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ITCAM for WebSphere Application Server and J2EE V6.1 Data Collector Performance Tuning Guide
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Home > Performance and Tuning > ITCAM for WebSphere Application Server and J2EE V6.1 Data Collector Performance Tuning Guide

ITCAM for WebSphere Application Server and J2EE V6.1 Data Collector Performance Tuning Guide

This topic includes performance tuning information about IBM® Tivoli® Composite Application Manager (ITCAM) for WebSphere® Application Server J2EE V6.1.

Introduction

IBM Tivoli Composite Application Manager (ITCAM) is a family of products allowing a user to monitor J2EE applications running on WebSphere (ITCAM for WebSphere version 6.1) as well as other J2EE application servers, such as WebLogic, JBOSS, Oracle, and so on (ITCAM for J2EE version 6.1). These products provide a customer with capability to monitor mission critical J2EE applications as well as to conduct deep-dive diagnostics of issues found through monitoring.

The Data Collector (DC) monitoring component of ITCAM products is responsible for collecting all transaction and request metrics, Java Virtual Machine metrics, WebSphere PMI metrics and other type of information such as thread and heap dumps. DC consists of platform-independent JAR files and platform-dependent native libraries and it runs within the targeted (monitored) J2EE application server process (java) to collect the metrics. DC sends data to ITCAM Management Server components for data rendering in ITCAM Web Console (or Visualization Engine) and data persistent in Management Server database. Since DC runs within the monitored J2EE application server process, it incurs a certain level of performance overhead to the application server depending on degree of monitoring level and other DC configuration settings.

ITCAM DC offers three monitoring levels for runtime transactions and requests: Monitor on Demand (MOD) level-1, level-2 and level-3. These MOD levels can be dynamically changed using the ITCAM Management Server console in order to give a user flexibility to choose the best suitable balance between level of data volume, depth, and granularity compared with the DC monitoring overhead incurring to provide the data under a particular condition and a user's purpose. ITCAM Management Server also provides a mechanism to control the MOD level automatically based on a user-defined schedule. The detailed descriptions and configurations of the MOD levels and their scheduling mechanism can be found in ITCAM for WebSphere Application Server V6.1 User's Guide.

General recommendation for MOD level-1, level-2, and level-3, and their use cases are documented in the User's Guide, which you can use as a guideline.

These flexible features of the MOD level management allow a user to monitor the production J2EE applications for 24 x 7 continuously with the appropriate level of depth associated with reasonable overhead that is best suited to the user's goal. In addition to these MOD level management, ITCAM DC provides some finetuning to further customize DC's CPU, memory, and throughput behavior. ITCAM DC is configured for best balance between performance and data collection level. However, under a particular user scenario, a user may like to finetune the behavior of DC to optimize the performance and data collection level for a particular purpose. The purpose of this document is to describe these finetune options of ITCAM DC to customize DC behavior in terms of CPU, memory consumption, and data collection capability.

Note that there is no magic to reduce performance in a nearly optimized environment. In most cases, a user must accept the trade-off between performance overhead and the level of monitoring. However, the optimal combination of the trade-off can vary from one user to another. This document addresses the trade-off and presents how a user can finetune ITCAM DC for their environment.

The following table summarizes DC Tuning options discussed in this document, their scope of expected improvements, WebSphere Application Server/J2EE applicability, out of the box default setting, brief description of prescription and potential costs of tuning. A user may refer to Appendix for high level descriptions of ITCAM for WebSphere Application Server/J2EE V6.1 features involved in the tuning options.

Table 1: Tuning Option Summary

Tuning Option Fine Grained PMI Counter DC Internal Buffer tuning MOD L2 instrumentation fine tuning MOD L2 Method Profiling
Scope MOD L1/L2/L3 CPU and throughput overhead Typically L3 throughput and L2 under high volume transactions MOD L1/L2 CPU and throughput
Startup time overhead
MOD L3
Expected tuning impacts Up to 4-5% if disable all PMI;
Bean counter may have 2-3% overhead alone If application uses many EJBs.
Reduce possibility of L2/L3 throughput slowdown due to DC Turbo Mode engagement Up to 1-3% for most of cases. For application with heavy nested requests this might have larger impact. It's possible to achieve any desired level of performance (up to L2 overhead), with corresponding L3 BCI customization.
Applicability to ITCAM WebSphere Application Server/J2EE WebSphere Application Server WebSphere Application Server/J2EE WebSphere Application Server/J2EE (finer tuning for J2) WebSphere Application Server/J2EE
Out of the box default On DC internal buffer size = 100MB All L2 instrumentation On Off
Brief description of prescription Fine tune to disable unnecessary PMI counters Increasing i_nternal.memory.limit_ value to reduce probability of DC turbo engagement Disable unnecessary L2 instrumentation points Use MOD L2 Method Profiling instead of MOD L3 when Method Profiling is sufficient.
Cost of tuning less PMI data Possible larger memory overhead under L2/L3 high volume transactions Less L2 sub-transaction data Method Profiling provides aggregate data vs L3 provides instance data

Table 2: Tuning Option Summary (continued)

Tuning Option MOD L3 custom method filtering GPE Turbo Disable DC
Scope MOD L3 CPU and throughput overhead
Startup time overhead
MOD L1/L2 CPU and throughput overhead Overall DC overhead
Expected tuning impacts It's possible to achieve any desired level of performance (up to L2 overhead), with corresponding L3 BCI customization. N/A (default is the best) Absolutely minimum DC overhead
Applicability to ITCAM WebSphere Application Server/J2EE WebSphere Application Server/J2EE WebSphere Application Server/J2EE WebSphere Application Server/J2EE
Out of the box default No custom exclusions On DC enabled
Brief description of prescription Fine tune BCI to filter out unnecessary/trivial L3 method instrumentation points Keep default ADMINISTRATION --> SERVER MANAGEMENT --> DATA COLLECTOR CONFIGURATION and select "Disable" button
 
Cost of tuning less method data None No DC functions but ability to enable DC on-line

The rest of the document is organized as follows: First an overall DC tuning approach is described in a step-by-step fashion. Next, each tuning option is described in detail - parameters to be changed, expected performance impact, locations and default values of the parameters and step-by-step tuning instruction. Then,
several ITCAM for WebSphere Application Server J2EE DC overhead best practices are described.

Step-By-Step DC Tuning Approach

ITCAM for WebSphere Application Server/J2EE DC includes a set of tuning parameters with default values, which may or may not be suitable to a particular user environment and use scenarios. Conduct the following step-by-step overall DC tuning. Further information for each tuning option can be found in theITCAM Data Collector Tuning Options section.

