The smart rules are organized into the following two categories:
Cluster Scope Smart Rules — Rules that are applied to every active Managed Server instance in a dynamic cluster. All cluster scope smart rules must be defined in policies that are run on the Administration Server.
Server Scope Smart Rules — Rules that are applied only to the local WebLogic Server instance on which the associated policies are run. You can execute policies containing server scope smart rules on the Administration Server or any individual Managed Server in the domain.
All smart rules involve the collection of metric values, which is the process of gathering data needed for monitoring system state and performance. Metrics are exposed to WLDF as attributes on qualified MBeans. Smart rules cause WLDF to gather values from selected MBean attributes at a specified sampling rate and retain those values for a specified duration of time. This allows you to track trends in metric changes in a server or cluster over time.
When you configure a smart rule, you always specify the following parameters:
Note:
Sampling rates and retention windows are completely independent of policy schedules. A policy schedule determines only when a smart rule is evaluated; the policy schedule does not determine the sampling rate or retention window.
sampling rate
The sampling rate is the frequency with which a metric value is collected. For example, a sampling rate of 30 seconds means that the value of an MBean attribute is collected every 30 seconds.
Each smart rule has a default sampling rate. When you are configuring a smart rule using either the WebLogic Server Administration Console or Fusion Middleware Control, you can accept the default sampling rate that is provided in the configuration assistant. However, when you configure a smart rule using WLST, REST, or JMX, you need to explicitly specify the sampling rate.
The sampling rate is a String value that can be specified using the following syntax:
amount[unit]
In the preceding syntax:
amount represents an integer.
unit] represents seconds, minutes, or hours. Each can be abbreviated to the first letter. For example: seconds can be abbreviated to s.
The default sampling rate time unit is seconds.
You may include a space character between amount and unit.
For example, any of the following can be used to specify 30 seconds:
"30"
"30 seconds"
"30snds"
"30s"
retention window
The retention window is the period of time during which collected samples are retained in an internal buffer for evaluation. For example, a retention window of 5 minutes causes the samples collected during the previous 5 minutes to be retained. As each new sample is collected, the oldest sample is removed.
Smart rules function by calculating the average value of a particular metric that has been collected over the period of time corresponding to the retention window. Obtaining average values allows you to obtain a more representative view of changes, and trends in those changes, that are occurring in a server, cluster, or operational environment of WebLogic Server.
The retention window you specify is a String value that uses the same syntax as the sampling rate:
amount[unit]
The time unit can be seconds, minutes, or hours, and each can be abbreviated. The default time unit in smart rule retention windows is minutes, which can be abbreviated to m. For example, any of the following can be used to specify 10 minutes:
"10"
"10 minutes"
"10mts"
"10m"
threshold value
The threshold value is an arbitrary value against which the average value of all metrics collected during a retention window is compared. If the average value meets the smart rule's comparison criteria for the threshold value, the smart rule can be evaluated to true, assuming all other conditions set in the smart rule are met.
For example, if you want a smart rule to be evaluated as true if the average number of idle threads in a cluster is greater than or equal to a specific number, you can enter that number as the threshold value in the ClusterHighIdleThreads smart rule, which monitors a cluster for a high idle thread count. In this context, the threshold value you specify for this smart rule is referred to as the high threshold value because the cluster is monitored to measure whether the average number of idle threads is greater than or equal to that threshold.
By contrast, if you want a smart rule to be evaluated as true if the average free heap in a cluster falls below a certain amount, you enter that amount as the threshold value in the ClusterLowHeapFreePercent smart rule, which monitors a cluster for a low free heap. In this context, this threshold value yo specify for this smart rule is referred to as the low threshold value because the cluster is monitored to measure whether the average free heap amount is less than that threshold.
Note that smart rules vary with regard to how the average collected metric value must compare to the threshold value. Some smart rules require that the average collected value must be greater than or equal to the threshold; some require that the average must be greater than the threshold; some require the average to be less than or equal to the threshold; and so on.
A cluster scope smart rule is one that is applied to all active nodes in a cluster, and that must be executed from a policy on the Administration Server. The set of cluster scope smart rules provided by WLDF are listed and summarized in Table A-2. For each smart rule, Table A-2 identifies the following:
The specific metric, typically an MBean attribute, that is sampled
The condition that causes the smart rule to be evaluated to true if, over the course of the retention window, the number of servers with an average metric value that meets specific comparison criteria against the threshold value is greater than or equal to a specified percentage of all servers in the cluster.
Table A-1 Summary or Administration Server Scope Smart Rules
| Smart Rule | Metric | Condition Required for Evaluation to true |
|---|---|---|
|
|
The average |
|
|
|
The average |
|
|
|
The average |
|
|
|
The average |
|
|
|
The average |
|
|
|
The average |
|
|
|
The average |
|
|
|
The average |
|
|
|
The average |
|
|
|
The average |
|
|
|
The average |
|
|
|
The average |
|
|
|
The average |
|
|
|
The average |
|
|
|
The average |
|
|
|
The average |
|
|
Specified MBean attribute value |
Any metric visible through JMX satisfies the specified comparison criteria with the threshold value. (This smart rule is a general form of cluster scope rule.) |
|
|
|
The average |
This 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. You can use this rule to determine whether cluster capacity can be safely reduced; for example, by executing a scale down action.
Target: Administration Server
Description
This smart rule evaluates to true if the number of Managed Servers with an average ThreadPoolRuntimeMBean.Throughput value that satisfies the low threshold comparison criteria is greater than or equal to the specified percentage of all servers in the cluster.
To use this smart rule, specify:
The sampling rate and retention window for the ThreadPoolRuntimeMBean.Throughput attribute
Low Throughput threshold value
Percentage of servers in the cluster with an average Throughput value that must be less than the low Throughput threshold value in order for the rule to evaluate to true
Syntax
wls:ClusterLowThroughput("clusterName", "period", "duration", throughputLimit, percentServersLimit)
| Parameter | Description |
|---|---|
clusterName |
Name of target dynamic cluster, expressed as a |
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Retention window during which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
throughputLimit |
Value established as the low threshold value of the |
percentServersLimit |
Percentage of servers in the cluster with an average This parameter is expressed as a |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
clusterName |
myCluster |
period |
30 |
duration |
15 |
throughputLimit |
5 |
percentServersLimit |
75 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ClusterLowThroughput("myCluster","30 seconds","15 minutes",5,75)
If configured with a scale down action, this example smart rule does the following:
Samples the value of the Throughput metric from each Managed Server instance in myCluster every 30 seconds over a retention window of 15 minutes.
At the end of the retention window, fires a scale down action if the following condition evaluates to true:
The average Throughput value, over the last 15 minutes, is less than 5 on at least 75 per cent of the Managed Servers in the cluster.
This rule measures an increase in system load across the cluster, as indicated by the average value of the ProcessCpuLoad attribute in each Managed Server. You can use this rule to determine whether cluster capacity needs to be increased; for example, by executing a scale up action.
Target: Administration Server
Description
This smart rule evaluates to true if the number of Managed Servers with an average ProcessCpuLoad value that satisfies the threshold comparison criteria is greater than or equal to the specified percentage of all servers in the cluster.
To use this smart rule, specify:
The sampling rate and retention window for the operating system's ProcessCpuLoad value
High ProcessCpuLoad threshold value
Percentage of servers in the cluster with an average ProcessCpuLoad value that must be greater than or equal to the high ProcessCpuLoad threshold value in order for the rule to evaluate to true
Note:
The value of the ProcessCpuLoad metric is platform-specific and is not available on all platforms. The MXBean attribute from which this metric originates is described at https://docs.oracle.com/javase/8/docs/jre/api/management/extension/com/sun/management/OperatingSystemMXBean.html#getProcessCpuLoad--.
Syntax
wls:ClusterHighProcessCpuLoadAverage("clusterName", "period", "duration", procCpuLoadLimit, percentServersLimit)
| Parameter | Description |
|---|---|
clusterName |
Name of target dynamic cluster, expressed as a |
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Retention window during which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
procCpuLoadLimit |
Value established as the high threshold value of the |
percentServersLimit |
Percentage of servers in the cluster with an average This parameter is expressed as a |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
clusterName |
myCluster |
period |
30 |
duration |
10 |
procCpuLoadLimit |
0.8 |
percentServersLimit |
60 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ClusterHighProcessCpuLoadAverage("myCluster","30 seconds","10 minutes",0.8,60)
If configured with a scale up action, this smart rule does the following:
Samples the value of the ProcessCpuLoad metric from each Managed Server instance in myCluster every 30 seconds over a retention window of 10 minutes.
