Auto-learning systems for system and network management
Many systems and network management systems require tuning and tweaking
to become really useful. Much of this work can be done automatically
by machine-learning algorithms.
IFOST has developed an
HP Software Operations (formerly called HP OpenView Operations and before that VantagePoint Operations).
The autolearning package's main features are:
- Normality recognition for CPU utilisation, memory usage (including
swap utilisation), disk activity, system call behaviour and process
creation. The system learns what is "normal" for each machine on your
network, and alerts on unusual activity.
- Predictive modelling of capacity on disk space, memory use and
cpu load to alarm about future capacity problems.
The autolearner reports
trends and alarms on expected dates in the future when a resource is going to be
- Automatic log file discovery and filtering without system
administrator involvement. New application log files are found
and pertinent lines indicating a problem are displayed to operators.
The system has some basic intelligence but quickly learns
further what is important and not important
based on how operators respond.
Our experience has been that it takes less than a day of consulting
time (together with two to three weeks of computer learning time) to
start getting excellent, responsive and relevant messages in even the
most chaotic of sites.
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