STEP 1 (apply to WebSphere Application Server only): Disable unnecessary PMI counters (See Section 4.1. for detail)

  1. A user must identify which PMI counters are necessary for MOD level-1 monitoring and which counters can be dropped from default PMI configuration (For WebSphere Application Server V6 default is BASIC PMI counter set. For WebSphere Application Server V5.1 default is described in datacollector.properties WebSphere Application Server PMI Section). Appendix-B lists all PMI counters available for WebSphere Application Server V6 and WebSphere Application Server V5 and their monitoring levels, by which you can map to Data Collector MOD level that uses the counters.
  2. Disable the unnecessary PMI counters as described in Section 3.1 Fine Grained PMI Counter Option.

STEP 2: DC Internal Buffer Tuning (See Section 4.2. for detail)

  1. Determine if there are frequent DC turbo mode engagements logged in trace-dc.log. Frequent DC Turbo engagement may not be desirable as it can slow down response times under L3 and high volume L2 monitoring conditions. Appendix-A of this document contains more detail on DC Turbo behavior.
  2. If it is acceptable to have larger DC memory footprint under L3 and high volume L2 monitoring conditions, increase internal.memory.limit value from 100 to 200 or more to reduce a chance of DC Turbo Mode engagement.
  3. Another consideration to minimize a chance of DC Turbo engagement is to upgrade ITCAM Management Server capacity, especially for PS components. Typically DC event flow to MS is limited by the PS processing capacity. You can increase the PS processing capacity by (1) having additional PS process(es) (i.e. less number of DCs that contend against each other per PS) and/or (2) upgrading the CPUs of the machine that the PS processes are running on by increasing the number of CPUs or replacing them with faster CPUs.

STEP 3: Apply MOD level-2 Instrumentation Fine Tuning (See Section 4.3. for detail)

  1. Determine if it is acceptable for a user to disabled a subset of instrumentation for MOD L2 nested requests. This can be done per J2EE container level for WebSphere. For J2 platform per EJB method level controls are also available. An example is shown in Section 3.3. MOD L3 Instrumentation Tuning Option of this document.
  2. If it is acceptable, disable selected MOD L2 instrumentation as described in Section 3.3 MOD level-2 Instrumentation Tuning Option of this document.

STEP 4: Use MOD L2 Method Profiling (See Section 4.4. for detail)

  1. Configure MOD L2 Method Profiling. This consist of (1) configure L3 BCI by uncommenting am.camtoolkit.gpe.customxml.L3 in toolkit_custom.properties (2) uncomment and set com.ibm.tivoli.itcam.toolkit.ai.methodentryexittrace **property to true (3) Configuring DC from Web Console to MOD L2 and check the Method Profiling check box.
  2. Increase value of am.mp.leagueTableSize in datacollector.properties to have large enough table entries so that Method Profiling table can contain all methods captured. A user may need to experiment with this value to find out what is the sufficient size of the table.
  3. Examine the output of Method Profiling. If a user finds many trivial or uninterested method entries, disable L3 instrumentation points for those methods as described in Section 3.5 MOD L3 Method Filtering Option of this document.
  4. Use MOD L2 Method Profiling instead of MOD L3 - this will reduce DC data volume dramatically but in many cases providing more useful information to analyze transaction performance than MOD L3.

STEP 5: Apply MOD L3 Method Filtering Option (See Section 4.5. for detail)

  1. Using information from MOD L2 Method profiling, identify trivial or uninterested method names.
  2. Filter out those methods from MOD L3 instrumentation as described on Section 3.5 MOD L3 Method Filtering Option of this document.
  3. Use MOD L2 Method Profiling instead of MOD L3 if applicable.

STEP 6: Confirm that GPE Turbo Option is ON (See Section 4.6. for detail)

  1. GPE Turbo should be always on. Confirm that am.camtoolkit.gpe.turbomode=true in toolkit.properties file.

STEP 7: Disable DC when no monitor is needed (See Section 4.7. for detail)

  1. Disable DC from Web Console when no monitor is needed. This will minimize performance overhead and ability to turn on DC on-line when needed.

ITCAM Data Collector Tuning Options

In the following section each of tuning options will be discussed in the following order:

  1. Name of configuration parameter
  2. Expected impact of tuning
  3. File(s) containing the configuration parameter(s)
  4. Default
  5. Instruction

All tuning options are readily available with ITCAM for WebSphere Application Server V6.1 (FixPack-1) Data Collector installation.

Fine Grained PMI Counter Option

  1. Name of configuration parameter: am.pmi.settings.nochange

  2. Expected impact of tuning: Enabling/Disabling some PMI counters directly impact WebSphere Application Server CPU overhead and throughput performance. Total PMI overhead can be up to 5-6% depending on application behavior. Especially reducing/disabling bean counter may have a large improvement (2-3%) if the application uses many EJBs. If a user is not interested in some PMI counters in MOD level-1, they can be turned off automatically when MOD level-1 is set. Similarly PMI counters in MOD level-2 and level-3 can be fine tuned.

  3. File contains the File(s) containing the configuration parameter(s):
    <DCHOME>/datacollector.properties

  4. Default: am.pmi.settings.nochange=false

  5. Instruction:

    1. Use the default setting am.pmi.settings.nochange=false.

    2. (For WebSphere Application Server V6) Add am.was6custompmi.settings.1 parameter to define specific PMI Counters to be enabled with MOD level-1. A detail description of this parameter is found in datacollector.properties file. Similarly, add am.was6custompmi.settings.2 and am.was6custompmi.settings.3 parameters for MOD level-2 and level-3 PMI counters.

    3. (For WebSphere Application Server V5) Use am.was5pmi.setting.1, am.was5pmi.setting.2 and am_.was5pmi.setting.3_ instead as documented in the datacollector.properties file. Appendix-B lists all PMI counters available for WebSphere Application Server V6 and WebSphere Application Server V5 and their monitoring levels, by which you can map to Data Collector MOD level that uses the counters.

    4. Restart the Application Server (PMI setting will be dynamic after the first restart).

DC Internal Buffer Tuning Option

  1. Name of configuration parameter: internal.memory.limit

  2. Expected impact of tuning parameter: DC Turbo Mode is a data collection mechanism that ensures integrity and successful storage of event data, improves event dequeueing speed, and improves throughput of requests through the application server in the event that the DC's internal buffers become filled. Please see Appendix-A of this document and ITCAM for WAS/J2EE Turbo Mode Guide for detail descriptions. Frequent DC Turbo engagement may not be desirable as it may slow down response times under L3 and high volume L2 monitoring conditions. If this is the case, a user can reduce the probability of DC Turbo Engagement by increasing internal buffer size defined by internal.memory.limit parameter.