At the end of the retention window, fires a scale up action if the following condition evaluates to true:
The average ProcessCpuLoad value, over the last 10 minutes, is greater than or equal to 0.8 on at least 60 per cent of the Managed Servers in the cluster.
This rule measures an increase in system throughput across the cluster, as indicated by the average value of the ThreadPoolRuntimeMBean.Throughput attribute in each Managed Server. You can use this rule to determine whether cluster capacity needs to be increased; for example, by executing a scale up action.
Target: Administration Server
Description
This smart rule evaluates to true if the number of Managed Servers with an average ThreadPoolRuntimeMBean.Throughput value that satisfies the threshold comparison criteria is greater than or equal to the specified percentage of all servers in the cluster.
To use this smart rule, specify:
The sampling rate and retention window of the ThreadPoolRuntimeMBean.Throughput metric
High Throughput threshold value
Percentage of servers in the cluster whose average Throughput value during the sampling period must be greater than or equal to the high Throughput threshold value in order for the rule to evaluate to true
Syntax
wls:ClusterHighThroughput("clusterName", "period", "duration", throughputLimit, percentServersLimit)
| Parameter | Description |
|---|---|
clusterName |
Name of target dynamic cluster, expressed as a |
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
throughputLimit |
Value established as the high threshold value of the |
percentServersLimit |
Percentage of servers in the cluster with an average This parameter is expressed as a |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
clusterName |
myCluster |
period |
30 |
duration |
10 |
throughputLimit |
100 |
percentServersLimit |
60 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ClusterHighThroughput("myCluster","30 seconds","10 minutes",100,60)
When configured with a scale up action, this smart rule does the following:
Samples the value of the Throughput metric from each Managed Server instance in myCluster every 30 seconds over a retention window of 10 minutes.
At the end of the retention window, fires a scale up action if the following condition evaluates to true:
The average Throughput value, over the last 10 minutes, is greater than or equal to 100 on at least 60 per cent of the Managed Servers in the cluster.
This rule measures a reduction in pending requests across the cluster as indicated by the average value of the ThreadPoolRuntimeMBean.PendingUserRequestCount attribute in each Managed Server. You can use this rule to determine whether cluster capacity can be reduced; for example, by executing a scale down action.
Target: Administration Server
Description
This smart rule evaluates to true if the number of Managed Servers with an average ThreadPoolRuntimeMBean.PendingUserRequestCount value that satisfies the threshold comparison criteria is greater than or equal to the specified percentage of all servers in the cluster.
To use this smart rule, specify:
The sampling rate and retention window for the ThreadPoolRuntimeMBean.PendingUserRequestCount metric
Low PendingUserRequestCount threshold value
Percentage of servers in the cluster with an average PendingUserRequestCount value that must be less than the low PendingUserRequestCount threshold value in order for the rule to evaluate to true
Syntax
wls:ClusterLowPendingUserRequests("clusterName", "period", "duration", pendingRequestsLimit, percentServersLimit)
| Parameter | Description |
|---|---|
clusterName |
Name of target dynamic cluster, expressed as a |
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
pendingRequestsLimit |
Value established as the low threshold value of the |
percentServersLimit |
Percentage of servers in the cluster with an average This parameter is expressed as a |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
clusterName |
myCluster |
period |
30 |
duration |
10 |
pendingRequestsLimit |
5 |
percentServersLimit |
75 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ClusterLowPendingUserRequests("myCluster","30 seconds","10 minutes",5,75)
When configured with a scale down action, this smart rule does the following:
Samples the value of the PendingUserRequestCount metric from each Managed Server instance in myCluster every 30 seconds over a retention window of 10 minutes.
At the end of the retention window, fires a scale down action if the following condition evaluates to true:
The average PendingUserRequestCount value, over the last 10 minutes, is less than 5 on at least 75 per cent of the Managed Servers in the cluster.
This rule measures whether the number of stuck threads is rising and may soon become deadlocked, as indicated by the average value of the ThreadPoolRuntimeMBean.StuckThreadCount attribute in each Managed Server. You can use this rule to determine whether cluster capacity needs to be increased; for example, by executing a scale up action.
Target: Administration Server
Description
This smart rule evaluates to true if the number of Managed Servers with an average ThreadPoolRuntimeMBean.StuckThreadCount value that satisfies the threshold comparison criteria is greater than or equal to the specified percentage of all servers in the cluster.
To use this smart rule, specify:
The sampling rate and retention window for the ThreadPoolRuntimeMBean.StuckThreadCount attribute
High StuckThreadCount threshold value
Percentage of servers in the cluster with an average ThreadPoolRuntimeMBean.StuckThreadCount value that must be greater than or equal to the high StuckThreadCount threshold value in order for the rule to evaluate to true
Syntax
wls:ClusterHighStuckThreads("clusterName", "period", "duration", stuckThreadsLimit, percentServersLimit)
| Parameter | Description |
|---|---|
clusterName |
Name of target dynamic cluster, expressed as a |
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
stuckThreadsLimit |
Value established as the high threshold value of the |
percentServersLimit |
Percentage of servers in the cluster with an average This parameter is expressed as a |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
clusterName |
myCluster |
period |
30 |
duration |
10 |
stuckThreadsLimit |
5 |
percentServersLimit |
60 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ClusterHighStuckThreads("myCluster","30 seconds","10 minutes",5,60)
When configured with a scale up action, this smart rule does the following:
Samples the value of the StuckThreadCount metric from each Managed Server instance in myCluster every 30 seconds over a retention window of 10 minutes.
At the end of the retention window, fires a scale up action if the following condition evaluates to true:
The average StuckThreadCount value, over the last 10 minutes, is greater than or equal to 5 on at least 60 per cent of the Managed Servers in the cluster.
This rule measures a decrease in system load across the cluster, as indicated by the average value of the ThreadPoolRuntimeMBean.QueueLength attribute in each Managed Server. You can use this rule to determine whether cluster capacity can be safely reduced; for example, by executing a scale down action.
Target: Administration Server
Description
This smart rule evaluates to true if the number of Managed Servers with an average ThreadPoolRuntimeMBean.QueueLength value that satisfies the threshold comparison criteria is greater than or equal to the specified percentage of all servers in the cluster.
To use this smart rule, specify:
The sampling rate and retention window for the ThreadPoolRuntimeMBean.QueueLength metric
Low QueueLength threshold value
Percentage of servers in the cluster with an average QueueLength value that must be less than the low QueueLength threshold value in order for the rule to evaluate to true
Syntax
wls:ClusterLowQueueLength("clusterName", "period", "duration", queueLengthLimit, percentServersLimit)
| Parameter | Description |
|---|---|
clusterName |
Name of target dynamic cluster, expressed as a |
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
queueLengthLimit |
Value established as the low threshold value of the |
percentServersLimit |
Percentage of servers in the cluster with an average This parameter is expressed as a |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
clusterName |
myCluster |
period |
30 |
duration |
15 |
queueLengthLimit |
5 |
percentServersLimit |
75 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ClusterLowQueueLength("myCluster","30 seconds","15 minutes",5,75)
When configured with a scale down action, this smart rule does the following:
Samples the value of the QueueLength metric from each Managed Server instance in myCluster every 30 seconds over a retention window of 15 minutes.
At the end of the retention window, fires a scale down action if the following condition evaluates to true:
The average QueueLength value, over the last 15 minutes, is less than 5 on at least 75 per cent of the Managed Servers in the cluster.
This rule measures an increase in system load across the cluster, as indicated by the average value of the ThreadPoolRuntimeMBean.PendingUserRequestCount attribute in each Managed Server. You can use this rul to determine whether cluster capacity needs to be increased; for example, by executing a scale up action.
