CLM Monitoring Managed Beans Reference

This content is O B S O L E T E

Please go to the monitoring page of the deployment wiki for a more organized, structured set of documents on our managed beans by version and product.

Managed beans (MBeans) are "Java objects that represent a manageable resource, such as an application, a service, a component, or a device" (1). These objects are available through a MBean Server or Java Management Extensions (JMX) agent.

Over the last few releases, we have been working to instrument the CLM applications using managed beans. This is part of our serviceability strategy for the product. Provide detailed instrumentation and best practices for collecting data on how your system is behaving.

This document outlines the various managed beans available in the product.

Java Virtual Machine Managed Beans

The two key managed beans we consume from the Java Virtual Machine are the Garbage Collector and Operating System beans.

Garbage Collector

This managed bean is providing information about the Garbage Collector. It is used for monitoring the virtual machine's garbage collection metrics. The CollectionTime, CollectionCount should be used for alerts.

Key Attributes	Description	MBean	Frequency
LastCollectionEndTime	Returns the end time in milliseconds of the last garbage collection that was carried out by this collector.	GarbageCollector	15m
CollectionCount	Returns the total number of collections that have occurred. This is set to -1 if the collection count is undefined for this collector.	GarbageCollector	15m
CollectionTime	Returns the approximate accumulated collection elapsed time in milliseconds. The Java virtual machine implementation may use a high resolution timer to measure the elapsed time. This method may return the same value even if the collection count has been incremented if the collection elapsed time is very short.	GarbageCollector	15m
MemoryUsed	Returns the amount of heap memory used by objects that are managed by the collector corresponding to this bean object.	GarbageCollector	15m
TotalMemoryFreed	Returns the cumulative total amount of memory freed, in bytes, by the garbage collector corresponding to this bean object.	GarbageCollector	15m
TotalCompacts	Returns the cumulative total number of compacts that was performed by garbage collector corresponding to this bean object.	GarbageCollector	15m
LastCollectionStartTime	Returns the start time in milliseconds of the last garbage collection that was carried out by this collector.	GarbageCollector	15m

• Garbage Collector Object Name: java.lang:type=GarbageCollector, name=collector's name

Operating System

This managed bean is providing information about the operating system metrics. It is used for monitoring CPU, Swap Space and Physical Memory Usage. The FreePhysicalMemorySize, FreeSwapSpaceSize, SystemCpuLoad should be used for alerts.

Key Attributes	Description	MBean	Frequency
SystemCpuLoad	Returns the "recent cpu usage" for the whole system. This value is a double in the [0.0,1.0] interval. A value of 0.0 means all CPUs were idle in the recent period of time observed, while a value of 1.0 means that all CPUs were actively running 100% of the time during the recent period of time observed. All values between 0.0 and 1.0 are possible.	OperatingSystem	15m
TotalPhysicalMemory	Returns the total available physical memory on the system in bytes.	OperatingSystem	15m
FreePhysicalMemorySize	Returns the amount of physical memory that is available on the system in bytes.	OperatingSystem	15m
TotalSwapSpaceSize	Returns the total amount of swap space in bytes.	OperatingSystem	15m
FreeSwapSpaceSize	Returns the amount of free swap space in bytes.	OperatingSystem	15m

• Operating System Object Name: java.lang:type=OperatingSystem

WebSphere Liberty Managed Beans

There are four managed beans we use from the WebSphere Liberty Application Server are Liberty Java Virtual Machine, Servlet Statistics, Session Statistics and Thread Pools beans.

Liberty Java Virtual Machine

This managed bean provides Liberty application server specific Java Virtual Machine information. It is available when the monitor-1.0 feature is enabled. It is used for monitoring the JVM information. Memory usage is a very important monitoring attribute for the Application Server. High memory usage could indicate high usage by deployed applications, heavy user workloads or memory leaks. The UsedMemory and ProcessCpu attributes should be used for alerts.