  3. File(s) containing the configuration parameter(s):
    <DCHOME>/datacollector.properties

  4. Default: internal.memory.limit=100

  5. Instruction:

    1. Determine if there are frequent DC turbo mode engagements logged in trace-dc.log. A user may also notice occasional pauses of Application Server transactions as indicators of DC Turbo engagement. It is very unlikely for DC Turbo to engage at MOD L1. Usually it engages at L3 with deep tracing or high volume L2 monitoring conditions.

    2. If it is acceptable to have larger DC memory overhead instead of frequent DC turbo mode engagements under L3 and high volume L2 monitoring conditions, increase internal.memory.limit to a larger value, such as 200.

    3. Restart the Application Server.

    4. This will reduce the chance of DC turbo mode engagement. However, it will increase peak memory overhead under high volume DC events by 100MB (or higher).

    5. It is reported that multiple DCs may send bursts of events to the MS simultaneously after the MS is recovering from off-line state. In that case, the larger DC event buffer might exaggerate the size of the bursts.

    6. Another consideration to minimize a chance of DC turbo mode engagement is to upgrade ITCAM Management Server capacity, especially for PS components. Typically DC event flow to MS is limited by the PS processing capacity. We can increase the PS processing capacity by (1) having additional PS process(es) (i.e. less number of DCs that contend against each other per PS) and/or (2) upgrade CPUs of the machine the PS processes are running on by increasing number of CPUs or replacing them with faster CPUs. Instruction to configure additional PS procesces is found in Chapter 10 of ITCAM: Managing Server Installation and Customization Guide (GC32-1931-00) or http://publib.boulder.ibm.com/infocenter/tivihelp/v3r1/index.jsp?topic=/com.ibm.itcamwas.doc_6.1/rev/ms_ws_full130.htm and http://publib.boulder.ibm.com/infocenter/tivihelp/v3r1/index.jsp?topic=/com.ibm.itcamwas.doc_6.1/rev/ms_ws\_full130.htm.

    7. A user should reduce number of DC events for MOD L2 and L3 monitoring by applying tuning options in Sections 3.3, 3.4 and 3.5. These will help reducing overhead by both (1) reducing instrumentation points and (2) reducing DC turbo mode engagement.

MOD Level-2 Instrumentation Tuning Option

  1. Name of configuration parameter: See in prescription.

  2. Expected impact of tuning: Excluding unnecessary L2 instrumentation will reduce L2 performance overhead in terms of CPU and throughput. Instrumentation for L2 nested requests can be easily disabled on a selective base. For WebSphere, instrumentation can be disabled per container basis. For J2 platforms, classes can be filtered out from EJB instrumentation.

  3. File(s) containing the configuration parameter(s): No parameters by default. They can be added to <DCHOME>/runtime/<server-name>/custom/toolkit_custom.properties.

  4. Default: No level-2 instrumentation exclusion.

  5. Instruction:

    1. For selected instrumentations to be disabled, set the corresponding properties in toolkit_custom.properties to a value of 'false':
      • com.ibm.tivoli.itcam.toolkit.ai.enableejb=false # disables EJB instrumentation
      • com.ibm.tivoli.itcam.toolkit.ai.enablejca=false # disables JCA instrumentation
      • com.ibm.tivoli.itcam.toolkit.ai.enablejdbc=false # disables JDBC instrumentation
      • com.ibm.tivoli.itcam.toolkit.ai.enablejndi=false # disables JNDI instrumentation
      • com.ibm.tivoli.itcam.toolkit.ai.enablejms=false # disables JMS instrumentation
      • com.ibm.tivoli.itcam.toolkit.ai.enableservlet=false # disables servlet instrumentation
      • com.ibm.tivoli.itcam.toolkit.ai.enablesessioncount=false # disables HTTP Session counting instrumentation
      • com.ibm.tivoli.itcam.dc.ctg.enablectg=false # disables CTG instrumentation

    2. Restart the Application Server to disable the instrumentations.

J2 Only: On J2EE servers, normally all EJB business methods are instrumented for EJB request data. It's possible to filter out classes from EJB instrumentation and reduce the cost of L1 and L2 data collection. Here is an example of how this can be done. In this case, the customer want to exclude EJB classes from instrumentation from a package called 'sample.package'.

The customer needs to create an XML file in the DCHOME/runtime/<server-name>/custom directory. In this example, he creates a file called excludeEJB.xml, containing the following:

<?xml version="1.0"?>

<gpe>
  <bci>

  <weaveFilters>       

 <selectClass>
     <selectionId>EntityBean</selectionId>
     <Matches>!sample.package.\*</Matches>
 </selectClass>

 <selectClass>
     <selectionId>SessionBean</selectionId>
     <Matches>!sample.package.\*</Matches>
 </selectClass>

 <selectClass>
     <selectionId>MessageDrivenBean</selectionId>
     <Matches>!sample.package.\*</Matches>
 </selectClass>

  </weaveFilters>
 </bci>
</gpe>

The presence of the '!' in front of "sample.package.*" on the <Matches> tag indicates that classes beginning with these prefixes should be excluded from Entity Bean, Session Bean, or Message Driven Bean instrumentation. After creating the XML file, the user should then modify the toolkit_custom.properties file to add a reference to the XML file. The user should add a property that begins with the prefix am.camtoolkit.gpe.customxml, followed by a suffix to make it unique. The value of the property should be the file name of the XML file in order to identify the XML file.
For example:

am.camtoolkit.gpe.customxml..excludeEJB=excludeEJB.xml.

MOD Level-2 Method Profiling Option

  1. Name of configuration parameter: Method Profiling check box in MOD level-2 configuration page in Web Console.

  2. Expected impact of tuning: Use MOD L2 Method Profiling instead of MOD L3 when it is sufficient. MOD L2 Method profiling provides method entry/exit data but only as aggregated data per method whereas L3 provide instance data. This will dramatically reduce volume of data generated by DC and thus reduce CPU and memory overhead and the chance of DC event buffer overflow.

  3. File(s) containing the configuration parameter(s): Method Profiling check box in MOD level-2 configuration page in Web Console.

  4. Default: disabled

  5. Instruction:

  6. Configure L3 BCI by uncommenting am.camtoolkit.gpe.customxml.L3 in <DCHOME>/runtime/<server-name>/custom/toolkit_custom.properties.

