Machine learning inference is becoming a core building block for interactive web
applications. As a result, the underlying model serving systems on which these applications …

In 2013, AmazonWeb Services revolutionized the data warehousing industry by launching
Amazon Redshift, the first fully-managed, petabyte-scale, enterprise-grade cloud data …

Log-based anomaly detection has been widely studied and achieves a satisfying
performance on stable log data. But, the existing approaches still fall short meeting these …

The high complexity and dynamics of the microservice architecture make its application
diagnosis extremely challenging. Static troubleshooting approaches may fail to obtain …

The nature of machine learning (ML) applications exposes rich characteristics to underlying
network transport, yet little work has been done so far to systematically exploit these …

Fail-slow hardware is an under-studied failure mode. We present a study of 114 reports of
fail-slow hardware incidents, collected from large-scale cluster deployments in 14 …

Prompt and accurate detection of system anomalies is essential to ensure the reliability of
software systems. Unlike manual efforts that exploit all available run-time information …

The management of cloud service incidents (unplanned interruptions or outages of a
service/product) greatly affects customer satisfaction and business revenue. After years of …

Emerging applications---cloud computing, the internet of things, and augmented/virtual
reality---demand responsive, secure, and scalable datacenter networks. These networks …

The availability of data center services is jeopardized by various network incidents. One of
the biggest challenges for network incident handling is to accurately localize the failures …