Key Attributes	Description	MBean	Frequency
UpTime	Time in milliseconds since the JVM has started.	JvmStats	15m
Heap	Heap size used for current JVM.	JvmStats	15m
FreeMemory	Free team available for the current JVM.	JvmStats	15m
UsedMemory	Used heap for current JVM.	JvmStats	15m
ProcessCPU	Percentage of CPU used by JVM process.	JvmStats	15m
GcCount	Number of times GC has happened since JVM starts.	JvmStats	15m
GcTime	Total accumulated value of GC time.	JvmStats	15m

• Liberty Java Virtual Machine Object Name: WebSphere:type=JvmStats

Servlet Statistics

The Servlet Statistics managed bean is used to provide servlet response times. When the monitor-1.0 feature is enabled, one instance is available for each servlet that has been served, where * is of the form AppName.ServletName. It is used to monitor servlet counts and average response times. The ResponseTime should be used for alerts.

Key Attributes	Description	MBean	Frequency
ResponseTimeDetails	ResponseTime details including number of snapshot taken, min and max values.	ServletStats	15m
AppName	Name of the application.	ServletStats	15m
ServletName	Name of the Servlet.	ServletStats	15m
RequestCount	Number of hits to this servlet.	ServletStats	15m
ResponseTime	Average response time (nano-seconds)	ServletStats	15m
Description	Description of counter.	ServletStats	15m
RequestCountDetails	RequestCount details including last time stamp.	ServletStats	15m

• Liberty Servlet Statistics Object Name: WebSphere:type=ServletStats,name=*

Session Statistics

The session statistics managed bean is responsible for reporting SessionStats for a single web application. It is available when the monitor-1.0 feature is enabled.

Key Attributes	Description	MBean	Frequency
InvalidatedCountbyTimeout	The total number of sessions invalidated by a timeout.	SessionStats	15m
CreateCount	Total number of sessions created.	SessionStats	15m
LiveCount	The total number of sessions that are currently cached in memory.	SessionStats	15m
ActiveCount	The total number of concurrently active sessions. A session is active if Liberty is processing a request that uses that session.	SessionStats	15m
InvalidatedCount	The total number of sessions that are invalidated.	SessionStats	15m

• Liberty Session Statistics Object Name: WebSphere:type=SessionStats,Name=*

Thread Pools

The Thread Pool managed bean provides web container thread pool information. It is available when the monitor-1.0 feature is enabled. ThreadPoolStats is used to monitor the active threads usage in relation to the pool size. Liberty uses an auto-tuning algorithm to find the sweet spot for how many threads the server needs. Liberty is always playing around and adjusting the number of threads in the pool in-between and defined bounds for the coreThreads and maxThreads. In Liberty the threadpool size is autosized by Liberty itself. The ActiveThreads attribute should be used for alerts.

Key Attributes	Description	MBean	Frequency
PoolName	Only supports Default Executor thread pool.	ThreadPoolStats	15m
PoolSize	Threads in the pool which represents the pool size.	ThreadPoolStats	15m
ActiveThreads	Active threads which are serving requests.	ThreadPoolStats	15m

• Liberty Thread Pools Object Name: WebSphere:type=ThreadPoolStats,name=DefaultExecutor

CLM Managed Beans

As part of improving the CLM serviceability, we added several classes of managed bean to help give administrators a complete picture of what is happening in the system. To leverage these managed beans, it is helpful to understand the basic architecture and the serviceability strategy that we used to approach the problem.

Below (figure 1) is a high level diagram of the CLM architecture. Several of the applications share a common development framework, called the Jazz Application Foundation SDK. The managed beans that have been built have been built as part of this SDK so all applications that are built on top of it get these managed beans by default. For parts of the CLM suite that are not built on this framework, they have to build their managed beans from scratch.

figure 1. The High Level CLM Architecture Overview

As the diagram shows, several applications (white boxes) share a common framework and these applications have managed beans. JTS, RTC, RQM, RDNG, RDM, and GC all have managed beans.