    1. Uncomment and set com.ibm.tivoli.itcam.toolkit.ai.methodentryexittrace **property in <DCHOME>/runtime/<server-name>/custom/toolkit_custom.properties to true.

    2. Restart the Application Server

    3. Set MOD L2 and check MOD L2 Method Profiling check mark in the ITCAM MS Adminstrator Console ADMINISTRATIONMONITORING ON DEMAND.

    4. Use MOD L2 with Method Profiling instead of MOD L3 when aggregated method entry/exit data is sufficient

    5. In <DCHOME>/runtime/<server-name>/<server-name>.datacollector.properties file, there are a few parameters to fine tune Method Profiling behavior. Important ones are:

      • # Support for Method Profiling
      • am.mp.cpuThreshold=30
      • am.mp.clockThreshold=30
      • am.mp.leagueTableSize=10000

am.mp.cpu.Threshold (in nanoseconds) and am.mp.clock.Threashold (in milliseconds) specify minimum CPU and clock times for a method to get measured. Method profiling allocates a fixed size table at startup time, in which it saves its method statistics. The size of this table is given by the am.mp.leagueTableSize property. The default is 10000, but a user might find that this value is too small. A user may need to experiment with this value to find out what is the sufficient size of the table. If it is too small, Method Profiling output will not display all methods captured. If a user increases the size of this property, application server needs to be restarted.

MOD Level-3 Method Filtering Option

  1. Name of configuration parameter: method_entry_exit.xml file

  2. Expected impact of tuning: Excluding unnecessary classes/methods from L3 method instrumentation by controlling Byte Code Injection will reduce L3 performance overhead in terms of CPU and throughput. DC configuration in Management Server Web Console also can exclude methods dynamically without having to restart server but this static definition of BCI exclusion is better in performance.

    In most cases, level-3 monitoring generates a large number of method entry/exit data from a small set of classes/methods - sometimes from just 2 or 3 methods. Also it is typical that the most of these methods have trivial response times and thus less investigative value for transaction performance analysis. Proper tuning of L3 instrumentation requires that unimportant or trivial methods should not be instrumented or reported on. However, often, it's difficult to determine which classes and methods should be filtered out.

    You can use Method Profiling feature described in Section 3.4 of this document to help spotting those classes or methods that should be filtered out. By enabling Method Profiling, and then analyzing the resulting data, you can quickly determine which methods are either of no interest or run so briefly and so often that collecting detailed data is unnecessary. Once these methods are filtered out, L3 tracing will consume less overhead, and the reports will be easier to read and provide more value to the customer.

    Also consider using L3 Filter Generation Tool developed by ITCAM ACE team (available on CAM Wiki page), which allows the user to construct an XML filter for monitoring methods based on existing data in the ITCAM for WebSphere database. This helps significantly with overhead at Level 3.

  3. File(s) containing the configuration parameter(s): <DCHOME>/itcamdc/etc/method_entry_exit.xml

  4. Default: No custom method exclusion.

  5. Instruction:

    1. Uncomment am.camtoolkit.gpe.customxml.L3 in <DCHOME>/runtime/<server-name>/custom/toolkit_custom.properties to enable MOD L3 BCI.

    2. Uncomment and set com.ibm.tivoli.itcam.toolkit.ai.methodentryexittrace **property in <DCHOME>/runtime/<server-name>/custom/toolkit_custom.properties to true.

    3. Edit <DCHOME>/itcamdc/etc/method_entry_exit.xml as in the example below to exclude unnecessary classes/methods.

    4. Restart application server.

Example of custom L3 method filtering: Within the Customer class, we want all methods to be BCI'd for entry/exit. Within the Supplier class, all methods should be BCI'd, except for those methods beginning with 'get' or 'set'.

GPE Turbo Option

  1. Name of configuration parameter: am.camtoolkit.gpe.turbomode

  2. Expected impact of tuning: GPE turbo will reduce code path in java BCM logic unnecessary for MOD L1 and MOD L2 monitoring levels, therefore will reduce CPU and throughput overhead of MOD L1 and L2. Note that this option should be true always for performance optimization. We provide this option for a future potential functionality/compatibility and no need to turn it off with ITCAM for WebSphere Application Server/J2EE V6.1.

  3. File(s) containing the configuration parameter(s):
    <DCHOME>/toolkit/etc/toolkit.properties

  4. Default: am.camtoolkit.gpe.turbomode=true

  5. Instruction:

    1. Confirm that am.camtoolkit.gpe.turbomode=true.

    2. If it has been set to false, set am.camtoolkit.gpe.turbomode=true and restart the Application Server to configure GPE Turbo option for minimum MOD L1 and L2 overhead.

Disable DC Option

  1. Name of configuration parameter: Data collector Configuration in ITCAM Web Console

  2. Expected impact of tuning: Minimize DC overhead to disable DC monitors. This will give them a heart beat and the ability to enable DC when needed.

  3. File(s) containing the configuration parameter(s): This is ITCAM Web Console configuration: ADMINISTRATION --> SERVER MANAGEMENT --> DATA COLLECTOR CONFIGURATION

  4. Default: DC enabled

  5. In ITCAM Web Console: ADMINISTRATION --> SERVER MANAGEMENT --> DATA COLLECTOR CONFIGURATION and select "Disable" button

ITCAM Data Collector Best Practices

  • Use MOD Level-2 Method Profiling instead of MOD Level-3. In most cases, the aggregate method entry/exit data is sufficient for transaction performance analysis. Often aggregate data is more powerful to understand nature of performance issues than instance data, yet it offers lower overhead.
  • Fine tune MOD L3 filter using Method Profiling data and L3 Filter Generation Tool.
  • Do not collect more data than you can effectively analyze. Generating detail data by itself will not help resolving performance problems at all; rather it will induce more performance overhead to your system.
  • A good performance analysis is typically done based on a small set of data with some inductive/deductive thinking processes. A flood of data usually just confuses you.

APPENDIX A

This Appendix is a list of high level descriptions of ITCAM for WebSphere Application Server/J2EE V6.1 features involved in the tuning options presented in this document.