Target: Administration Server
Description
This smart rule evaluates to true if the number of Managed Servers with an average ThreadPoolRuntimeMBean.PendingUserRequestCount value that satisfies the threshold comparison criteria is greater than or equal to the specified percentage of all servers in the cluster.
To use this smart rule, specify:
The sampling rate and retention window for the ThreadPoolRuntimeMBean.PendingUserRequestCount metric
High PendingUserRequestCount threshold value
Percentage of servers in the cluster with an average PendingUserRequestCount value that must be greater than or equal to the high PendingUserRequestCount threshold value in order for the rule to evaluate to true
Syntax
wls:ClusterHighPendingUserRequests("clusterName", "period", "duration", pendingRequestsLimit, percentServersLimit)
| Parameter | Description |
|---|---|
clusterName |
Name of target dynamic cluster, expressed as a |
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
pendingRequestsLimit |
Value established as the high threshold value of the |
percentServersLimit |
Percentage of servers in the cluster with an average This parameter is expressed as a |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
clusterName |
myCluster |
period |
30 |
duration |
10 |
pendingRequestsLimit |
100 |
percentServersLimit |
60 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ClusterHighPendingUserRequests("myCluster","30 seconds","10 minutes",100,60)
When configured with a scale up action, this smart rule does the following:
Samples the value of the PendingUserRequestCount metric from each Managed Server instance in myCluster every 30 seconds over a retention window of 10 minutes.
At the end of the retention window, fires a scale up action if the following condition evaluates to true:
The average PendingUserRequestCount value, over the last 10 minutes, is greater than or equal to 100 on at least 60 per cent of the Managed Servers in the cluster.
This rule measures a reduction of system CPU load across a cluster, as indicated by the average value of the ProcessCpuLoad attribute in each Managed Server. You can use this rule to determine whether cluster capacity needs to be decreased; for example, by executing a scale down action.
Target: Administration Server
Description
This smart rule evaluates to true if the number of Managed Servers with an average ProcessCpuLoad value that satisfies the threshold comparison criteria is greater than or equal to the specified percentage of all servers in the cluster.
Note that the value of ProcessCpuLoad is platform specific and is not available on all platforms.
To use this smart rule, specify:
The sampling rate and retention window for the java.lang:type=OperatingSystem ProcessCpuLoad metric
Low ProcessCpuLoad threshold value
Percentage of servers in the cluster with an average ProcessCpuLoad value that must be less than the low ProcessCpuLoad threshold value in order for the rule to evaluate to true
Note:
The value of the ProcessCpuLoad metric is platform-specific and is not available on all platforms. The MXBean attribute from which this metric originates is described at https://docs.oracle.com/javase/8/docs/jre/api/management/extension/com/sun/management/OperatingSystemMXBean.html#getProcessCpuLoad.
Syntax
wls:ClusterLowProcessCpuLoadAverage("clusterName", "period", "duration", procCpuLoadLimit, percentServersLimit)
| Parameter | Description |
|---|---|
clusterName |
Name of target dynamic cluster, expressed as a |
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
procCpuLoadLimit |
Value established as the low threshold value of the |
percentServersLimit |
Percentage of servers in the cluster with an average This parameter is expressed as a |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
clusterName |
myCluster |
period |
30 |
duration |
15 |
procCpuLoadLimit |
0.2 |
percentServersLimit |
75 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ClusterLowProcessCpuLoadAverage("myCluster","30 seconds","10 minutes",0.2,75)
When configured with a scale down action, this smart rule does the following:
Samples the value of the ProcessCpuLoad metric from each Managed Server instance in myCluster every 30 seconds over a retention window of 15 minutes.
At the end of the retention window, fires a scale down action if the following condition evaluates to true:
The average ProcessCpuLoad value, over the last 15 minutes, is less than 0.2 on at least 75 per cent of the Managed Servers in the cluster.
This rule measures an increase in the number of idle threads in a cluster, as indicated by the average value of the ThreadPoolRuntimeMBean.ExecuteThreadIdleCount attribute in each Managed Server. You can use this rule to determine whether cluster capacity can be safely reduced; for example, by executing a scale down action.
Target: Administration Server
Description
This smart rule evaluates to true if the number of Managed Servers with an average ThreadPoolRuntimeMBean.ExecuteThreadIdleCount value that satisfies the threshold comparison criteria is greater than or equal to the specified percentage of servers in the cluster.
To use this smart rule, specify:
The sampling rate and retention window for the ThreadPoolRuntimeMBean.ExecuteThreadIdleCount metric
High ExecuteThreadIdleCount threshold value
Percentage of Managed Servers in the cluster with an average ExecuteThreadIdleCount value that must be greater than or equal to the high ExecuteThreadIdleCount threshold value in order for the rule to evaluate to true
Syntax
wls:ClusterHighIdleThreads("clusterName", "period", "duration", idleThreadsLimit, percentServersLimit)
| Parameter | Description |
|---|---|
clusterName |
Name of target dynamic cluster, expressed as a |
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
idleThreadsLimit |
Value established as the high threshold value of the |
percentServersLimit |
Percentage of servers in the cluster with an average This parameter is expressed as a |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
clusterName |
myCluster |
period |
30 |
duration |
10 |
idleThreadsLimit |
20 |
percentServersLimit |
75 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ClusterHighIdleThreads("myCluster","30 seconds","10 minutes",20,75)
When configured with a scale down action, this smart rule does the following:
Samples the value of the ExecuteThreadIdleCount metric from each Managed Server instance in myCluster every 30 seconds over a retention window of 10 minutes.
At the end of the retention window, fires a scale down action if the following condition evaluates to true:
The average ExecuteThreadIdleCount value, over the last 10 minutes, is greater than or equal to 20 on at least 75 per cent of the Managed Servers in the cluster.
This rule measures a decrease in system load across a cluster, as indicated by the average value of the SystemLoadAverage attribute in each Managed Server. You can use this rule to determine whether cluster capacity needs to be decreased; for example, by executing a scale down action.
Target: Administration Server
Description
This smart rule evaluates to true if the number of Managed Servers with an average SystemLoadAverage value that satisfies the threshold comparison criteria is equal to or greater than the specified percentage of all servers in the cluster.
Note that the value of SystemLoadAverage is system dependent.
To use this smart rule, specify:
The sampling rate and retention window for the java.lang:type=OperatingSystem SystemLoadAverage metric
Low SystemLoadAverage threshold value
Percentage of Managed Servers in the cluster with an average SystemLoadAverage value that must be less than the low SystemLoadAverage threshold value in order for the rule to evaluate to true
Note:
The value of the SystemLoadAverage metric is platform-specific and is not available on all platforms. The MXBean attribute from which this metric originates is described at http://docs.oracle.com/javase/8/docs/api/java/lang/management/OperatingSystemMXBean.html#getSystemLoadAverage--.
Syntax
wls:ClusterLowSystemLoadAverage("clusterName", "period", "duration", loadLimit, percentServersLimit)
| Parameter | Description |
|---|---|
clusterName |
Name of target dynamic cluster, expressed as a |
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
loadLimit |
Value established as the low threshold value of the |
percentServersLimit |
Percentage of servers in the cluster with an average This parameter is expressed as a |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
clusterName |
myCluster |
period |
30 |
duration |
15 |
loadLimit |
0.2 |
percentServersLimit |
75 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ClusterLowSystemLoadAverage("myCluster","30 seconds","15 minutes",0.2,75)
When configured with a scale down action, this smart rule does the following:
Samples the value of the SystemLoadAverage metric from each Managed Server instance in myCluster every 30 seconds over a retention window of 15 minutes.
At the end of the retention window, fires a scale down action if the following condition evaluates to true:
The average SystemLoadAverage value, over the last 15 minutes, is less than 0.2 on at least 75 per cent of the Managed Servers in the cluster.
This rule measures an increase in system load across the cluster, as indicated by the average value of the ThreadPoolRuntimeMBean.QueueLength attribute in each Managed Server. You can use this rule to determine whether the cluster capacity needs to be increased; for example, by executing a scale up action.
Target: Administration Server
Description
This smart rule evaluates to true if the number of Managed Servers with an average ThreadPoolRuntimeMBean.QueueLength value that satisfies the threshold comparison criteria is greater than or equal to the specified percentage of all servers in the cluster.
