10 citations · 49 across the 10 of their papers we have counts for
12 papers
Failure Identification from Unstable Log Data using Deep Learning
Jasmin Bogatinovski, Sasho Nedelkoski, Li Wu +2
The reliability of cloud platforms is of significant relevance because society increasingly relies on complex software systems running on the cloud. To improve it, cloud providers…
Data-Driven Approach for Log Instruction Quality Assessment
Jasmin Bogatinovski, Sasho Nedelkoski, Alexander Acker +2
In the current IT world, developers write code while system operators run the code mostly as a black box. The connection between both worlds is typically established with log messa…
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…
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…
Hugo: A Cluster Scheduler that Efficiently Learns to Select Complementary Data-Parallel Jobs
Lauritz Thamsen, Ilya Verbitskiy, Sasho Nedelkoski +5
Distributed data processing systems like MapReduce, Spark, and Flink are popular tools for analysis of large datasets with cluster resources. Yet, users often overprovision resourc…
Autoencoder-based Condition Monitoring and Anomaly Detection Method for Rotating Machines
Sabtain Ahmad, Kevin Styp-Rekowski, Sasho Nedelkoski +1
Rotating machines like engines, pumps, or turbines are ubiquitous in modern day societies. Their mechanical parts such as electrical engines, rotors, or bearings are the major comp…