DC Turbo Mode

DC Turbo is a data handling algorithm in DC native code controlled by properties in datacollector.properties file. Detail of DC Turbo can be found in ITCAM for WebSphere/J2EE Turbo Mode Guide available on CAM Wiki. Engaging DC turbo will change DC data handling logic in native codes. It will increase DC data throughput to Management Server component by (1) raising the priority of native event agents and network agents and (2) lowering the sleep times of native event agents and network agents when native DC event buffer size grows over a threshold specified by turbo.mem.ulimit (default is 75% of internal.memory.limit specified in Megabytes (MB) with a default value of 100). When DC event buffer size goes down to a level specified by turbo.mem.llimit (default is 60% of internal.memory.limit specified in MB with a default value of 100) it goes back to normal mode. It will also reduce incoming data by turn off all instrumentation of newly arriving transactions during Turbo Mode. This will ensure that no DC event data will be dropped but may negatively impact J2EE transactions/requests throughput during DC turbo mode as DC network and event agents take higher priority and CPU time is taken away from J2EE transaction/request threads. The throughput may be partially compensated by disabling instrumentation for newly arriving transactions. Also note that enabling DC turbo configuration by itself should not affect performance if Turbo mode does not engage.

Method Profiling

Method Profiling is an optional feature of MOD L2 monitoring available in MOD L2 configuration screen. **MOD L2 Method profiling provides method entry/exit data but only as aggregated data per method whereas L3 provide instance data. This will dramatically reduce volume of data generated by DC and thus reduce CPU and memory overhead and the chance of DC event buffer overflow.

AspectJ and Weaving

AspectJ is Byte Code Instrumentation (BCI) technology adopted by ITCAM for WebSphere Application Server/J2EE V6.1 data collector and weaving is an AspectJ terminology for bytecode instrumentation.

GPE Turbo

GPE turbo will reduce code path in java BCM logic unnecessary for MOD L1 and MOD L2 monitoring levels, therefore will reduce CPU and throughput overhead of MOD L1 and L2. Note that this option should be true always for performance optimization. We provide this option for a future potential functionality/compatibility and no need to turn it off with ITCAM for WebSphere Application Server/J2EE V6.1.

APPENDIX B

Enabling WebSphere Application Server V6.x Performance Monitoring Infrastructure(PMI)

WebSphere Application Server V6 PMI data is organized according to B (Basic), E(Extended), A (All). By default DC Monitoring levels are configured according to the following PMI levels. At L1 - Basic, L2 - Extended, L3 - All. So the following table describes which counters are displayed at what level.

Resource Model WebSphere V5 and V6 PMI Metrics that must be enabled for collection Statistic set in which they are collected:
B=Basic
E=Extended- superset of B
A=All- superset of E
WebSphere Application Server V6 Statistic Set to enable
Application Server Status N/A N/A N/A
DB Pools JDBC Connection Pools.FaultCount JDBC Connection Pools.JDBCTime
JDBC Connection Pools.PercentUsed
JDBC Connection Pools.WaitTime
E
E
B
E
E
Dynamic Cache DynamicCaching.cacheModule.template.HitsInMemory
DynamicCaching.cacheModule.template.Misses
E
E
E
EJBs Enterprise Beans.MethodCallCount
Enterprise Beans.MethodResponseTime Enterprise Beans.ReturnsDiscardCount
Enterprise Beans.ReturnsToPoolCount
B
B
E
E
E
HTTP Sessions Servlet Session Manager.LiveCount
Servlet Session Manager.NoRoomForNewSessionCount
E
E
E
J2C Connection Pool JCA Connection Pools.UseTime B B
JVM Runtime JVM Runtime.FreeMemory
JVM Runtime.UsedMemory
E
B
E
Node Agent Status N/A N/A N/A
Resource Use N/A N/A N/A
ThreadPool Thread Pools.ActiveCount
Thread Pools.PoolSize
E
B
E
Transactions Transaction Manager.CommittedCount
Transaction Manager.GlobalBegunCount
Transaction Manager.GlobalTimeoutCount
Transaction Manager.GlobalTranTime
Transaction Manager.LocalBegunCount
Transaction Manager.LocalCommittedCount
Transaction Manager.LocalTimeoutCount
Transaction Manager.LocalTranTime
B
E
E
E
E
A
E
E
E
Web Applications Web Applications.ConcurrentRequests
Web Applications.ErrorCount
Web Applications.RequestCount
Web Applications.ServiceTime
E
E
B
B
E

If you enable the Extended set, apply & save, then go to Custom set, you can add LocalCommittedCount to the set of enabled metrics and won't need to enable All.

WebSphere Application Server V5 PMI Counters

WebSphere Application Server V5 PMI metrics are organized according to NONE, LOW, MEDIUM, HIGH, XTREME. At each DC monitoring level, we have certain PMI level in effect by default. At L1- PMI level is at (M) MEDIUM, L2 - (H) HIGH, L3 - (X) XTREME. The following tables describe which metrics are displayed at what levels.

BeanModule data counters

Data counter definitions

Name Description Version Granularity Type Level
creates Number of times beans were created 3.5.5 and above per home CountStatistic Low
removes Number of times beans were removed 3.5.5 and above per home CountStatistic Low
passivates Number of times beans were passivated (entity and stateful) 3.5.5 and above per home CountStatistic Low
activates Number of times beans were activated (entity and stateful) 3.5.5 and above per home CountStatistic Low
persistence loads Number of times bean data was loaded from persistent storage (entity) 3.5.5 and above per home CountStatistic Low
persistence stores Number of times bean data was stored in persistent storage (entity) 3.5.5 and above per home CountStatistic Low
instantiations Number of times bean objects were instantiated 3.5.5 and above per home CountStatistic Low
destroys Number of times bean objects were freed 3.5.5 and above per home CountStatistic Low
Num Ready Beans Number of concurrently ready beans (entity and session). This counter was called concurrent active in Versions 3.5.5+ and 4.0. 3.5.5 and above per home RangeStatistic High
concurrent live Number of concurrently live beans 3.5.5 and above per home RangeStatistic High
avg method rsp time Average response time in milliseconds on the bean methods (home, remote, local) 3.5.5 and above per home TimeStatistic High
avg method rsp time for create Average time in milliseconds a bean create call takes including the time for the load if any 5.0 per home TimeStatistic Medium
avg method rsp time for load Average time in milliseconds for loading the bean data from persistent storage (entity) 5.0 per home TimeStatistic Medium
avg method rsp time for store Average time in milliseconds for storing the bean data to persistent storage (entity) 5.0 per home TimeStatistic Medium
avg method rsp time for remove Average time in milliseconds a bean entries call takes including the time at the database, if any 5.0 per home TimeStatistic Medium
total method calls total number of method calls 3.5.5 and above per home CountStatistic High
avg method rsp time for activation Average time in milliseconds a beanActivate call takes including the time at the database, if any 5.0 per home TimeStatistic Medium
avg method rsp time for passivation Average time in milliseconds a beanPassivate call takes including the time at the database, if any 5.0 per home TimeStatistic Medium
active methods Number of concurrently active methods - num methods called at the same time. 3.5.5 and above per home TimeStatistic High
Per method invocations Number of calls to the bean methods (home, remote, local) 3.5.5 and above per method/per home CountStatistic Max
Per method rsp time Average response time in milliseconds on the bean methods (home, remote, local) 3.5.5 and above per home TimeStatistic Max
Per method concurrent invocations Number of concurrent invocations to call a method 5.0 per method/per home RangeStatistic Max
getsFromPool Number of calls retrieving an object from the pool (entity and stateless) 3.5.5 and above per home/object pool CountStatistic Low
getsFound Number of times a retrieve found an object available in the pool (entity and stateless) 3.5.5 and above per home/object pool CountStatistic Low
returnsToPool Number of calls returning an object to the pool (entity and stateless) 3.5.5 and above per home/object pool CountStatistic Low
returnsDiscarded Number of times the returning object was discarded because the pool was full (entity and stateless) 3.5.5 and above per home/object pool CountStatistic Low
drainsFromPool Number of times the daemon found the pool was idle and attempted to clean it (entity and stateless) 3.5.5 and above per home/object pool CountStatistic Low
avgDrainSize Average number of objects discarded in each drain (entity and stateless) 3.5.5 and above per home/object pool TimeStatistic Medium
avgPoolSize Number of objects in the pool (entity and stateless) 3.5.5 and above per home/object pool RangeStatistic High
messageCount Number of messages delivered to the bean onMessage method (message driven beans) 5.0 per type CountStatistic Low
messageBackoutCount Number of messages failed to be delivered to the bean onMessage method (message driven beans) 5.0 per type CountStatistic Low
serverSessionWait Average time to obtain a ServerSession from the pool (message drive bean) 5.0 per type TimeStatistic Medium
serverSessionUsage Percentage of server session pool in use (message driven) 5.0 per type RangeStatistic High