To use this smart rule, specify:
The sampling rate and retention window for the ThreadPoolRuntimeMBean.QueueLength metric
High QueueLength threshold value
Percentage of Managed Servers in the cluster with an average QueueLength value that must be greater than or equal to the high QueueLength threshold value in order for the rule to evaluate to true
Syntax
wls:ClusterHighQueueLength("clusterName", "period", "duration", queueLengthLimit, percentServersLimit)
| Parameter | Description |
|---|---|
clusterName |
Name of target dynamic cluster, expressed as a |
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
queueLengthLimit |
Value established as the high threshold value of the |
percentServersLimit |
Percentage of servers in the cluster with an average This parameter is expressed as a |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
clusterName |
myCluster |
period |
30 |
duration |
10 |
queueLengthLimit |
100 |
percentServersLimit |
60 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ClusterHighQueueLength("myCluster","30 seconds","10 minutes",100,60)
When configured with a scale up action, this smart rule does the following:
Samples the value of the QueueLength metric from each Managed Server instance in myCluster every 30 seconds over a retention window of 10 minutes.
At the end of the retention window, fires a scale up action if the following condition evaluates to true:
The average QueueLength value, over the last 10 minutes, is greater than or equal to 100 on at least 60 per cent of the Managed Servers in the cluster.
This rule measures an increase in heap stress across a cluster, as indicated by the average value of the JVMRuntimeMBean.HeapFreePercent attribute in each Managed Server. You can use this rule to determine whether the cluster capacity needs to be increased; for example, by executing a scale up action.
Target: Administration Server
Description
This smart rule evaluates to true if the number of Managed Servers with an average JVMRuntimeMBean.HeapFreePercent value that satisfies the threshold comparison criteria is greater than or equal to a specific percentage of all servers in the cluster.
To use this smart rule, specify:
The sampling rate and retention window for the JVMRuntimeMBean.HeapFreePercent metric
Low HeapFreePercent threshold value
Percentage of Managed Servers in the cluster with an average HeapFreePercent value during the sampling period that must be less than the low HeapFreePercent threshold value in order for the rule to evaluate to true
Syntax
wls:ClusterLowHeapFreePercent("clusterName", "period", "duration", percentFreeLimit, percentServersLimit)
| Parameter | Description |
|---|---|
clusterName |
Name of target dynamic cluster, expressed as a |
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
percentFreeLimit |
Value established as the low threshold value of the |
percentServersLimit |
Percentage of servers in the cluster with an average This parameter is expressed as a |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
clusterName |
myCluster |
period |
30 |
duration |
10 |
percentFreeLimit |
20 |
percentServersLimit |
60 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ClusterLowHeapFreePercent("myCluster","30 seconds","10 minutes",20,60)
When configured with a scale up action, this smart rule does the following:
Samples the value of the HeapFreePercent metric from each Managed Server instance in myCluster every 30 seconds over a retention window of 10 minutes.
At the end of the retention window, fires a scale up action if the following condition evaluates to true:
The average HeapFreePercent value, over the last 10 minutes, is less than 20 on at least 60 per cent of the Managed Servers in the cluster.
This rule measures an increase on system load across a cluster, as indicated by the average value of the SystemLoadAverage attribute in each Managed Server. You can use this rule to determine if cluster capacity needs to be increased; for example, by executing a scale up action.
Target: Administration Server
Description
This smart rule evaluates to true if the number of Managed Servers with an average java.lang:type=OperatingSystem SystemLoadAverage value that satisfies the threshold comparison criteria is greater than or equal to the specified percentage of all servers in the cluster.
Note that the value of the SystemLoadAverage is system dependent.
To use this smart rule, specify:
The sampling rate and retention window for the java.lang:type=OperatingSystem SystemLoadAverage metric
High SystemLoadAverage threshold value
Percentage of Managed Servers in the cluster with an average SystemLoadAverage value that must be greater than or equal to the high SystemLoadAverage threshold value in order for the rule to evaluate to true
Note:
The value of the SystemLoadAverage metric is platform-specific and is not available on all platforms. The MXBean attribute from which this metric originates is described at http://docs.oracle.com/javase/8/docs/api/java/lang/management/OperatingSystemMXBean.html#getSystemLoadAverage--.
Syntax
wls:ClusterHighSystemLoadAverage("clusterName", "period", "duration", loadLimit, percentServersLimit)
| Parameter | Description |
|---|---|
clusterName |
Name of target dynamic cluster, expressed as a |
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
loadLimit |
Value established as the high threshold value of the |
percentServersLimit |
Percentage of servers in the cluster with an average This parameter is expressed as a |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
clusterName |
myCluster |
period |
30 |
duration |
5 |
loadLimit |
0.8 |
percentServersLimit |
60 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ClusterHighSystemLoadAverage("myCluster","30 seconds","5 minutes",0.8,60)
When configured with a scale up action, this smart rule does the following:
Samples the value of the SystemLoadAverage metric from each Managed Server instance in myCluster every 30 seconds over a retention window of 5 minutes.
At the end of the retention window, fires a scale up action if the following condition evaluates to true:
The average SystemLoadAverage value, over the last 5 minutes, is greater than or equal to 0.8 on at least 60 per cent of the Managed Servers in the cluster.
This rule measures a reduction in heap stress across a dynamic cluster, as indicated by the average value of the JVMRuntimeMBean.HeapFreePercent attribute in each Managed Server. You can use this rule to determine if cluster capacity can be reduced; for example, by executing a scale down action.
Target: Administration Server
Description
This smart rule evaluates to true if the number of Managed Servers with an average JVM free heap percentage value that satisfies the threshold comparison criteria is greater than or equal to a specified percentage of all servers in the cluster.
To use this smart rule, specify:
The sampling rate and retention window for the JVM free heap percentage metric
High JVM free heap threshold value
Percentage of Managed Servers in the cluster with an average JVM free heap value that must be greater than or equal to the high JVM free heap threshold value in order for the rule to evaluate to true
Syntax
wls:ClusterHighHeapFreePercent("clusterName", "period", "duration", percentFreeLimit, percentServersLimit)
| Parameter | Description |
|---|---|
clusterName |
Name of target dynamic cluster, expressed as a |
period |
Sampling rate for JVM free heap percentage values, expressed as a
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
percentFreeLimit |
Value established as the high threshold value of the JVM free heap percentage. |
percentServersLimit |
Percentage of servers in the cluster with an average JVM free heap percentage that must be greater than or equal to the This parameter is expressed as a |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
clusterName |
myCluster |
period |
30 |
duration |
5 |
percentFreeLimit |
60 |
percentServersLimit |
75 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ClusterHighHeapFreePercent("myCluster","30 seconds","5 minutes",60,75)
When configured with a scale down action, this smart rule does the following:
Samples the value of the JVM free heap percentage metric from each Managed Server instance in myCluster every 30 seconds over a retention window of 5 minutes.
At the end of the retention window, fires a scale down action if the following condition evaluates to true:
The average JVM free heap percentage value, over the last 5 minutes, is greater than or equal to 60 on at least 75 per cent of the Managed Servers in the cluster.
This rule measures a reduction of the system CPU load average across a cluster, as indicated by the average value of the SystemCpuLoad attribute in each Managed Server. You can use this rule to determine whether cluster capacity needs to be decreased; for example, by executing a scale down action.
Target: Administration Server
Description
This smart rule evaluates to true if the number of Managed Servers with an average java.lang:type=OperatingSystem SystemCpuLoad value satisfies the threshold comparison criteria is greater than or equal to a specified percentage of all servers in the cluster.
Note that the value of the SystemCpuLoad metric is platform-specific and is not available on all platforms.
To use this smart rule, specify:
The sampling rate and retention window for the java.lang:type=OperatingSystem SystemCpuLoad metric
Low SystemCpuLoad threshold value
Percentage of Managed Servers in the cluster with an average SystemCpuLoad value that must be below the low SystemCpuLoad threshold value in order for the rule to evaluate to true
Note:
The value of the SystemCpuLoad metric is platform-specific and is not available on all platforms. The MXBean attribute from which this metric originates is described at https://docs.oracle.com/javase/8/docs/jre/api/management/extension/com/sun/management/OperatingSystemMXBean.html#getSystemCpuLoad--.