Now that you understand what applications have managed beans, consider the Service Invocation Architecture described in figure 2 and the recommended attributes that should be considered when monitoring the overall application health.

figure 2. Jazz Service Invocation Architecture

In addition to those attributes that we recommend monitoring, there are optional attributes that you might want to consider as well, which we show you in figure 3.

figure 3. Jazz Service Invocation Architecture - Optional Managed Beans

Enabling CLM Managed Beans

The managed beans are not enabled by default out of the box. You need to consider your monitoring strategy and only turn on those managed beans you will actually consume. These managed beans are enabled through the advanced properties admin UI. To turn them on, you would locate the background task in the table below and enable it by setting the enable property to true. It is recommended that you take the default values because these have been carefully considered and tuned for optimal efficiency.

https://<< host:port >>/<< context root >>/admin#action=com.ibm.team.repository.admin.configureAdvanced

Table of Managed Beans

MBean Name	Category	Object Name	Background Task	Description	Frequency
Distributed Data Microservice – Elapsed time (in ms)	Cluster Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, Distributed Persistence Layer,facet=Elapsed time (in ms),counterName=*	ClusterMetricsTask	This facet reports the times it takes for the data transfers to and from the persistence layer.	15m
Active Services	Performance Metrics	com.ibm.team.foundation.activeservices:name=<< contextRoot>>, type=activeServicesMetrics, serviceName=*	MetricsCollectorTask	This is all the active services currently running in the server. Each service provides information like service name, requested user, start time and duration, and start time. This is useful to understand the standard patterns of low level service activity in a production system. Helps to understand the unique set of users currently working in the system.	15m
Active Services Summary	Performance Metrics	com.ibm.team.foundation.activeservices:name=<< contextRoot>>, type=activeServicesSummaryMetrics	HighFrequencyMetricsNodeScopedTask	This is a summary of the total count of active services running in the system. This provides information like total count, CPU ratio and services that have exceeded duration thresholds. This is useful to understand the active services that are long running. Helps also to understand if the system specifications are adequate to meet the user load.	15m
Contributor Information	Usage Metrics	com.ibm.team.foundation.contributors:name=<< contextRoot>>, type=contributorMetrics	CommonMetricsCollectorTask	This publishes the number of active and archived users in the repository. This is useful to understand the active registered users.	60m
Diagnostics	Server Health Metrics	com.ibm.team.foundation.diagnostic:name=<< contextRoot>>, type=diagnosticMetrics, testId=*	DiagnosticsMetricsTask	This provides the results of the server diagnostics which by default runs every hour. This is useful to track the status of the periodic execution of server diagnostics.	70m
Log Events	Server Health Metrics	com.ibm.team.foundation.logevents:name=<< contextRoot>>, type=logEventDetailsMetrics, errorNameAndId=*	MetricsCollectorTask	This provides all the errors and warnings from the log files and for each log entry provides additional contextual information like userd id, active configuration, servlet request URL etc. This is useful to understand error log entries occurring in the system when other aspects of the system are misbehaving. This provides a maximum of 1000 entries during the collection interval.	15m
Full Text Index Information	Performance Metrics	com.ibm.team.foundation.fulltextindexing:name=<< contextRoot>>, type=richTextIndexDataMetrics	FullTextIndexDataCollectorTask	This provides the index size and index location information for the full text lucene index used by RTC and RQM. This is useful to track the size of the lucene index.	60m
JFS Index Information	Performance Metrics	com.ibm.team.foundation.jfsindexing:name=<< contextRoot>>, type=jfsIndexDataMetrics, indexname=*	IndexDataCollectorTask	This provides the index size and index queue information for the rdf and text index used by DNG and DM. Index information is provided for RDF Live, RDF History, Text Live and Text History indices. This is useful to track the size of the index and indirectly help with determining the optimal RAM and JVM Heap memory for the system.	60m
Item Count Details	Performance Metrics	com.ibm.team.foundation.itemcounts:name=<< contextRoot>>, type=itemCountMetrics,type Name=*	ItemCountMetricsCollectorTa sk	This provides information about each type of item in the repository and their counts in terms of number of states and the overall size of these items in relation to the total size. This is useful to understand the data growth in the system and also the breakdown between the different types of items. Sometimes items like attachments or build results may be growing at an alarming rate and tracking this metric can explain the reason for this growth. Added to this, increase in DB size during a period can also be explained by the items that were added during this period.	1 week
