Working with queuing network models

A queuing network (QN) model predicts future system utilization, throughput, queue length, and response time based on the impact of business drivers running on systems. A key feature of this model is that it enables you to perform what-if analysis to predict, for example, the impact of a system type change or a variance in system resources like CPU or memory based on the current model.

Types of queuing network models

TrueSight Capacity Optimization supports the following types of queuing network models:


The Customized queuing network model is deprecated in TrueSight Capacity Optimization version 11.3.01. BMC recommends that you use the easy-to-setup and maintain express queueing network model that provides the same what-if capabilities with a simplified workflow. See Deprecated and dropped features and components.

Overview of the QN model type

The following figure shows how an example of how an input-output table for a QN model appears in TrueSight Capacity Optimization.

Example of an input-output table for the QN model

The following table describes the Business Drivers (formerly known and shown in the figure as Workloads) and Systems in the example.

Business drivers


  • The model contains two business drivers: number of visits and orders received.
  • Based on the current (metric) value that is available, a target value can be set that determines the cutoff after which the model estimation terminates.
  • Target value is determined by target growth factor, which is the ratio between target and current value.
  • The current setup will not support a target growth factor of 4 because the upper limit predicted by the model is 2.05.
  • TrueSight Capacity Optimization warns you that the target values exceed the model thresholds by displaying the affected values in red.
  • A red indicator in the far-right column of the table alerts you that the given business driver violates the response time of 5 seconds.
  • The model contains a set of 6 systems.
  • The multiplicity of every existing system or resource can be chosen, and its speed variation be calculated based on TrueSight Capacity Optimization built-in benchmark data.
  • If the current number of CPUs are increased for the Apache_cluster system from 8 to 12, the calculated utilization of 33% does not violate the maximal permissible utilization of 70% (green indicator).
  • If, for the system bea_frontend, the number of CPUs is decreased from 8 to 5, a red indicator appears, showing that the utilization will be exceeded.
  • To obtain a better response time, a what-if analysis can be performed by upgrading the computer with a TrueSight Capacity Optimization benchmark.

The following figure shows the response time chart for the example.

Response time plot before computer upgrade

Beyond the given threshold, the response time experiences an exponential increase in value (the region shaded red).

The current system can be improved, as shown in the following figure.

Upgrading the computers to see the effect on the response time

Applying this change yields the plot shown in the following figure.

Response time plot after computer upgrade

The response time drops compared to the earlier values.

With TrueSight Capacity Optimization, you can simulate various scenarios to arrive at the solution that best corresponds to your needs.

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