Syntax
wls:ClusterLowSystemCpuLoadAverage("clusterName", "period", "duration", systemCpuLoadLimit, percentServersLimit)
| Parameter | Description |
|---|---|
clusterName |
Name of target dynamic cluster, expressed as a |
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
systemCpuLoadLimit |
Value established as the low threshold value of the |
percentServersLimit |
Percentage of servers in the cluster with an average This parameter is expressed as a |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
clusterName |
myCluster |
period |
30 |
duration |
15 |
systemCpuLoadLimit |
0.2 |
percentServersLimit |
75 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ClusterLowSystemCpuLoadAverage("myCluster","30 seconds","15 minutes",0.2,75)
When configured with a scale down action, this smart rule does the following:
Samples the value of the SystemCpuLoad metric from each Managed Server instance in myCluster every 30 seconds over a retention window of 15 minutes.
At the end of the retention window, fires a scale down action if the following condition evaluates to true:
The average SystemCpuLoad value, over the last 15 minutes, is less than 0.2 on at least 75 per cent of the Managed Servers in the cluster.
This rule measures an increase in load stress across the cluster, as indicated by the average value of the ThreadPoolRuntimeMBean.ExecuteThreadIdleCount attribute in each Managed Server. You can use this rule to determine whether cluster capacity needs to be increased; for example, by executing a scale up action.
Target: Administration Server
Description
This smart rule evaluates to true if the number of Managed Servers with an average ThreadPoolRuntimeMBean.ExecuteThreadIdleCount value that satisfies the threshold comparison criteria is greater than or equal to a specified percentage of all servers in the cluster.
To use this smart rule, specify:
The sampling rate and retention window for the ThreadPoolRuntimeMBean.ExecuteThreadIdleCount metric
Low ExecuteThreadIdleCount threshold value
Percentage of Managed Servers in the cluster whose average ExecuteThreadIdleCount value is less than the low ExecuteThreadIdleCount threshold value in order for the rule to evaluate to true
Syntax
wls:ClusterLowIdleThreads("clusterName", "period", "duration", idleThreadsLimit", percentServerLimit")
| Parameter | Description |
|---|---|
clusterName |
Name of target dynamic cluster, expressed as a |
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
idleThreadsLimit |
Value established as the low |
percentServersLimit |
Percentage of servers in the cluster with an average This parameter is expressed as a |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
clusterName |
myCluster |
period |
30 |
duration |
10 |
idleThreadsLimit |
5 |
percentServersLimit |
60 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ClusterLowIdleThreads("myCluster","30 seconds","10 minutes",5,60)
When configured with a scale up action, this example smart rule:
Samples the value of the ExecuteThreadIdleCount metric from each Managed Server instance in myCluster every 30 seconds over a retention window of 10 minutes.
At the end of the retention window, fires a scale up action if the following condition evaluates to true:
The average ExecuteThreadIdleCount value, over the last 10 minutes, is less than 5 on at least 60 per cent of the Managed Servers in the cluster.
This smart rule is typically used to observe trends in JMX metrics that are published through the Server Runtime MBean Server and that are not provided through the other cluster scope smart rules.
Target: Administration Server
Description
This smart rule allows you to view the average value of any metric obtained through JMX within a specific time interval, and compare that average value to a specified threshold value by using a specified comparison operator for each Managed Server in the cluster. If the percentage of servers matching the comparison criteria meets or exceeds the specified limit, the overall condition of the rule is satisfied and this rule returns true.
To use this smart rule, specify:
Dynamic cluster name
A valid JMX ObjectName or ObjectName pattern
An attribute name, or attribute expression (as an EL expression), where the expression is an attribute expression relative to each MBean.
For example, if the MBean is the ServerRuntimeMBean, 'OpenSocketsCurrentCount' obtains the value of the ServerRuntimeMBean.OpenSocketsCurrentCount attribute. In contrast, 'HealthState.State' accesses the State value of the HealthState child object.
A valid boolean comparison operator
A threshold value against which the selected attribute is compared
Percentage of Managed Servers in the cluster whose average attribute value during the sampling period must meet the threshold value in order for the rule to evaluate to true
The sampling rate and retention window for the metric on each Managed Server instance in the cluster
Period of time during which samples are collected
Syntax
wls:ClusterGenericMetricRule("clusterName", "instancePattern", "attribute", "operation", thresholdValue, percentServersLimit, "period", "duration")
| Parameter | Description |
|---|---|
clusterName |
Name of target dynamic cluster, expressed as a |
instancePattern |
A valid JMX |
attribute |
A Java EL expression that retrieves a value on each MBean instance that matches For example, if the MBean is the |
operation |
A boolean comparison operator: |
thresholdValue |
Threshold value against which the value of the |
percentServersLimit |
Percentage of servers in the cluster with an average attribute value that must satisfy the comparison criteria with the value of the This parameter is expressed as a |
period |
Sampling rate for metric values, expressed as a
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
clusterName |
myCluster |
instancePattern |
java.lang:type=OperatingSystem |
attribute |
ProcessCpuLoad |
operation |
>= |
thresholdValue |
0.9 |
percentServersLimit |
75 |
period |
30 |
duration |
10 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ClusterGenericMetricRule("myCluster","java.lang:type=OperatingSystem","ProcessCpuLoad",">=",0.9,75,"30 seconds","10 minutes")
This example smart rule:
Samples the value of the ProcessCpuLoad metric from each Managed Server instance in myCluster every 30 seconds over a retention window of 10 minutes.
At the end of the retention window, this smart rule evaluates to true in the following condition:
The average value of ProcessCpuLoad on the OperatingSystemMXBean, over the last 10 minutes, is greater than or equal to 0.9 on at least 75 per cent of the Managed Servers in the cluster.
This rule measures an increase on system load across the cluster, as indicated by the average value of the operating system SystemCpuLoad attribute in each Managed Server. You use this rule to determine whether cluster capacity needs to be increased; for example, by executing a scale up action.
Target: Administration Server
Description
This smart rule evaluates to true if the number of Managed Servers with an average java.lang:type=OperatingSystem SystemCpuLoad value that satisfies the threshold comparison criteria is greater than or equal to a specified percentage of all servers in the cluster.
Note that the value of SystemCpuLoad is platform-specific and is not available on all platforms.
To use this smart rule, specify:
The sampling rate and retention window for the java.lang:type=OperatingSystem SystemCpuLoad metric
High SystemCpuLoad threshold value
Percentage of Managed Servers in the cluster with an average SystemCpuLoad value that is greater than or equal to the high SystemCpuLoad threshold value in order for the rule to evaluate to true
Note:
The value of the SystemCpuLoad metric is platform-specific and is not available on all platforms. The MXBean attribute from which this metric originates is described at https://docs.oracle.com/javase/8/docs/jre/api/management/extension/com/sun/management/OperatingSystemMXBean.html#getSystemCpuLoad--.
Syntax
wls:ClusterHighSystemCpuLoadAverage("clusterName", "period", "duration", systemCpuLoadLimit, percentServersLimit)
| Parameter | Description |
|---|---|
clusterName |
Name of target dynamic cluster, expressed as a |
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
systemCpuLoadLimit |
Value established as the high threshold value of the |
percentServersLimit |
Percentage of servers in the cluster with an average This parameter is expressed as a |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
clusterName |
myCluster |
period |
30 |
duration |
5 |
systemCpuLoadLimit |
0.8 |
percentServersLimit |
60 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ClusterHighSystemCpuLoadAverage("myCluster","30 seconds","5 minutes",0.8,60)
When configured with a scale up action, this example smart rule:
Samples the value of the SystemCpuLoad metric from each Managed Server instance in myCluster every 30 seconds over a retention window of 5 minutes.
At the end of the retention window, fires a scale up action if the following condition evaluates to true:
The average SystemCpuLoad value, over the last 5 minutes, is greater than or equal to 0.8 on at least 60 per cent of the Managed Servers in the cluster.
Server scope smart rules, listed and summarized in Table A-2, are rules that are applied only to the local WebLogic Server instance on which the associated policies are run. You can execute policies containing server scope smart rules on the Administration Server or any individual Managed Server in the domain.
