Machine learning (ML) and deep learning (DL), in particular, are common tools for anomaly
detection (AD). With the rapid increase in the number of Internet-connected devices, the …

The auto-scaling feature is fundamental to serverless computing, and it automatically allows
applications to scale as needed. Hence, this allows applications to be configured to adapt to …

The growing complexity of cloud based software systems has resulted in incident
management becoming an integral part of the software development lifecycle. Root cause …

Distributed systems have been widely used in many safety‐critical areas. Any abnormalities
(eg, service interruption or service quality degradation) could lead to application crashes or …

Context: DevOps has recently become a mainstream solution for bridging the gaps between
development (Dev) and operations (Ops) enabling cross-functional collaboration. The …

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

As microservice and cloud computing operations increasingly adopt automation, the
importance of models for fostering resilient and efficient adaptive architectures becomes …

Disease surveillance is used to monitor ongoing control activities, detect early outbreaks,
and inform intervention priorities and policies. However, data from disease surveillance that …

Adversarial lateral movement via compromised accounts remains difficult to discover via
traditional rule-based defenses because it generally lacks explicit indicators of compromise …

Monitoring a microservice system may bring a lot of benefits to development teams such as
early detection of run-time errors and various performance anomalies. In this study, we …