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Configuring work factors in multiple tier configurations

Use this task to compute and configure work factors for your multiple tier configuration.

Before you begin

  • Install the product.
  • Install applications that are operational under a workload.

About this task

A work factor exists for every combination of transaction class, target web module, and processing tier. The work factor describes how heavily a request of the given transaction class loads the processing tier. You can define work factors at varying levels of granularity. The autonomic request flow manager (ARFM) uses work factors at the level of service class, target deployment target, and processing tier. You can define work factors at a variety of levels for any processing tier that is not a target tier or is not the one and only processing tier in the target module.

In a configuration that has multiple tiers, the work profiler automatically computes work factors for the target tier, which communicates directly with the on demand router (ODR). For any tiers that are deeper than the target tier, you must define work factors. If your deployment target contains both a target tier and a non-target tier, you must configure the work factors for both tiers because the work profiler cannot automatically compute work factors in that situation. You can compute the work factor by dividing the average processor utilization by the average number of executing requests per second. This task describes how to find these values and configure the work factor for your multiple tier configuration.

Procedure

  1. Generate traffic for a transaction class and module pair. You can generate traffic by using an application client or a stress tool.
  2. Monitor processor utilization in your configuration. Determine an average processor utilization. You need the processor utilization of all the machines that are involved in serving your traffic, and all machines that have performance interactions with them, to be at the configured limit that is defined with the Maximum CPU utilization property on the Operational policies > Autonomic managers > Autonomic request flow manager panel. Disable all the autonomic managers so that you can ensure the system does not make changes while you take the processor utilization measurement.
    • The application placement controller: Disable the application placement controller by putting it in manual mode. Click Operational policies > Autonomic managers > Application placement controller. Select the Enable check box to disable the application placement controller.
    • The autonomic request flow manager: You can set the arfmManageCpu custom property to false at the cell level to disable the ARFM.
    • Dynamic workload management: Disable dynamic workload management for each dynamic cluster. Click Servers > Dynamic clusters > dynamic_cluster_name > Dynamic WLM. Select the Dynamic WLM check box to disable dynamic workload management.
    If you disable the autonomic managers, you can add processor load through background tasks. Use an external monitoring tool for your hardware.
  3. Using the runtime charting in the administrative console, monitor the number of requests per second (throughput). Click Runtime operations > Runtime topology. You can view the number of requests per second.
  4. Compute the work factor for the deployment target. Use the following equation to calculate the work factor:
    work factor = (normalized CPU speed) * (CPU utilization) /
    (number of requests per second, measured at entry and exit of the target tier)
  5. Configure the work factor in the administrative console. You set the custom property on the deployment target, for example, a cluster of servers, or a stand-alone application server. For more information about the overrides that you can create with the workFactorOverrideSpec custom property, read about autonomic request flow manager advanced custom properties.
    1. Define a case for each tier in the deployment target. Each case is separated by a comma, and contains a pattern that is set to a value that is equal to the work factor that you calculated. The pattern defines the set of service classes, transaction classes, applications, or modules that you can override for the particular tier, as shown in the following example:
      service-class:transaction-class:application:module:[tier, optional]=value
      You can specify a wild card for any of the service class, transaction class, application, or module by entering a * symbol. Each pattern can include at most one application, at most one module, at most one service class, and at most one transaction class. The tier is optional, and represents the deployment target name and relative tier name. Set the value to a work factor override number or to none to define no override.
      In the following examples, work factor override values are set for two-tier configurations:
      • Set an override value to 100 for the one and only processing tier in the target cluster:
        *:*:*:*100
      • Set an override value to none for the first tier of the MyDynamicCluster cluster. Set an override value to 100 for the second tier of the MyDynamicCluster cluster in the default cell:
        *:*:*:*=none,*:*:*:*:MyDynamicCluster+2=100
      • Set an override value to none for the first tier. Set an override value to 0.7 for the CICS+1 tier in the DbCel cell:
        *:*:*:*=none,*:*:*:*:../DbCel/CICS=0.7
    2. Create the custom property in the administrative console. Click Servers > Dynamic clusters > dynamic_cluster_name > Custom properties > New. Set the name of the property to workFactorOverrideSpec. Set the value of the property to the string you created in the previous step.
    3. Save your configuration.

Results

Work factors are configured to override the work factor values that are created by the work profiler and support performance management of more than one tier.

What to do next

Repeat these steps for each transaction class module and non-target tier node pair. You also must configure the node speed for each external node. For more information about configuring the node, see configuring node computing power.

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時間戳記圖示 前次更新: July 9, 2016 11:18
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