Table A-2 Summary of Managed Server Scope Smart Rules
| After the retention window, the following smart rule . . . | . . . returns true if . . . |
|---|---|
|
The average |
|
|
The average |
|
|
The average value of a metric visible through JMX within the local JVM satisfies the comparison criteria with the threshold value. |
|
|
The average |
|
|
The average value of the |
|
|
The average value of the |
|
|
The average |
|
|
The average |
|
|
The average |
|
|
The average |
|
|
The average |
|
|
The average |
|
|
The average percentage of free heap on the local server is greater than or equal to the high threshold value. |
|
|
The average |
|
|
The average |
|
|
The average |
|
|
The average percentage of free heap on the local server is less than the low threshold value. |
|
|
The average |
This smart rule detects if the average number of idle threads is below the specified threshold within the local server in which the rule is running, as indicated by the average value of the ThreadPoolRuntimeMBean.ExecuteThreadIdleCount attribute.
You can target this smart rule on either a Managed Server or an Administration Server.
Group: Server
Description
This smart rule returns true if the average value of the ThreadPoolRuntimeMBean.ExecuteThreadIdleCount attribute is equal to or less than the specified threshold value.
To use this smart rule, specify:
The sampling rate and retention window for the ThreadPoolRuntimeMBean.ExecuteThreadIdleCount metric
Low ExecuteThreadIdleCount threshold value
Syntax
wls:ServerLowIdleThreads("period", "duration", idleThreadsLimit)
| Parameter | Description |
|---|---|
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
idleThreadsLimit |
Value established as the low threshold value of the |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
period |
30 |
duration |
5 |
idleThreadsLimit |
0.8 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ServerLowIdleThreads("30 seconds","10 minutes",5)
This example smart rule:
Samples the value of the ExecuteThreadIdleCount metric from the local server instance every 30 seconds over a retention window of 5 minutes.
At the end of the retention window, fires the associated action if the following condition evaluates to true:
The average ExecuteThreadIdleCount value, over the last 5 minutes, is less than or equal to 0.8 on this server instance.
This smart rule determines whether an increase in throughput exists within the local server in which the rule is running.
You can target this smart rule on either a Managed Server or an Administration Server.
Group: Server
Description
This smart rule returns true if the average value of the ThreadPoolRuntimeMBean.Throughput attribute over the specified retention window is greater than or equal to the high threshold value.
To use this smart rule, specify:
The sampling rate and retention window of the ThreadPoolRuntimeMBean.Throughput attribute.
High Throughput threshold value
Syntax
wls:ServerHighThroughput("period", "duration", throughputLimit)
| Parameter | Description |
|---|---|
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
throughputLimit |
Value established as the high threshold value of the |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
period |
30 |
duration |
10 |
throughputLimit |
100 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ServerHighThroughput("30 seconds","10 minutes",100)
This example smart rule:
Samples the value of the Throughput metric from the local server instance every 30 seconds over a retention window of 10 minutes.
At the end of the retention window, fires the associated action if the following condition evaluates to true:
The average Throughput value, over the last 10 minutes, is greater than or equal to 100 on this server instance.
This is a general server scope smart rule you can use to observe trends of any JMX metric that is published through the Server Runtime MBean Server and that is not provided by the other server scope smart rules. This smart rule allows you to collect the average value of the metric across a recent time interval and compare it to a threshold value using a specified comparison operator.
You can target this smart rule on either a Managed Server or an Administration Server.
Group: Server
Description
This smart rule returns true if the average value of the metric meets or exceeds the specified threshold value.
To use this smart rule, specify:
A valid JMX ObjectName or ObjectName pattern
A Java EL expression that retrieves a value on each matching MBean instance, where the expression is an attribute expression relative to each MBean.
A boolean comparison operator using the specified comparison operator
A threshold value against which the selected attribute is compared
The sampling rate and retention window of the metric.
Syntax
wls:ServerGenericMetricRule("instancePattern", "attribute", "operation", thresholdValue, "period", "duration")
| Parameter | Description |
|---|---|
instancePattern |
A valid JMX |
attribute |
A Java EL expression that retrieves a value on each MBean instance that matches For example, if the MBean is the |
operation |
A boolean comparison operator: |
thresholdValue |
A threshold value with which to compare the selected attribute using the specified comparison operator. |
period |
Sampling rate for metric values, expressed as a
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
instancePattern |
java.lang:type=OperatingSystem |
attribute |
ProcessCpuLoad |
operation |
>= |
thresholdValue |
0.9 |
period |
30 |
duration |
10 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ServerGenericMetricRule("java.lang:type=OperatingSystem","ProcessCpuLoad",">=",0.9,"30 seconds","10 minutes")
The smart rule:
Samples the value of the ProcessCpuLoad metric on the targeted server instance every 30 seconds over a retention window of 10 minutes.
At the end of the retention window, this smart rule evaluates to true in the following condition:
The average value of ProcessCpuLoad on the OperatingSystemMXBean, over the last 10 minutes, is greater than or equal to 0.9 on this server instance.
This smart rule determines whether the average number of pending user requests within the local server in which the rule is running, as indicated by the value of the ThreadPoolRuntimeMBean.PendingUserRequestCount attribute.
You can target this smart rule on either a Managed Server or an Administration Server.
Group: Server
Description
This smart rule returns true if the average value of the ThreadPoolRuntimeMBean.PendingUserRequestCount attribute over the specified retention window is less than the low threshold value.
To use this smart rule, specify:
The sampling rate and retention window of the ThreadPoolRuntimeMBean.PendingUserRequestCount attribute.
Low PendingUserRequestCount threshold value
Syntax
wls:ServerLowPendingUserRequests("period", "duration", pendingRequestsLimit)
| Parameter | Description |
|---|---|
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
pendingRequestsLimit |
Value established as the low threshold value of the |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
period |
30 |
duration |
15 |
pendingRequestsLimit |
5 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ServerLowPendingUserRequests("30 seconds","15 minutes",5)
This example smart rule:
Samples the value of the PendingUserRequestCount metric from the local server instance every 30 seconds over a retention window of 15 minutes.
At the end of the retention window, evaluates to true if the following condition exists:
The average PendingUserRequestCount value, over the last 15 minutes, is less than 5 on this server instance.
This smart rule determines whether a reduction exists in the average system load within the local server instance in which the rule is running.
You can target this smart rule on either a Managed Server or an Administration Server.
Group: Server
Description
This rule returns true if the average value of the ProcessCpuLoad metric of the java.lang:type=OperatingSystem MXBean over the specified time interval is less than a specified threshold value.
Note:
The value of the ProcessCpuLoad metric is platform-specific and is not available on all platforms. The MXBean attribute from which this metric originates is described at https://docs.oracle.com/javase/8/docs/jre/api/management/extension/com/sun/management/OperatingSystemMXBean.html#getProcessCpuLoad--.
To use this smart rule, specify:
The sampling rate and retention window of the ProcessCpuLoad attribute.
Low ProcessCpuLoad threshold value
Syntax
wls:ServerLowProcessCpuLoadAverage("period", "duration", processCpuLoadLimit)
| Parameter | Description |
|---|---|
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
processCpuLoadLimit |
Value established as the low threshold value of the |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
period |
30 |
duration |
15 |
processCpuLoadLimit |
0.2 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ServerLowProcessCpuLoadAverage("30 seconds","15 minutes",0.2)
This example smart rule:
Samples the value of the ProcessCpuLoad metric from the local server instance every 30 seconds over a retention window of 15 minutes.
At the end of the retention window, fires the associated action if the following condition evaluates to true:
The average ProcessCpuLoad value, over the last 15 minutes, is less than 0.2 on this server instance.
This smart rule determines whether a reduction exists on the average system load within the local server in which the rule is running.
You can target this smart rule on either a Managed Server or an Administration Server.
Group: Server
Description
This rule returns true if the average value of the SystemLoadAverage metric from the java.lang:type=OperatingSystem MXBean on the local server instance over specified interval is greater than or equal to a specific high threshold value.
To use this smart rule, specify:
The sampling rate and retention window of the SystemLoadAverage attribute.
High SystemLoadAverage threshold value
Note:
The value of the SystemLoadAverage metric is platform-specific and is not available on all platforms. The MXBean attribute from which this metric originates is described at http://docs.oracle.com/javase/8/docs/api/java/lang/management/OperatingSystemMXBean.html#getSystemLoadAverage--.
