal states. To mitigate the overhead associated with …

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 …

Distributed tracing has been widely adopted in many microservice systems and plays an
important role in monitoring and analyzing the system. However, trace data often come in …

Modern large-scale service-based systems such as microservice systems have become
increasingly complex, making it hard to localize anomalous services when various issues …

Microservice invocation anomalies can have a detrimental impact on user experience and
service revenue. While existing trace anomaly detection approaches typically focus on …

Since only a small number of traces generated from distributed tracing helps in
troubleshooting, its storage requirement can be significantly reduced by biasing the …

Microservice is a widely-adopted architecture for constructing cloud-native applications. To
test application resiliency, chaos engineering is widely used to inject faults proactively in …

Distributed tracing is cutting-edge technology used for monitoring, managing, and
troubleshooting native cloud applications. It offers a more comprehensive and continuous …