Repotools Verify Information	Server Health Metrics	com.ibm.team.foundation.datavalidation:name=<< contextRoot>>, type=onlineVerifyMetrics, componentId=*	OnlineVerifyMetricsTask	This provides the results of the repository verifiers, which are used in the verify repotools infrastructure. This is useful to keep an eye on the data integrity of the production database. This is useful to track the status of the periodic execution of data verification rules against the repository.	1 week
Project Area Information	Usage Metrics	com.ibm.team.foundation.projectarea:name=<< contextRoot>>, type=projectMetrics, projectNameAndId=*	ProjectMetricsCollectorTask	This publishes the number of contributor, team, development lines, work items and attachments for each project area in the repository. Additionally it indicates if the project is archived or not. You can monitor these and also setup alerts if the usage patterns are not within normal parameters. In future it will contain an attribute for the total size of the project area in the repository. This will help determine if the project warrants its own server and can be a candidate for server split. It also provides if the project area has be opted in and provides configuration management metrics like number of component, streams, baselines etc.	1 week
Project Area Summary Information	Usage Metrics	com.ibm.team.foundation.projectarea:name=<< contextRoot>>, type=projectSummaryMetrics	CommonMetricsCollectorTask	This publishes the number of projects in the repository and if they are archived or not.	60m
Expensive Scenario Details	Performance Metrics	com.ibm.team.foundation.scenarios:name=<< contextRoot>>, type=expensiveScenarioDetailsMetrics, scenarioNameAndId=*	MetricsCollectorTask	This will publish details about the active and completed resource intensive scenarios in the system. This is useful to understand how the resource intensive scenarios are performing and understand what are the active scenarios at any given point in time. It also gives details about the user who requested the scenario.	15m
Server Information	Server Health Metrics	com.ibm.team.foundation.server:name=<< contextRoot>>, type=serverMetrics	MetricsCollectorTask	This publishes the server health information including memory usage, DB ping time and status on services and DB connections. This is useful to understand how the server is performing. Most important attribute is the dbPingTime. If the latency between server and DB gets worse it will impact the almost every use case in the product.	15m
SQL Activity	Performance Metrics	com.ibm.team.foundation.sqlactivity:name=<< contextRoot>>, type=sqlActivityMetrics, id=*	SQLActivityMetricsTask	This provides the SQL activity during the specified interval as a MBean. This is useful to understand the standard patterns of SQL activity in a production system. This is useful to track the counts and average response times for many SQL queries. Helps to understand the high runners and optimize them. Also helps to drive data partitioning decisions and preserve the query response time.	60m
SQL Activity Summary	Performance Metrics	com.ibm.team.foundation.sqlactivity:name=<< contextRoot>>, type=sqlActivitySummaryMetrics, sqlStmtType=*	SQLActivityMetricsTask	This provides the summary SQL activity during the specified interval as a MBean. This is useful to understand the standard patterns of SQL activity in a production system. This is useful to track the counts and average response times for many SQL queries by type. Helps to understand the high runners and optimize them. Also helps to drive data partitioning decisions and preserve the query response time.	60m
Work Item Information	Usage Metrics	com.ibm.team.foundation.projectarea:name=<< contextRoot>>, type=projectWorkItemMetrics, typeNameAndProjectNameAndId=*	ProjectMetricsCollectorTask	This provides the type of workitem and the total count of this type of work items for each project area.	1 week
Cluster Member Information	Cluster Metrics	com.ibm.team.foundation.clustermembers:name=<< contextRoot>>, type=clusterMemberDataMetrics, nodeId=*	CommonMetricsCollectorTask	This publishes the basic node information for each node in the cluster and also the node state.	60m
MQTT Endpoint Metrics	Cluster Metrics	com.ibm.team.foundation.cluster.mqtt:name=<< contextRoot>>, type=mqttEndpointStatistics	ClusterMetricsTask	This provides information about configured end points with the MessageSight MQTT broker. It has details like total connections, bytes read or written, messages sent/received/lost etc.	15m
MQTT Memory Metrics	Cluster Metrics	com.ibm.team.foundation.cluster.mqtt:name=<< contextRoot>>, type=mqttMemorytatistics	ClusterMetricsTask	This provides information about the memory characteristics of the MessageSight MQTT broker machine. It includes details like free memory, message payloads etc.	15m
MQTT Store Metrics	Cluster Metrics	com.ibm.team.foundation.cluster.mqtt:name=<< contextRoot>>, type=mqttStoretatistics	ClusterMetricsTask	This provides information about the disk and pool characteristics of the MessageSight MQTT broker machine.	15m
MQTT Topic Metrics	Cluster Metrics	com.ibm.team.foundation.cluster.mqtt:name=<< contextRoot>>, type=mqttTopictatistics	ClusterMetricsTask	This provides information about the topics in the MessageSight MQTT broker machine. It includes details like subscriptions, published messages etc.	15m
Asynchronous Tasks Elapsed Time	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=asynchronoustasks,facet=elapsed time in seconds, counterName=*	MetricsCollectorTask	This is useful to track the average response time for background tasks and help with tuning the frequency of these and also monitor the degradation in their response time.	15m