JDBC connection pool data counters

Data counter definitions

PMI collects performance data for 4.0 and 5.0 JDBC data sources. For a 4.0 data source, the data source name is used. For a 5.0 data source, the JNDI name is used.

Name Description Version Granularity Type Level
creates Total number of connections created 3.5.5 and above per connection pool CountStatistic Low
avg pool size Average pool size 3.5.5 and above per connection pool BoundedRangeStatistic High
free pool size Average free pool size 5.0 per connection pool BoundedRangeStatistic High
allocates Total number of connections allocated 3.5.5 and above per connection pool CountStatistic Low
returns Total number of connections returned 4.0 and above per connection pool CountStatistic Low
avg waiting threads Number of threads that are currently waiting for a connection 3.5.5 and above per connection pool RangeStatistic High
connection pool faults Total number of faults, such as, timeouts, in connection pool 3.5.5 and above per connection pool CountStatistic Low
destroys Number of times bean objects were freed 3.5.5 and above per connection pool CountStatistic Low
avg wait time Average waiting time in milliseconds until a connection is granted 5.0 per connection pool TimeStatistic Medium
avg time in use Average time a connection is used 5.0 per connection pool TimeStatistic Medium
percent used Average percent of the pool that is in use 3.5.5 and above per connection pool RangeStatistic High
percent maxed Average percent of the time that all connections are in use 3.5.5 and above per connection pool RangeStatistic High
Statement cache discard count Total number of statements discarded by the LRU algorithm of the statement cache 4.0 and above per connection pool CountStatistic Low
Number managed connections Number of ManagedConnection objects in use 5.0 per connection factory CountStatistic Low
Number connections Current number of connection objects in use 5.0 per connection factory CountStatistic Low
jdbcOperationTimer Amount of time in milliseconds spent executing in the JDBC driver 5.0 per data source TimeStatistic Medium

J2C connection pool data counters

Data counter definitions

Name Description Version Granularity Type Level
Number managed connections Number of ManagedConnection objects in use 5.0 per connection factory CountStatistic Low
Number connections Current number of connection objects in use 5.0 per connection factory CountStatistic Low
Number managed connections created Total number of connections created 5.0 per connection factory CountStatistic Low
Number managed connections destroyed Total number of connections destroyed 5.0 per connection factory CountStatistic Low
Number managed connections allocated Total number of connections allocated 5.0 per connection factory CountStatistic Low
Number managed connections freed Total number of connections freed 5.0 per connection factory CountStatistic Low
faults Number of faults, such as timeouts, in connection pool 5.0 per connection factory CountStatistic Low
free pool size Number of free connections in the pool 5.0 per connection factory BoundedRangeStatistic High
pool size Pool size 5.0 per connection factory BoundedRangeStatistic High
concurrent waiters Average number of threads concurrently waiting for a connection 5.0 per connection factory RangeStatistic High
Percent used Average percent of the pool that is in use 5.0 per connection factory RangeStatistic High
Percent maxed Average percent of the time that all connections are in use 5.0 per connection factory RangeStatistic High
Average wait time Average waiting time in milliseconds until a connection is granted 5.0 per connection factory TimeStatistic Medium
Average use time Average time in milliseconds that connections are in use 5.0 per connection factory TimeStatistic Medium

Java Virtual Machine data counters

Data counter definitions

Name Description Version Granularity Type Level
Free memory Free memory in JVM run time 3.5.5 and above per Java Virtual Machine (JVM) CountStatistic Low
Used memory Used memory in JVM run time 3.5.5 and above per JVM CountStatistic Low
Total memory Total memory in JVM run time 3.5.5 and above per JVM BoundedRangeStatistic High
Up time The amount of time the JVM is running 5.0 per JVM CountStatistic Low
Number garbage collection calls Number of garbage collection calls. This counter is not available unless -XrunpmiJvmpiProfiler is set when starting the JVM. 4.0 and above per JVM CountStatistic Max
Average time between garbage collection Average garbage collection in seconds between two garbage collection. This counter is not available unless -XrunpmiJvmpiProfiler is set when starting the JVM. 4.0 and above per JVM TimeStatistic Max
Average garbage collection duration Average duration of a garbage collection. This counter is not available unless -XrunpmiJvmpiProfiler is set when starting the JVM. 4.0 and above per JVM TimeStatistic Max
num waits for a lock Number of times that a thread waits for a lock.This counter is not available unless -XrunpmiJvmpiProfiler is set when starting the JVM. 4.0 and above per JVM CountStatistic Max
avg time waiting for lock Average time that a thread waits for a lock. This counter is not available unless -XrunpmiJvmpiProfiler is set when starting the JVM. 4.0 and above per JVM TimeStatistic Max
Number of objects allocated Number of objects allocated in heap. This counter is not available unless -XrunpmiJvmpiProfiler is set when starting the JVM. 4.0 and above per JVM CountStatistic Max
Number of objects found Number of objects in heap. This counter is not available unless -XrunpmiJvmpiProfiler is set when starting the JVM. 4.0 and above per JVM CountStatistic Max
Number of objects freed Number of objects freed in heap. This counter is not available unless -XrunpmiJvmpiProfiler is set when starting the JVM. 4.0 and above per JVM CountStatistic Max

