Unsupervised detection of microservice trace anomalies through service-level deep bayesian networks
The anomalies of microservice invocation traces (traces) often indicate that the quality of the
microservice-based large software service is being impaired. However, timely and …
microservice-based large software service is being impaired. However, timely and …
Opprentice: Towards practical and automatic anomaly detection through machine learning
Closely monitoring service performance and detecting anomalies are critical for Internet-
based services. However, even though dozens of anomaly detectors have been proposed …
based services. However, even though dozens of anomaly detectors have been proposed …
Identifying bad software changes via multimodal anomaly detection for online service systems
In large-scale online service systems, software changes are inevitable and frequent. Due to
importing new code or configurations, changes are likely to incur incidents and destroy user …
importing new code or configurations, changes are likely to incur incidents and destroy user …
Robust and rapid adaption for concept drift in software system anomaly detection
Anomaly detection is critical for web-based software systems. Anecdotal evidence suggests
that in these systems, the accuracy of a static anomaly detection method that was previously …
that in these systems, the accuracy of a static anomaly detection method that was previously …
Syslog processing for switch failure diagnosis and prediction in datacenter networks
Syslogs on switches are a rich source of information for both post-mortem diagnosis and
proactive prediction of switch failures in a datacenter network. However, such information …
proactive prediction of switch failures in a datacenter network. However, such information …
Interpretable Failure Localization for Microservice Systems Based on Graph Autoencoder
Accurate and efficient localization of root cause instances in large-scale microservice
systems is of paramount importance. Unfortunately, prevailing methods face several …
systems is of paramount importance. Unfortunately, prevailing methods face several …
Spatio-temporal factorization of log data for understanding network events
Understanding the impacts and patterns of network events such as link flaps or hardware
errors is crucial for diagnosing network anomalies. In large production networks, analyzing …
errors is crucial for diagnosing network anomalies. In large production networks, analyzing …
Auric: using data-driven recommendation to automatically generate cellular configuration
Cellular service providers add carriers in the network in order to support the increasing
demand in voice and data traffic and provide good quality of service to the users. Addition of …
demand in voice and data traffic and provide good quality of service to the users. Addition of …
Measurement and analysis on the packet delivery performance in a large-scale sensor network
Understanding the packet delivery performance of a wireless sensor network (WSN) is
critical for improving system performance and exploring future developments and …
critical for improving system performance and exploring future developments and …
Robust network compressive sensing
Networks are constantly generating an enormous amount of rich diverse information. Such
information creates exciting opportunities for network analytics. However, a major challenge …
information creates exciting opportunities for network analytics. However, a major challenge …