We start with a welcome and conference introduction by Sebastian Meyen, the conference chair.

Followed by Prof. Dr. Odej Kao’s keynote:

Artificial Intelligence for IT Operations (AIOps) combines big data and machine learning to replace a broad range of IT operations tasks including availability, performance, and monitoring of services. By exploiting log, tracing, metric, and network data, AIOps aim at detecting service and system anomalies before these turn into failures. This talk will present the basic idea, business reasoning, and potential behind the AIOPs and introduce the typical structure of the corresponding platforms including the major data types used for the analysis. An overview of sample tools available for the development and operation cycle will be complemented by description of  typical pipeline for monitoring, anomaly detection, root cause analysis, and anomaly remediation and as well as incident visualization. A short insight into the suggested rules for AI-governance as well as into the scientific foundations of supervised machine learning for incident detection using log data will conclude the talk.