Object Request Broker data counters

Data counter definitions

Name Description Version Granularity Type Level
referenceLookupTime The time (in milliseconds) to look up an object reference before method dispatch can be carried out 5.0 Object Request Broker (ORB) TimeStatistic Medium
numRequest The total number of requests sent to the ORB 5.0 ORB CountStatistic Low
concurrentRequests The number of requests that are concurrently processed by the ORB 5.0 ORB RangeStatistic High
processingTime The time (in milliseconds) it takes a registered portable interceptor to run 5.0 per interceptor TimeStatistic Medium

Session data counters

Data counter definitions

Name Description Version Granularity Type Level
createdSessions Number of sessions created 3.5.5 and above per web application CountStatistic Low
invalidatedSessions Number of sessions invalidated 3.5.5 and above per web application CountStatistic Low
sessionLifeTime The average session lifetime 3.5.5 and above per web application TimeStatistic Medium
activeSessions The number of concurrently active sessions. A session is active if WebSphere is currently processing a request which uses that session. 3.5.5 and above per web application RangeStatistic High
liveSession The number of sessions that are currently cached in memory 5.0 and above per web application RangeStatistic High
NoRoomForNewSession Applies only to session in memory with AllowOverflow=false. The number of times that a request for a new session can not be handled because it would exceed the maximum session count. 5.0 per Web application CountStatistic Low
cacheDiscards Number of session objects that have been forced out of the cache. (An LRU algorithm removes old entries to make room for new sessions and cache misses). Applicable only for persistent sessions. 5.0 per Web application CountStatistic Low
externalReadTime Time (milliseconds) taken in reading the session data from persistent store. For multirow sessions, the metrics are for the attribute; for single row sessions, the metrics are for the whole session. Applicable only for persistent sessions. When using a JMS persistent store, the user has the choice of whether to serialize the data being replicated. If they choose not to serialize the data, the counter will not be available. 5.0 per Web application TimeStatistic Medium
externalReadSize Size of session data read from persistent store. Applicable only for (serialized) persistent sessions; similar to externalReadTime above. 5.0 per Web application TimeStatistic Medium
externalWriteTime Time (milliseconds) taken to write the session data from the persistent store. Applicable only for (serialized) persistent sessions. Similar to externalReadTime above. 5.0 per Web application TimeStatistic Medium
externalWriteSize Size of session data written to persistent store. Applicable only for (serialized) persistent sessions. Similar to externalReadTime above. 5.0 per Web application TimeStatistic Medium
affinityBreaks The number of requests received for sessions that were last accessed from another Web application. This can indicate failover processing or a corrupt plug-in configuration. 5.0 per Web application CountStatistic Low
serializableSessObjSize The size in bytes of (the serializable attributes of ) in-memory sessions. Only count session objects that contain at least one serializable attribute object. Note that a session may contain some attributes that are serializable and some that are not. The size in bytes is at a session level. 5.0 per Web application TimeStatistic Max
timeSinceLastActivated The time difference in milliseconds between previous and current access time stamps. Does not include session time out. 5.0 per Web application TimeStatistic Medium
invalidatedViaTimeout The number of requests for a session that no CountStatistic exists, presumeably because the session timed out. 5.0 per Web application CountStatistic Low
attemptToActivateNotExistentSession Number of requests for a session that no longer exists, presumeably because the session timed out. Use this counter to help determine if the timeout is too short. 5.0 per Web application CountStatistic Low

Transaction data counters

Data counter definitions

Name Description Version Granularity Type Level
Number global transactions begun Total number of global transactions begun on server 4.0 and above per transaction manager/server CountStatistic Low
Number global transactions involved Total number of global trans involved on server (for example, begun and imported) 4.0 and above per transaction manager/server CountStatistic Low
Number local transactions begun Total number of local transactions begun on server 4.0 and above per transaction manager/server CountStatistic Low
Active global transactions Number of concurrently active global transactions 3.5.5 and above per transaction manager/server CountStatistic Low
Active local transactions Number of concurrently active local transactions 4.0 and above per transaction manager/server CountStatistic Low
Global transactions duration Average duration of global transactions 3.5.5 and above per transaction manager/server TimeStatistic Medium
Local transaction duration Average duration of local transactions 4.0 and above per transaction manager/server TimeStatistic Medium
Local transactions before_completion time Average duration of before_completion for local transactions 4.0 and above per transaction manager or server TimeStatistic Medium
Global transaction commit time Average duration of commit for global transactions 4.0 and above per transaction manager/server TimeStatistic Medium
Global transaction prepare time Average duration of prepare for global transactions 4.0 and above per transaction manager/server TimeStatistic Medium
Local transaction before_completion time Average duration of before_completion for local transactions 4.0 and above per transaction manager/server TimeStatistic Medium
Local transaction commit time Average duration of commit for local transactions 4.0 and above per transaction manager/server TimeStatistic Medium
Number global transactions committed Total number of global transactions committed 3.5.5 and above per transaction manager/server CountStatistic Low
Number of global transactions rolled back Total number of global transactions rolled back 3.5.5 and above per transaction manager/server CountStatistic Low
Number global transactions optimized Number of global transactions converted to single phase for optimization 4.0 and above per transaction manager/server CountStatistic Low
Number of local transactions committed Number of local transactions committed 4.0 and above per transaction manager/server CountStatistic Low
Number of local transactions rolled back Number of local transactions rolled back 4.0 and above per transaction manager/server CountStatistic Low
Number of global transactions timed out Number of global transactions timed out 4.0 and above per transaction manager/server CountStatistic Low
Number of local transactions timed out Number of local transactions timed out 4.0 and above per transaction manager/server CountStatistic Low

ThreadPool data counters

Data counter definitions

Name Description Version Granularity Type Level
Thread creates Total number of threads created 3.5.5 and above per thread pool CountStatistic Low
Thread destroys Total number of threads destroyed 3.5.5 and above per thread pool CountStatistic Low
Active threads The number of concurrently active threads 3.5.5 and above per thread pool RangeStatistic High
Pool size Average number of threads in pool 3.5.5 and above per thread pool BoundedRangeStatistic High
Percent maxed Average percent of the time that all threads are in use 3.5.5 and above per thread pool RangeStatistic High