Syntax
wls:ServerHighSystemLoadAverage("period", "duration", loadLimit)
| Parameter | Description |
|---|---|
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
loadLimit |
Value established as the high threshold value of the |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
period |
30 |
duration |
5 |
loadLimit |
0.8 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ServerHighSystemLoadAverage("30 seconds","5 minutes",0.8)
This example smart rule:
Samples the value of the SystemLoadAverage metric on the local server instance every 30 seconds over a retention window of 5 minutes.
At the end of the retention window, fires the associated action if the following condition evaluates to true:
The average SystemLoadAverage value, over the last 5 minutes, is greater than or equal to 0.8 collected on this server instance.
This smart rule determines whether a reduction exists in the average thread pool queue length within the local server in which the rule is running, as indicated by the value of the ThreadPoolRuntimeMBean.QueueLength metric.
You can target this smart rule on either a Managed Server or an Administration Server.
Group: Server
Description
This rule returns true if the average value of the ThreadPoolRuntimeMBean.QueueLength attribute on the local server instance over specified interval is less than a specific low threshold value.
To use this smart rule, specify:
The sampling rate and retention window of the ThreadPoolRuntimeMBean.QueueLength attribute.
Low QueueLength threshold value
Syntax
wls:ServerLowQueueLength("period", "duration", queueLengthLimit)
| Parameter | Description |
|---|---|
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
queueLengthLimit |
Value established as the low threshold value of the |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
period |
30 |
duration |
15 |
queueLengthLimit |
5 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ServerLowQueueLength("30 seconds","15 minutes",5)
This example smart rule:
Samples the value of the QueueLength metric from the local server instance every 30 seconds over a retention window of 15 minutes.
At the end of the retention window, fires the associated action if the following condition evaluates to true:
The average QueueLength value, over the last 15 minutes, is less than 5 on this server instance.
This smart rule determines whether a decrease exists in the average throughput within the local server in which the rule is running.
You can target this smart rule on either a Managed Server or an Administration Server.
Group: Server
Description
This rule returns true if the average value of the ThreadPoolRuntimeMBean.Throughput attribute on the local server over the specified interval is less than the specified low threshold value.
To use this smart rule, specify:
The sampling rate and retention window of the ThreadPoolRuntimeMBean.Throughput attribute.
Low Throughput threshold value
Syntax
wls:ServerLowThroughput("period", "duration", throughputLimit)
| Parameter | Description |
|---|---|
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
throughputLimit |
Value established as the low threshold value of the |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
period |
30 |
duration |
15 |
idleThreadsLimit |
5 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ServerLowThroughput("30 seconds","15 minutes",5)
This example smart rule:
Samples the value of the Throughput metric from the local server instance every 30 seconds over a retention window of 15 minutes.
At the end of the retention window, fires the associated action if the following condition evaluates to true:
The average Throughput value, over the last 15 minutes, is less than 5 on this server instance.
This smart rule determines whether an increase exists in the average thread pool queue length within the local server in which the rule is running, as indicated by the value of the ThreadPoolRuntimeMBean.QueueLength attribute.
You can target this smart rule on either a Managed Server or an Administration Server.
Group: Server
Description
This rule returns true if the average value of the ThreadPoolRuntimeMBean.QueueLength attribute over a specific time interval is greater than or equal to a specific high threshold value.
To use this smart rule, specify:
The sampling rate and retention window of the ThreadPoolRuntimeMBean.QueueLength attribute.
High QueueLength threshold value
Syntax
wls:ServerHighQueueLength("period", "duration", queueLengthLimit)
| Parameter | Description |
|---|---|
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
queueLengthLimit |
Value established as the high threshold value of the |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
period |
30 |
duration |
10 |
queueLengthLimit |
100 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ServerHighQueueLength("30 seconds","10 minutes",100)
This example smart rule:
Samples the value of the QueueLength metric from the local server instance every 30 seconds over a retention window of 10 minutes.
At the end of the retention window, fires the associated action if the following condition evaluates to true:
The average QueueLength value, over the last 10 minutes, is greater than or equal to 100 on this server instance.
This smart rule determines whether an increase exists in the average system CPU load within the local server in which the rule is running.
You can target this smart rule on either a Managed Server or an Administration Server.
Group: Server
Description
This rule returns true if the average value of the SystemCpuLoad attribute of the java.lang:type=OperatingSystem MXBean over a specific time interval is greater than or equal to a specific high threshold.
Note:
The value of the SystemCpuLoad metric is platform-specific and is not available on all platforms. The MXBean attribute from which this metric originates is described at https://docs.oracle.com/javase/8/docs/jre/api/management/extension/com/sun/management/OperatingSystemMXBean.html#getSystemCpuLoad--.
To use this smart rule, specify:
The sampling rate and retention window of the SystemCpuLoad attribute.
High SystemCpuLoad threshold value
Syntax
wls:ServerHighSystemCpuLoadAverage("period", "duration", systemCpuLoadLimit)
| Parameter | Description |
|---|---|
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
systemCpuLoadLimit |
Value established as the high threshold value of the |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
period |
30 |
duration |
10 |
systemCpuLoadLimit |
0.8 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ServerHighSystemCpuLoadAverage("30 seconds","10 minutes",0.8)
This example smart rule:
Samples the value of the SystemCpuLoad metric from the local server instance every 30 seconds over a retention window of 10 minutes.
At the end of the retention window, fires the associated action if the following condition evaluates to true:
The average SystemCpuLoad value, over the last 10 minutes, is greater than or equal to 0.8 on this server instance.
This smart rule determines whether an increase exists in the number of pending user requests within the local server in which the rule is running, as indicated by the value of the ThreadPoolRuntimeMBean.PendingUserRequestCount attribute.
You can target this smart rule on either a Managed Server or an Administration Server.
Group: Server
Description
This rule returns true if the average value of the ThreadPoolRuntimeMBean.PendingUserRequestCount attribute over a specific interval is greater than or equal to a specific threshold value.
To use this smart rule, specify:
The sampling rate and retention window of the ThreadPoolRuntimeMBean.PendingUserRequestCount attribute.
High PendingUserRequestCount threshold value
Syntax
wls:ServerHighPendingUserRequests("period", "duration", pendingRequestsLimit)
| Parameter | Description |
|---|---|
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
pendingRequestsLimit |
Value established as the high threshold value of the |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
period |
30 |
duration |
10 |
pendingRequestsLimit |
100 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ServerHighPendingUserRequests("30 seconds","10 minutes",100)
This example smart rule:
Samples the value of the PendingUserRequestCount metric from the local server instance every 30 seconds over a retention window of 10 minutes.
At the end of the retention window, fires the associated action if the following condition evaluates to true:
The average PendingUserRequestCount value, over the last 10 minutes, is greater than or equal to 100 on this server instance.
This smart rule determines whether a reduction exists in the average system CPU load within the local server in which the rule is running.
You can target this smart rule on either a Managed Server or an Administration Server.
Group: Server
Description
This rule returns true if the average value of the SystemCpuLoad metric of the java.lang:type=OperatingSystem MXBean over a specific interval is less than the specified low threshold value.
Note:
The value of the SystemCpuLoad metric is platform-specific and is not available on all platforms. The MXBean attribute from which this metric originates is described at https://docs.oracle.com/javase/8/docs/jre/api/management/extension/com/sun/management/OperatingSystemMXBean.html#getSystemCpuLoad--.
To use this smart rule, specify:
The sampling rate and retention window of the SystemCpuLoad attribute.
Low SystemCpuLoad threshold value
Syntax
wls:ServerLowSystemCpuLoadAverage("period", "duration", systemCpuLoadLimit)
| Parameter | Description |
|---|---|
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
systemCpuLoadLimit |
Value established as the low threshold value of the |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
period |
30 |
duration |
15 |
systemCpuLoadLimit |
0.8 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ServerLowSystemCpuLoadAverage("30 seconds","15 minutes",0.8)
This example smart rule:
Samples the value of the SystemCpuLoad metric from the local server instance every 30 seconds over a retention window of 15 minutes.
