  This paper presents AUGURY, an application for the analysis of monitoring
data from computers, servers or cloud infrastructures. The analysis is based on
the extraction of patterns and trends from historical data, using elements of
time-series analysis. The purpose of AUGURY is to aid a server administrator by
forecasting the behaviour and resource usage of specific applications and in
presenting a status report in a concise manner. AUGURY provides tools for
identifying network traffic congestion and peak usage times, and for making
memory usage projections. The application data processing specialises in two
tasks: the parametrisation of the memory usage of individual applications and
the extraction of the seasonal component from network traffic data. AUGURY uses
a different underlying assumption for each of these two tasks. With respect to
the memory usage, a limited number of single-valued parameters are assumed to
be sufficient to parameterize any application being hosted on the server.
Regarding the network traffic data, long-term patterns, such as hourly or daily
exist and are being induced by work-time schedules and automatised
administrative jobs. In this paper, the implementation of each of the two tasks
is presented, tested using locally-generated data, and applied to data from
weather forecasting applications hosted on a web server. This data is used to
demonstrate the insight that AUGURY can add to the monitoring of server and
cloud infrastructures.