Web application data counters

Data counter definitions

Name Description Version Granularity Type Level
numLoadedServlets Number of servlets that were loaded 3.5.5 and above per Web application CountStatistic Low
numReloads Number of servlets that were reloaded 3.5.5 and above per Web application CountStatistic Low
totalRequests Total number of requests a servlet processed 3.5.5 and above per servlet CountStatistic Low
concurrentRequests Number of requests that are concurrently processed 3.5.5 and above per servlet RangeStatistic High
responseTime The response time, in milliseconds, of a servlet request 3.5.5 and above per servlet TimeStatistic Medium
numErrors Total number of errors in a servlet or Java Server Page (JSP) 3.5.5 and above per servlet CountStatistic Low

Workload Management data counters

Data counter definitions

Name Description Version Granularity Type Level
numIncomingRequests Total number of incoming IIOP requests to an application server 5.0 per server CountStatistic Low
numIncomingStrongAffinityRequests Number of incoming IIOP requests to an application server that are based on a strong affinity. A strong affinity request is defined as a request that must be serviced by this application server because of a dependency that resides on the server. This request could not successfully be serviced on another member in the server cluster. In Version 5.0 ND edition, transactional affinity is the only example of a strong affinity 5.0 per server CountStatistic Low
numIncomingNonAffinityRequests Number of incoming IIOP requests to an application server based on no affinity. This request was sent to this server based on workload management selection policies that were decided in the Workload Management (WLM) run time of the client. 5.0 per server CountStatistic Low
numIncomingNonWLMObjectRequests Number of incoming IIOP requests to an application server that came from a client that does not have the WLM run time present or where the object reference on the client was flagged not to participate in workload management. 5.0 per server CountStatistic Low
numServerClusterUpdates Number of times initial or updated server cluster data is sent to a server member from the deployment manager. This metric determines how often cluster information is being propagated. 5.0 per server CountStatistic Low
numOfWLMClientServiced Number of WLM enabled clients that have been serviced by this application server. 5.0 per server CountStatistic Low
numOfConcurrentRequests Number of remote IIOP requests currently being processed by this server 5.0 per server RangeStatistic High
serverResponseTime The response time (in milliseconds) of IIOP requests being serviced by an application server. The response time is calculated based on the time the request is received to the time when the reply is sent back out. 5.0 per server TimeStatistic Medium
numOfOutgoingRequests The total number of outgoing IIOP requests being sent from a client to an application server 5.0 per WLM CountStatistic Low
numClientClusterUpdates The number of times initial or updated server cluster data is sent to a WLM enabled client from server cluster member. Use this metric to determine how often cluster information is being propagated. 5.0 per WLM CountStatistic Low
clientResponseTime The response time (in milliseconds) of IIOP requests being sent from a client. The response time is calculated based on the time the request is sent from the client to the time the reply is received from the server. 5.0 per WLM TimeStatistic Medium

System data counters

Data counter definitions

Name Description Version Granularity Type Level
percentCpuUsage The average system CPU utilization taken over the time interval since the last reading. Because the first call is required to perform initialization, an invalid value such as 0 will be returned. All subsequent calls will return the expected value. On SMP machines, the value returned will be the utilization averaged over all CPUs. 5.0 per node CountStatistic Low
freeMemory The amount of real free memory available on the system. Real memory that is not allocated is only a lower bound on available real memory, since many operating systems take some of the otherwise unallocated memory and use it for additional I/O buffering. The exact amount of buffer memory which can be freed up is dependent on both the platform and the application(s) running on it. 5.0 per node CountStatistic Low
avgCpuUsage The average percentCpuUsage that is busy after the server is started 5.0 per node TimeStatistic Medium

Dynamic cache data counters

Data counter definitions

Name Description Version Granularity Type Level
maxInMemoryCacheSize Maximum number of in-memory cache entries 5.0 per server CountStatistic Low
inMemoryCacheSize Current number of in-memory cache entries 5.0 per server CountStatistic Low
totalTimeoutInvalidation Aggregate of template timeouts and disk timeouts 5.0 per server CountStatistic Low
hitsInMemory Requests for this cacheable object served from memory 5.0 per template CountStatistic Low
hitsOnDisk Requests for this cacheable object served from disk 5.0 per template CountStatistic Low
explicitInvalidations Total explicit invalidation issued for this template 5.0 per template CountStatistic Low
lruInvalidations Cache entries evicted from memory by a Least Recently Used algorithm. These entries are passivated to disk if disk overflow is enabled. 5.0 per template CountStatistic Low
timeoutInvalidations Cache entries evicted from memory and/or disk because their timeout has expired 5.0 per template CountStatistic Low
Entries Current number of cache entries created from this template. Refers to the per-template equivalent of totalCacheSize. 5.0 per template CountStatistic Low
hitsRemove Requests for this cacheable object served from other Java Virtual Machines (JVM) in the cluster 5.0 per template CountStatistic Low
Misses Requests for this cacheable object that were not found in the cache 5.0 per template CountStatistic Low
RequestFromClient Requests for this cacheable object generated by applications running on the application server 5.0 per template CountStatistic Low
requestsFromJVM Requests for this cacheable object generated by cooperating caches in this cluster 5.0 per template CountStatistic Low
explicitInvalidationsFromMemory Explicit invalidations resulting in an entry being removed from memory 5.0 per template CountStatistic Low
explicitInvalidationsFromDisk Explicit invalidations resulting in an entry being removed from disk 5.0 per template CountStatistic Low
explicitInvalidationsNoOp Explicit invalidations received for this template where no corresponding entry exists 5.0 per template CountStatistic Low
explicitInvalidationsLocal Explicit invalidations generated locally, either programmatically or by a cache policy 5.0 per template CountStatistic Low
explicitInvalidationsRemote Explicit invalidations received from a cooperating JVM in this cluster 5.0 per template CountStatistic Low
remoteCreations Entries received from cooperating dynamic caches 5.0 per template CountStatistic Low

Web Service Gateway (WSGW) data counters

Data counter definitions

Name Description Version Granularity Type Level
synchronousRequests Number of synchronous requests that were made 5.0 per Web service CountStatistic Low
synchronousResponses Number of synchronous responses that were made 5.0 per Web service CountStatistic Low
asynchronousRequests Number of asynchronous requests that were made 5.0 per Web service CountStatistic Low
asynchronousResponses Number of asynchronous responses that were made 5.0 per Web service CountStatistic Low

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