At the end of the retention window, fires the associated action if the following condition evaluates to true:
The average SystemCpuLoad value, over the last 15 minutes, is less than 0.8 on this server instance.
This smart rule determines whether an increase in heap stress exists within the local server in which the rule is running.
You can target this smart rule on either a Managed Server or an Administration Server.
Group: Server
Description
This rule returns true if the average JVMRuntimeMBean.HeapFreePercent value over the specific time interval is greater than or equal to the specified high threshold value.
To use this smart rule, specify:
The sampling rate and retention window of the JVMRuntimeMBean.HeapFreePercent attribute.
High JVM free heap percentage threshold value
Syntax
wls:ServerHighHeapFreePercent("period", "duration", percentFreeLimit)
| Parameter | Description |
|---|---|
period |
Sampling rate for JVM free heap percentage values, expressed as a
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
percentFreeLimit |
Value established as the high threshold of the JVM free heap percentage, specified as a |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
period |
30 |
duration |
10 |
percentFreeLimit |
60 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ServerHighHeapFreePercent("30 seconds","10 minutes",60)
This example smart rule:
Samples the value of the JVM free heap percentage from the local server instance every 30 seconds over a retention window of 10 minutes.
At the end of the retention window, fires the associated action if the following condition evaluates to true:
The average JVM free heap value, over the last 10 minutes, is greater than or equal to 60 per cent on this server instance.
This smart rule determines whether an increase exists on server stress based on the average number of stuck threads within the local server in which the rule is running, as indicated by the value of the ThreadPoolRuntimeMBean.StuckThreadCount attribute.
You can target this smart rule on either a Managed Server or an Administration Server.
Group: Server
Description
This rule returns true if the average value of the ThreadPoolRuntimeMBean.StuckThreadCount attribute over a specific time interval is greater than or equal to the specified threshold value.
To use this smart rule, specify:
The sampling rate and retention window of the ThreadPoolRuntimeMBean.StuckThreadCount attribute.
High StuckThreadCount threshold value
Syntax
wls:ServerHighStuckThreads("period", "duration", stuckThreadsLimit)
| Parameter | Description |
|---|---|
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
stuckThreadsLimit |
Value established as the high threshold value of the |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
period |
30 |
duration |
10 |
stuckThreadsLimit |
5 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ServerHighStuckThreads("30 seconds","10 minutes",5)
This example smart rule:
Samples the value of the StuckThreadCount metric from the local server instance every 30 seconds over a retention window of 10 minutes.
At the end of the retention window, fires the associated action if the following condition evaluates to true:
The average StuckThreadCount value, over the last 10 minutes, is greater than or equal to 5 on this server instance.
This smart rule determines whether an decrease exists in the average system load within the local server in which the rule is running.
You can target this smart rule on either a Managed Server or an Administration Server.
Group: Server
Description
This rule returns true if the average ProcessCpuLoad value of the java.lang:type=OperatingSystem MXBean over the specified interval is greater than or equal to the specified threshold.
Note:
The value of the ProcessCpuLoad metric is platform-specific and is not available on all platforms. The MXBean attribute from which this metric originates is described at https://docs.oracle.com/javase/8/docs/jre/api/management/extension/com/sun/management/OperatingSystemMXBean.html#getProcessCpuLoad--.
To use this smart rule, specify:
The sampling rate and retention window of the ProcessCpuLoad attribute.
High ProcessCpuLoad threshold value
Syntax
wls:ServerHighProcessCpuLoadAverage("period", "duration", processCpuLoadLimit)
| Parameter | Description |
|---|---|
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
processCpuLoadLimit |
Value established as the high threshold value of the |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
period |
30 |
duration |
5 |
processCpuLoadLimit |
0.8 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ServerHighProcessCpuLoadAverage("30 seconds","5 minutes",0.8)
This example smart rule:
Samples the value of the ProcessCpuLoad metric from the local server instance every 30 seconds over a retention window of 5 minutes.
At the end of the retention window, fires the associated action if the following condition evaluates to true:
The average ProcessCpuLoad value, over the last 5 minutes, is greater than or equal to 0.8 on this server instance.
This smart rule determines whether a reduction exists in the average system load within the local server in which the rule is running.
You can target this smart rule on either a Managed Server or an Administration Server.
Group: Server
Description
This rule returns true if the value of the SystemLoadAverage metric of the java.lang:type=OperatingSystem MXBean over a specified interval is less than the specified low threshold value.
Note:
The value of the SystemLoadAverage metric is platform-specific and is not available on all platforms. The MXBean attribute from which this metric originates is described at http://docs.oracle.com/javase/8/docs/api/java/lang/management/OperatingSystemMXBean.html#getSystemLoadAverage--.
To use this smart rule, specify:
The sampling rate and retention window of the SystemLoadAverage attribute.
Low SystemLoadAverage threshold value
Syntax
wls:ServerLowSystemLoadAverage("period", "duration", loadLimit)
| Parameter | Description |
|---|---|
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
loadLimit |
Value established as the low threshold value of the |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
period |
30 |
duration |
15 |
loadLimit |
0.2 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ServerLowSystemLoadAverage("30 seconds","15 minutes",0.2)
This example smart rule:
Samples the value of the SystemLoadAverage metric from the local server instance every 30 seconds over a retention window of 15 minutes.
At the end of the retention window, fires the associated action if the following condition evaluates to true:
The average SystemLoadAverage value, over the last 15 minutes, is less than 0.2 on this server instance.
This smart rule determines whether an increase exists in heap stress within the local server in which the rule is running.
You can target this smart rule on either a Managed Server or an Administration Server.
Group: Server
Description
This rule returns true if the average JVMRuntimeMBean.HeapFreePercent value over the specified time interval is less than the specified low threshold value.
To use this smart rule, specify:
The sampling rate and retention window of the JVMRuntimeMBean.HeapFreePercent attribute.
Low Java free heap percentage threshold value
Syntax
wls:ServerLowHeapFreePercent("period", "duration", percentFreeLimit)
| Parameter | Description |
|---|---|
period |
Sampling rate for Java free heap percentage values, expressed as a
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
percentFreeLimit |
Value established as the low threshold value of the Java free heap percentage. |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
period |
30 |
duration |
5 |
percentFreeLimit |
20 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ServerLowHeapFreePercent("30 seconds","5 minutes",20)
This example smart rule:
Samples the value of the Java free heap percentage from the local server instance every 30 seconds over a retention window of 5 minutes.
At the end of the retention window, fires the associated action if the following condition evaluates to true:
The average Java free heap percentage value, over the last 5 minutes, is less than 20 per cent on this server instance.
This smart rule determines whether a reduction in average system load exists within the local server in which the rule is running, by measuring an increase in idle threads as indicated by the ThreadPoolRuntimeMBean.ExecuteThreadIdleCount attribute.
You can target this smart rule on either a Managed Server or an Administration Server.
Group: Server
Description
This rule returns true if the average value of the ThreadPoolRuntimeMBean.ExecuteThreadIdleCount attribute over the specified retention window is greater than or equal to the specified threshold value.
To use this smart rule, specify:
The sampling rate and retention window of the ThreadPoolRuntimeMBean.ExecuteThreadIdleCount attribute.
High ExecuteThreadIdleCount threshold value
Syntax
wls:ServerHighIdleThreads("period", "duration", idleThreadsLimit)
| Parameter | Description |
|---|---|
period |
Sampling rate for
See sampling rate for more information about specifying this parameter. |
duration |
Period of time for which collected samples are retained, expressed as a
See retention window for more information about specifying this parameter. |
idleThreadsLimit |
Value established as the high threshold value of the |
Example
The smart rule shown in this example uses the following input parameters:
| Parameter | Value |
|---|---|
period |
30 |
duration |
10 |
idleThreadsLimit |
20 |
The smart rule that uses the preceding parameters is expressed as follows:
wls:ServerHighIdleThreads("30 seconds","10 minutes",20)
This example smart rule:
Samples the value of the ExecuteThreadIdleCount metric from the local server instance every 30 seconds over a retention window of 10 minutes.
At the end of the retention window, fires the associated action if the following condition evaluates to true:
The average ExecuteThreadIdleCount value, over the last 10 minutes, is greater than or equal to 20 on this server instance.