10 citations · 36 across the 12 of their papers we have counts for
7 papers · 1 filter
A2Log: Attentive Augmented Log Anomaly Detection
Thorsten Wittkopp, Alexander Acker, Sasho Nedelkoski +4
Anomaly detection becomes increasingly important for the dependability and serviceability of IT services. As log lines record events during the execution of IT services, they are a…
Bellamy: Reusing Performance Models for Distributed Dataflow Jobs Across Contexts
Dominik Scheinert, Lauritz Thamsen, Houkun Zhu +4
Distributed dataflow systems enable the use of clusters for scalable data analytics. However, selecting appropriate cluster resources for a processing job is often not straightforw…
Learning Dependencies in Distributed Cloud Applications to Identify and Localize Anomalies
Dominik Scheinert, Alexander Acker, Lauritz Thamsen +2
Operation and maintenance of large distributed cloud applications can quickly become unmanageably complex, putting human operators under immense stress when problems occur. Utilizi…
Robust and Transferable Anomaly Detection in Log Data using Pre-Trained Language Models
Harold Ott, Jasmin Bogatinovski, Alexander Acker +2
Anomalies or failures in large computer systems, such as the cloud, have an impact on a large number of users that communicate, compute, and store information. Therefore, timely an…
TELESTO: A Graph Neural Network Model for Anomaly Classification in Cloud Services
Dominik Scheinert, Alexander Acker
Deployment, operation and maintenance of large IT systems becomes increasingly complex and puts human experts under extreme stress when problems occur. Therefore, utilization of ma…
Decentralized Federated Learning Preserves Model and Data Privacy
Thorsten Wittkopp, Alexander Acker
The increasing complexity of IT systems requires solutions, that support operations in case of failure. Therefore, Artificial Intelligence for System Operations (AIOps) is a field…