Asynchronous Tasks Queued Count	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=asynchronoustasks, facet=queuedcount, counterName=*	MetricsCollectorTask	This is useful to track the backlog of the background tasks being queued up.	15m
JDBC Connection Pool Active Connections	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=resourceusage, facet=activeconnections, counterName= JDBC connection pool	MetricsCollectorTask	This is useful to understand the sizing for the JDBC pools and if these pool sizes are correctly set for the current concurrency level of the system. If the size is small then higher concurrency will result in operations waiting and is the size is too big then system resources are consumed even though the load does not exist (Article). The different facets are active connections, usage percentage, queue length and wait time.	15m
JDBC Connection Pool Queue Length	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=resourceusage, facet=queuelength, counterName=JDBC connection pool	MetricsCollectorTask	This is useful to understand the sizing for the JDBC pools and if these pool sizes are correctly set for the current concurrency level of the system. This facet highlights the size of the queue of pending connection requests.	15m
JDBC Connection Pool Usage Percentage	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=resourceusage, facet=usagepercentage, counterName=JDBC connection pool	MetricsCollectorTask	This is useful to understand the sizing for the JDBC pools and if these pool sizes are correctly set for the current concurrency level of the system. If the size is small then higher concurrency will result in operations waiting and is the size is too big then system resources are consumed even though the load does not exist (Article). The different facets are active connections, usage percentage, queue length and wait time.	15m
JDBC Connection Pool Wait Time in milliseconds	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=resourceusage, facet=wait time in ms, counterName=JDBC connection pool	MetricsCollectorTask	This is useful to understand the sizing for the JDBC pools and if these pool sizes are correctly set for the current concurrency level of the system. This facet highlights the size of the queue of pending connection requests.	15m
RDB Mediator Connection Pool Active Connections	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=resourceusage, facet=active connections, counterName=RDB mediator pool	MetricsCollectorTask	This is useful to understand the sizing for the RDB mediator pools and if these pool sizes are correctly set for the current concurrency level of the system. If the size is small then higher concurrency will result in operations waiting and is the size is too big then system resources are consumed even though the load does not exist (Article). The different facets are active connections, usage percentage, queue length and wait time.	15m
RDB Mediator Connection Pool Queue Length	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=resourceusage, facet=queue length,counterName=RDB mediator pool	MetricsCollectorTask	This is useful to understand the sizing for the RDB mediator pools and if these pool sizes are correctly set for the current concurrency level of the system. This facet highlights the size of the queue of pending connection requests.	15m
RDB Mediator Pool Usage Percentage	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=resource usage,facet=usage percentage,counterName=RDB mediator pool	MetricsCollectorTask	This is useful to understand the sizing for the RDB mediator pools and if these pool sizes are correctly set for the current concurrency level of the system. If the size is small then higher concurrency will result in operations waiting and is the size is too big then system resources are consumed even though the load does not exist (Article). The different facets are active connections, usage percentage, queue length and wait time.	15m
RDB Mediator Pool Wait Time in milliseconds	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=resource usage,facet=wait time in ms,counterName=RDB mediator pool	MetricsCollectorTask	This is useful to understand the sizing for the RDB mediator pools and if these pool sizes are correctly set for the current concurrency level of the system. This facet highlights the size of the queue of pending connection requests.	15m
Local configuration management cache statistics – Cache hit ratio	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=local config mgmt cache statistics,facet=Cache hit ratio as a percentage,counterName=*	MetricsCollectorTask	This is useful to understand how the caches are performing. In a production environment the hit ratio of the caches should be greater than 95% (Blog). Other facets are Entry added to cache, Entry removed from cache, Entry found in cache, Entry not found in cache, Entry replaced in cache and Entry garbage collected from cache.	15m
Local configuration management cache statistics – Entry added to cache	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=local config mgmt cache statistics,facet=Entry added to cache,counterName=*	MetricsCollectorTask	This is useful to understand how the caches are performing. In a production environment the hit ratio of the caches should be greater than 95% (Blog). This facet highlights the entries added to the cache	15m
