Agilent Technologies J3972A User's Guide Page 15

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14 5967–9446
RMON Utilities—At a Glance
Alarms and Traps
Alarms and traps let you configure
RMON agents to alert you when
interesting activity occurs on the
network. You define what “inter-
esting activity” is, and you control
what happens when the agent
detects it.
For example, you might configure an
alarm to monitor octet counts per
second. When the count rises above
the value you specify, the alarm trig-
gers and sends a trap—a message to
your management station—indi-
cating that the count exceeded the
threshold you specified.
For details, see page 417.
Live Statistics
The RMON Utilities include several
tools for viewing live statistics.
Multi-Segment Statistics show
segment-level statistics from mul-
tiple agents on the same graph,
allowing you to compare statistics
from different segments with ease.
The statistics shown by this tool are
based on RMON’s Statistics group.
Node Statistics let you view the
entire node (host or station) table, or
you can display a graph of statistics
for specified nodes on the segment.
The statistics shown by this tool are
based on RMON’s Host group and
tokenRing Station table.
Traffic Matrix lets you view
activity between specified nodes as a
graph or a table of statistics. The
statistics shown by this tool are
based on RMON’s Matrix group.
For details, see page 455.
Historical Statistics
(including Baseline)
Historical Statistics lets you view
past network activity and develop
baselines that help you discern
patterns of activity, trends in
behavior, and exceptional events.
By looking at short-term statistics,
you can identify network perfor-
mance problems; long-term statistics
assist you in network configuration,
capacity planning, and network
segmentation.
Three studies can be viewed: hourly,
which shows data at 5-second inter-
vals; daily, at 30-second intervals;
and monthly, at 30-minute intervals.
You can also access historical data in
files created by the collector daemon,
allowing you to view long-term
trends and calculate baselines.
Baselines combine historical
measurements with statistical
algorithms to analyze network data.
In particular, baselines:
Highlight exceptional activity,
helping to pinpoint network
problems.
Show network patterns, helping
you discover what’s normal for
your site. This information is
useful when setting alarms that
trigger when something is
abnormal.
Reveal long-term trends, which is
useful when planning expansions
and purchasing equipment based
on utilization growth.
For details, see page 475.
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