An architecture for detecting infrastructure anomalies at Germany’s Federal Employment Agency

Abstract

The data centers of Germany’s Federal Employment Agency (FEA) provide an information technology (IT) infrastructure that is critical for both external stakeholders and internal processes. For FEA and many other organizations like it, it is essential that any IT infrastructure anomalies - deviations from normal behavior - are detected and their underlying causes are understood and, if appropriate, addressed. In this paper we develop a solution that can help increase the availability of an IT landscape such as FEA’s that is characterized by increasing technical complexity and increasing relevance of its applications. The solution detects IT service anomalies based on IT service access logs analyzed with time series methods. The solution also provides visualizations to support further analyses.