  In this paper we analyze the performance issues involved in the generation of
auto- mated traffic reports for large IT infrastructures. Such reports allows
the IT manager to proactively detect possible abnormal situations and roll out
the corresponding cor- rective actions. With the ever-increasing bandwidth of
current networks, the design of automated traffic report generation systems is
very challenging. In a first step, the huge volumes of collected traffic are
transformed into enriched flow records obtained from diverse collectors and
dissectors. Then, such flow records, along with time series obtained from the
raw traffic, are further processed to produce a usable report. As will be
shown, the data volume in flow records is very large as well and requires
careful selection of the Key Performance Indicators (KPIs) to be included in
the report. In this regard, we discuss the use of high-level languages versus
low- level approaches, in terms of speed and versatility. Furthermore, our
design approach is targeted for rapid development in commodity hardware, which
is essential to cost-effectively tackle demanding traffic analysis scenarios.
