Enlisted are some of our contributions to the area of AIOps:

2021

Robust and Transferable Anomaly Detection in Log Data using Pre-Trained Language Models
Harald Odtt, Bogatinovski Jasmin, Alexander Acker, Nedelkoski Sasho, and Odej Kao In Proceedings of the 43th International Conference on Software Engineering (ICSE 2021) Workshop on Cloud Intelligence 2021 Workshop on Cloud Intelligence 2021. To appear. arXiv

MicroDiag: Fine-grained Performance Diagnosis for Microservice Systems
Wu L., Tordsson J., Bogatinovski J., Elmroth E., Kao O.
In Proceedings of the 43th International Conference on Software Engineering (ICSE 2021) Workshop on Cloud Intelligence 2021
HAL

Learning dependencies in distributed cloud applications to identify and localize anomalies
Scheinert D., Acker A., Thamsen L., Geldenghuys M. K., Kao O.
In 43-rd International Conference on Software Engineering, To appear. ACM, 2021. arxiv

Artificial Intelligence for IT Operations (AIOPS) Workshop White Paper
Bogatinovski J., Nedelkoski S., Acker A., Schmidt F., Wittkopp T., Becker S., Cardoso J., Kao O.
arXiv

2020

Self-Supervised Anomaly Detection from Distributed Traces
Bogatinovski J., Nedelkoski S., Cardoso J., Kao O. 2020
IEEE/ACM 13th International Conference on Utility and Cloud Computing (UCC), Leicester, UK, 2020, pp. 342-347.
arXiv

Multi-Source Anomaly Detection in Distributed IT Systems
Bogatinovski J., Nedelkoski S.
In 18th International Conference on Service-Oriented Computing, To appear, Dubai,United Arab Emirates, December 2020
arXiv

Self-Supervised Log Parsing
Bogatinovski J., Nedelkoski S., Acker A., J Cardoso, Kao O.
In European Conference on Machine Learning and Principles and Practice of Knowledge Discovery in Databases, ECML-PKDD 2020, pages 1–742, 2020
arXiv

Self-attentive classification-based anomaly detection in unstructured logs
Nedelkoski S., Bogatinovski J., Acker A., Cardoso J., Kao O.
In ICDM 2020: 20th IEEE International Conference on Data Mining, pages 1196–1201
arXiv

Multi-source distributed system data for AI-powered analytics
Nedelkoski S., Bogatinovski J., Mandapati AK., Becker S., Cardoso J., Kao O.
In ESOCC 2020: European Conference On Service-Oriented And Cloud Computing, pages 161–176. Springer International Publishing
Zenodo

Superiority of Simplicity: A Lightweight Model for Network Device Workload Prediction
Acker A., Wittkopp T., Nedelkoski S., Bogatinovski J., Kao O.
Superiority of simplicity: A lightweight model for network device workload prediction. In 15th Conference on Computer Science and Information Systems, pages 7–10. IEEE, 2020.
arXiv

Optimizing convergence for iterative learning of arima for stationary time series
Styp-Rekowski K., Schmidt F., Kao O.
In 2020 IEEE Inter-national Conference on Big Data, To appear. IEEE, 2020.
arxiv

Learning more expressive joint distributions in multimodal variational methods Nedelkoski S., Bogojevski M., Kao O.
In 2020 International Conference on Machine Learning, Optimization, and Data Science, LOD 2020, pages 137–149, 2020.
arxiv

Performance diagnosis in cloud microservices using deep learning
Wu L., Bogatinovski J., Nedelkoski S., Tordsson J., and Kao O.
In 18th International Conference on Service-Oriented Computing, To appear, Dubai,United Arab Emirates, December 2020. Springer.
arxiv

Microras: Automatic recovery in the absence of historical failure data for microservice systems Wu L., Tordsson J., Acker A., Kao, O.
In 2020 IEEE/ACM 13th International Conference on Utility and Cloud Computing (UCC), pages 227–236. IEEE, 2020
arxiv

Microrca: Root cause localization of performance issues in microservices
Wu L., Tordsson J., Elmroth E., Kao O. In NOMS 2020 IEEE/IFIP Network Operations and Management Symposium, pages 1–9. IEEE, 2020.
arxiv

Towards aiops in edge computing environments
Becker S., Schmidt F., Gulenko A., Acker A., Kao O.
In 2020 IEEE International Conference on Big Data, pages 3470–3475. IEEE, 2020
arxiv

Ai-governance andlevels of automation for aiops-supported system administration
Gulenko A., Acker A., Kao O., Liu F.
In The 29th International Conference on Computer Communications and Networks, pages 1–6. IEEE, 2020
link

Bitflow: An in situ stream processing framework
Gulenko A., Acker A., Schmidt F., Becker S., Kao O.,
In International Conference on Autonomic Computing and Self-Organizing Systems, pages 182–187.IEEE, 2020.
link

Telesto: A graph neural network model for anomaly classification in cloud services
Scheinert D., Acker A.
In 18th International Conference on Service-Oriented Computing, To appear, Dubai,United Arab Emirates, December 2020
arXiv

Decentralized federated learning preserves model and data privacy
Wittkopp T., Acker A.
In 18th International Conference on Service-Oriented Computing, To appear, Dubai,United Arab Emirates, December 2020
arXiv

Sensor artificial intelligence and its application to space systems - a whitepaper
Bearner A., Hübers H. M., Kao O., Schmidt F., Becker S., Denzler J., Matolin D., Haber D., Lucia S., Samek W., et al.
arxiv

Autoencoder-based condition monitoring and anomaly detection method for rotating machines
Ahmad S., Styp-Rekowski K., Nedelkoski S., Kao O.
In 2020 IEEE International Conference on Big Data, To appear. IEEE, 2020.
arxiv

Mary, hugo, and hugoi: Learning to schedule distributed data-parallel processing jobs on shared clusters
Tran V. T., Nedelkoski S., Thamsen L., Beilharz J., Kao O.
Concurrency and Computation: Practiceand Experience, page e5823, 2020.
link