Local configuration management cache statistics – Entry found in cache	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=local config mgmt cache statistics,facet=Entry found in cache,counterName=*	MetricsCollectorTask	This is useful to understand how the caches are performing. In a production environment the hit ratio of the caches should be greater than 95% (Blog). This facet highlights the entries found in cache	15m
Local configuration management cache statistics – Entry not found in cache	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=local config mgmt cache statistics,facet=Entry not found in cache,counterName=*	MetricsCollectorTask	This is useful to understand how the caches are performing. In a production environment the hit ratio of the caches should be greater than 95% (Blog). This facet highlights the entries not found in cache	15m
Local configuration management cache statistics – Entry removed from cache	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=local config mgmt cache statistics,facet=Entry removed from cache,counterName=*	MetricsCollectorTask	This is useful to understand how the caches are performing. In a production environment the hit ratio of the caches should be greater than 95% (Blog). This facet highlights the entries removed from cache	15m
Local configuration management cache statistics – Entry replaced in cache	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=local config mgmt cache statistics,facet=Entry replaced in cache,counterName=*	MetricsCollectorTask	This is useful to understand how the caches are performing. In a production environment the hit ratio of the caches should be greater than 95% (Blog). This facet highlights the entries replaced in cache	15m
Local configuration management cache statistics – Entry garbage collected from cache	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=local config mgmt cache statistics,facet=Entry garbage collected from cache,counterName=*	MetricsCollectorTask	This is useful to understand how the caches are performing. In a production environment the hit ratio of the caches should be greater than 95% (Blog). This facet highlights the entries garbage collected from cache.	15m
Local configuration management cache statistics – Time for computing a value in ms	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=local config mgmt cache statistics,facet=Time for computing a value in ms,counterName=*	MetricsCollectorTask	This is useful to understand how the caches are performing. In a production environment the hit ratio of the caches should be greater than 95% (Blog). This facet highlights the average time to compute a value in ms.	15m
Local configuration management service statistics – Elapsed time in milliseconds	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=local config mgmt service,facet=Elapsed time (in ms),counterName=*	MetricsCollectorTask	This helps with monitoring the average execution time of the different local configuration management service API for DNG and DM. This includes but not limited to operations like creating a changeset, creating a stream, creating a baseline, committing a changeset etc.	15m
Local configuration management service statistics – Creation time in milliseconds	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=Configuration aware functionality,facet=Creation time (ms),counterName=*	MetricsCollectorTask	This helps with monitoring the average execution time of some of the advanced config mgmt. operations like skew detection on streams and baselines.	15m
Local configuration management service statistics – Rows created in in a new stream	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=Configuration aware functionality,facet=Rows created,counterName=*	MetricsCollectorTask	This helps with monitoring the number of rows created when a steam create operation is executed.	15m
Transaction cache statistics – Number of hits	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=Item Cache Summary,facet=hits,counter Name=*	MetricsCollectorTask	This provides the transaction cache(s) operation metrics. This provides counts for the following operations on ITEM currents and ITEM state caches. The facets are added, misses, invalidated, hits and autoupdated. This is useful to understand how the caches are performing. In a production environment the hit ratio of the caches should be greater than 95% (Blog).	15m
Transaction cache statistics – Number of misses	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=Item Cache Summary,facet=misses,counterName=*	MetricsCollectorTask	This provides the transaction cache(s) operation metrics. This provides counts for the following operations on ITEM currents and ITEM state caches. This facet highlights the number of misses from the cache.	15m
Transaction cache statistics – Number of invalidations	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=Item Cache Summary,facet=invalidated, counterName=*	MetricsCollectorTask	This provides the transaction cache(s) operation metrics. This provides counts for the following operations on ITEM currents and ITEM state caches. This facet highlights the number of invalidations from the cache.	15m
Transaction cache statistics – Number of entries added	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=Item Cache Summary,facet=added,counterName=*	MetricsCollectorTask	This provides the transaction cache(s) operation metrics. This provides counts for the following operations on ITEM currents and ITEM state caches. This facet highlights the number of entries added to the cache.	15m
