A CMIS
typically contains capacity and performance related time-series data captured
from all sub-process levels. This data
is typically captured and stored to produce recurrence, exception and
forecasted reports and plans to the business.
An example of
some of the metrics that should be captured and stored within the CMIS:
•
Component
•
Server
information e.g. CPU, memory, disks etc
•
SAN
information e.g. Buffer cache, IO Response
•
Application
specific metrics
•
Network
usage e.g. Port, switch, router
•
Service
•
Service
response times
•
Transaction
volumes
•
Reliability, failure rates
•
Business
•
Forecast
information
•
Strategy
•
Finance
The
information captured can be kept native, filtered, aggregated and used for
longer term trend analysis.
Capturing and
storing the data into a single system provides many benefits which will be
explained throughout this white paper, but notably:
•
Different
metrics
•
Same
metrics, different sample
•
Combinations
of metrics for correlation
The ability
to bring information together from the different sub-processes onto a single
report or chart allows for correlation analysis to take place, for example
whether an increase in the numbers of transaction volumes has an effect on the
CPU or Memory utilization or whether business forecasts meet reality.
The information captured can be kept native,
filtered, aggregated and used for longer term trend analysis.
On Monday I'll be discussing why the CMIS is so important.
Jamie Baker
Principal Consultant
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