utilization data is at the foundation of capacity analysis. This data is
sampled values of performance counters such as: CPU, Memory, Disk, and Network.
The data set is from the busy hour as determined by the steps described above.
short-duration spikes that are statistical outliers, use a sample rate of one
sample every 15 seconds of each of the listed counters. Of the sample set, base
the calculation on the 95th percentile sample. The 95th percentile is the
smallest number that is greater than 95% of the numbers in a given set.
Counters are divided
into two categories:
- "Measurement" value:
value is only valid if the indicator values are
the indicator values are within acceptable levels, then the measurement value
is used in the forthcoming calculation to determine utilization.
- "Indicator" value:
value is a Boolean indication of
exceeding the maximum threshold is, of course,
the indicator value is
assume that capacity utilization was exceeded. If so, you must take steps to
return the system to < 100% utilization which may require hardware upgrade.
Capacity utilization is considered to be >= 100% if published sizing limits are exceeded for any given component. See the
Cisco Unified Contact Center Enterprise Design Guide at https://www.cisco.com/en/US/products/sw/custcosw/ps1844/products_implementation_design_guides_list.html for a quick reference on configuration limits and scalability constraints. For more information see Unified Communications in a Virtualized Environment.
For information on Unified CCE Solution
Compatibility Matrix see https://www.cisco.com/c/en/us/support/customer-collaboration/unified-contact-center-enterprise/products-device-support-tables-list.html.
For information on system constraints, see the
Sizing Tool. For example: if the
server on which a Unified CC PG is installed has a published capacity of 1,000
agents but there are 1,075 active agents at a particular time, the server is
considered to be greater than 100% utilization regardless of what might be
calculated using the methods described herein. The reason for this is that
although the server/application seems to be performing at acceptable levels,
any legitimate change in usage patterns could drive utilization beyond 100% and
cause a system outage because the published capacity was exceeded. Published
capacities seek to take into account differences between deployments and/or
changes in usage patterns without driving the server into the red zones of
performance thresholds. As such, all deployments must remain within these
published capacities to enjoy continued Cisco support.