Transaction cache statistics – Number of entries auto updated	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=Item Cache Summary,facet=autoUpdated ,counterName=*	MetricsCollectorTask	This provides the transaction cache(s) operation metrics. This provides counts for the following operations on ITEM currents and ITEM state caches. This facet highlights the number of entires that were updated in the cache.	15m
Resource Intensive Scenarios – Elapsed time in milliseconds	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=scenarios,facet=elapsed time in millisecs,counterName=*	MetricsCollectorTask	This provides the counts and average response time for each of the resource intensive scenarios in the system (Deployment Wiki). This is useful to understand how the resource intensive scenarios are performing and track any degradation in their response times.	15m
Resource Intensive Scenarios – Summary Elapsed time in milliseconds	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=scenarios,facet=elapsed time in millisecs,counterNameAndId =summary_*	MetricsCollectorTask	This provides the counts and average response time for all the resource intensive scenarios in the system (Deployment Wiki) during the collection interval. This is useful to understand how the resource intensive scenarios are performing and track any degradation in their response times.	15m
Web Service Statistics – Elapsed time in seconds	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=web service,facet=elapsed time in secs,counterName=*	MetricsCollectorTask	This is useful to track the average response time for web services and watch for degradations. Added to this the other facets are bytes sent to client and bytes received from client. These are useful to track the average request pay load and response pay load for web services and watch for large payloads that may affect the network I/O.	15m
Web Service Statistics – Bytes sent to client	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=web service,facet=bytes sent to client,counterName=*	MetricsCollectorTask	These are useful to track the average request pay load and response pay load for web services and watch for large payloads that may affect the network I/O.	15m
Web Service Statistics – Bytes received from client	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=web service,facet=bytes received from client,counterName=*	MetricsCollectorTask	These are useful to track the average request pay load and response pay load for web services and watch for large payloads that may affect the network I/O.	15m
Web Services Statistics Summary Over Collection Intervals	Performance Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=webServicesSummary Metrics,facet=*,component=*	MetricsCollectorTask	This bean captures the summary information over collection intervals. The summary includes total count, average over interval, max over interval, transaction rate, the total value over interval etc. The summary bean is create by facet and within each facet you can get a summary by component.	15m
Floating license consumption statistics – Concurrent use	Usage Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=Floating license concurrent use,facet=All servers,counterName=*	LicenseMetricsCollectorTask	This facet captures the floating license consumption from the servers.	15m
Floating license consumption statistics – Concurrent use	Usage Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=Floating license concurrent use,facet=All servers,counterName=*	LicenseMetricsCollectorTask	This facet captures the floating license consumption from the servers.	15m
Floating license consumption statistics – License checkout time	Usage Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=Floating license checkout time,facet=All servers,counterName=*	LicenseMetricsCollectorTask	This facet captures the floating license checkout time from the servers.	15m
Floating license consumption statistics – License Denials	Usage Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=Floating license denials,facet=All servers,counterName=*	LicenseMetricsCollectorTask	This facet captures the floating license denials from the servers.	15m
Token License consumption statistics – Concurrent use	Usage Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group= License token use,facet=All providers,counterName=*	LicenseMetricsCollectorTask	This facet captures the token license consumption from the servers.	15m
Token License consumption statistics – License Denials	Usage Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group= License token provider denials,facet=All providers,counterName=*	LicenseMetricsCollectorTask	This facet captures the token license denials from the providers.	15m
Compatible Client Login Details – Number of logins	Usage Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group= Compatible client logins,facet=Number of logins,counterName=*	LicenseMetricsCollectorTask	This facet captures the number of login attempts from different versions of the client. This MBean is only available in RTC.	15m
Jazz MQTT Service – Messages Received Count	Cluster Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=MqttService,facet=Count,counterName=*	ClusterMetricsTask	This facet captures the count of messages received by the Jazz MQTT service.	15m
