WLDF provides two elastic actions, scale up and scale down, that you can assign to a policy to perform a scaling operation. For more information on the scale up and scale down actions, see Elastic Actions. Only one scaling action can be assigned to a given policy.

For example, Example 6-1 shows the WLST commands to create and configure a policy that, when triggered, executes a scale up action. Note the following:

• The scale up action, scaleUp, is created. This action is configured to scale up the dynamic cluster, DynamicCluster, by one server instance.

• The policy, named highMark, is configured to be evaluated every 10 seconds.

• When the policy is triggered — that is, it is evaluated to true — the corresponding scale up action is executed.

Similarly, Example 6-2 shows the configuration of a policy that, when triggered, executes a scale down action. Note the following:

• The scale down action, scaleDown, is created. This action is configured to scale down the dynamic cluster, DynamicCluster, by one server instance.

• The policy, named LowMark, is configured to be evaluated every 10 seconds.

• When the policy is triggered — that is, it is evaluated to true — the corresponding scale down action is executed.

scaleUp=wn.lookupScaleUpAction('scaleUp')
if scaleUp == None:
  print "Creating scale up action"
  scaleUp=wn.createScaleUpAction('scaleUp')
scaleUp.setScalingSize(1)
scaleUp.setClusterName(DynamicCluster)
high=wn.createWatch('highMark')
high.setExpressionLanguage('EL')
high.getSchedule().setMinute('*')
high.getSchedule().setSecond('*/10')
high.getRuleType()
high.setAlarmType('AutomaticReset')
high.setAlarmResetPeriod(150000)
high.setRuleExpression("wls:ClusterHighThroughput('"+DynamicCluster+"', '10s', '30s', 250, 60)")
high.addNotification(scaleUp)
high.setEnabled(true)

scaleDown=wn.lookupScaleDownAction('scaleDown')
if scaleDown == None:
  print "Creating scale down action"
  scaleDown=wn.createScaleDownAction('scaleDown')
scaleDown.setScalingSize(1)
scaleDown.setClusterName(DynamicCluster)
low=wn.createWatch('lowMark')
low.setExpressionLanguage('EL')
low.getSchedule().setMinute('*')
low.getSchedule().setSecond('*/10')
low.getRuleType()
low.setAlarmType('AutomaticReset')
low.setAlarmResetPeriod(60000)
low.setRuleExpression("wls:ClusterLowThroughput('"+DynamicCluster+"', '10s', '60s', 50, 75)")
low.addNotification(scaleDown)
low.setEnabled(true)

Smart rules are prepackaged functions with a set of configurable parameters that allow you to create complex policy expressions just by specifying the values for these configurable parameters.

A smart rule can be used as a predicate within a policy expression, either alone or with other predicates to create a more complex policy expression. Smart rules policy expressions are specified using the Java Expression Language (EL). See Configuring Smart Rule Based Policies in Configuring and Using the Diagnostics Framework for Oracle WebLogic Server.

Smart rules can be used in policy-based scaling. Policy-Based Scaling Example shows the use of policies that use smart rules, wls:ClusterHighThroughput() and wls:ClusterLowThroughput(), in their rule expressions. These two smart rules are also shown in Example 6-1 and Example 6-2:

• Example 6-1 shows the wls:ClusterHighThroughput() smart rule. This smart rule measures whether the average throughput in a cluster is increasing, as indicated by the average value of the ThreadPoolRuntimeMBean.Throughput attribute in each Managed Server.

  As specified in this example, this smart rule is triggered — that is, it is evaluated to true — if the average Throughput value, collected at 10-second intervals over the previous 30 seconds, is greater than or equal to 250 on at least 60 per cent of the servers in the dynamic cluster, DynamicCluster. When this smart rule is triggered, it executes the scale up action, scaleUp, which starts up a server instance in the cluster.

• Example 6-2 shows the wls:ClusterLowThroughput() smart rule. This smart rule measures whether the average throughput in a cluster is decreasing, as indicated by the average value of the ThreadPoolRuntimeMBean.Throughput attribute in each Managed Server.

  As specified in this example, this smart rule is triggered — that is, it is evaluated to true — if the average Throughput value, collected at 10-second intervals over the previous 60 seconds, is less than 50 on at least 75 per cent of the servers in the dynamic cluster, DynamicCluster. When this smart rule is triggered, it executes the scale down action, scaleDown, which stops a server instance in the cluster.

For more information about creating and configuring smart rule-based policies:

• See Create and configure policies and actions in Administering Oracle WebLogic Server with Fusion Middleware Control using the Fusion Middleware Control console.

• See Smart Rule Reference in Configuring and Using the Diagnostics Framework for Oracle WebLogic Server.

You can create policies that use the wls:HighThroughput() and wls:LowThroughput() smart rules to scale a dynamic cluster up under high load, and then scale the dynamic cluster back down when the demand decreases.

The following topics describe the tasks for running a demonstration that shows policy-based scaling of a dynamic cluster:

• Prerequisites
  
• Setting the Environment
  
• Creating the Domain and its Resources
  
• Configuring and Starting the Apache Web Server
  
• Viewing Dynamic Server Configuration and Activity
  
• Using JMeter to Drive the Demo
  
• Re-running and Stopping the Elasticity Demo