Jazz MQTT Service – Messages Received Frequency (msgs/sec)	Cluster Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=MqttService,facet=Frequency (msg/s),counterName=*	ClusterMetricsTask	This facet captures the frequency of messages received by the Jazz MQTT service.	15m
Jazz MQTT Service – Messages Received Reset Counter	Cluster Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=MqttService,facet=Reset,counterName=*	ClusterMetricsTask	This facet captures the count of reset messages received by the Jazz MQTT service.	15m
Jazz MQTT Service – Messages Sent Count	Cluster Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=MqttService,facet=Count,counterName=*	ClusterMetricsTask	This facet captures the count of messages sent by the Jazz MQTT service.	15m
Jazz MQTT Service – Messages Sent Frequency (msgs/sec)	Cluster Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=MqttService,facet=Frequency (msg/s),counterName=*	ClusterMetricsTask	This facet captures the frequency of messages sent by the Jazz MQTT service.	15m
Jazz MQTT Service – Messages Sent Reset Counter	Cluster Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=MqttService,facet=Reset,counterName=*	ClusterMetricsTask	This facet captures the count of reset messages sent by the Jazz MQTT service.	15m
Jazz MQTT Service – Messages Sent Queued Counter	Cluster Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=MqttService,facet=Queued,counterName=*	ClusterMetricsTask	This facet captures the count of queued messages to be sent by the Jazz MQTT service.	15m
Jazz MQTT Service – Messages Received Queue Exhausted Counter	Cluster Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=MqttService,facet=Queue Exhausted,counterName=*	ClusterMetricsTask	This facet captures the count of times when the thread pool size to process received messages has maxed out and the queue to hold excess is full.	15m
Jazz MQTT Service – Published Messages Lost Count	Cluster Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=MqttService Stats,facet=Send Success rate,counterName=*	ClusterMetricsTask	This facet captures the count of published messages that got lost and did not make it to the broker.	15m
Jazz MQTT Service – Message Processing Time	Cluster Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=MqttService Stats,facet=Elapsed time in seconds,counterName=*	ClusterMetricsTask	This facet captures the average processing time for handling messages received by the Jazz MQTT service.	15m
Jazz MQTT Service – Message Sent Result - Success	Cluster Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=MqttService Stats,facet=Send Success rate,counterName=*	ClusterMetricsTask	This facet captures the count of published messages that were successfully delivered to the broker.	15m
Jazz MQTT Service – Message Sent Result - Failure	Cluster Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=MqttService Stats,facet=Send Success rate,counterName=*	ClusterMetricsTask	This facet captures the count of published messages that failed to be delivered to the broker.	15m
Jazz MQTT Service – Message processed on main thread	Cluster Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=MqttService Stats,facet=Send Success rate,counterName=*	ClusterMetricsTask	This facet captures the count of received messages that were processed on the main thread in the Jazz MQTT Service as the service was being deactivated and also when the threadpool and the queue to use for holding tasks before they are executed were exhausted.	15m
Jazz MQTT Service – Received Messages - Queue Size	Cluster Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=MqttService Stats,facet=Arrived Messages Processing,counterName=*	ClusterMetricsTask	This facet captures the size of the queue in MQTT service used to hold incoming messages before a background thread becomes available to process them.	15m
Jazz MQTT Service – Received Messages – thread pool size	Cluster Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=MqttService Stats,facet=Arrived Messages Processing,counterName=*	ClusterMetricsTask	This facet captures the size of the thread pool used to handle the incoming messages by the Jazz MQTT service. The excess messages will be held in queue.	15m
Jazz MQTT Service – Failed connections to broker	Cluster Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=MqttService Client Stats,facet=Failed to connect,counterName=*	ClusterMetricsTask	This facet captures the count of failed connections to the broker from the Jazz MQTT service.	15m
Jazz MQTT Service – Lost connections to broker	Cluster Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=MqttService Client Stats,facet=Connection lost,counterName=*	ClusterMetricsTask	This facet captures the count of lost connections to the broker from the Jazz MQTT service.	15m
Distributed Data Microservice – Key Size	Cluster Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=Distributed Maps and Values Sizes,facet=Key Size,counterName=*	ClusterMetricsTask	Facet reports the size of the object used as a map Key.	15m
Distributed Data Microservice – Added Value Size	Cluster Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=Distributed Maps and Values Sizes,facet=Added Value Size,counterName=*	ClusterMetricsTask	This facet reports the size of the data help in the map.	15m
Distributed Data Microservice – Number of Elements in Map	Cluster Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=Distributed Maps and Values Sizes,facet=Number of Elements in Map,counterName=*	ClusterMetricsTask	This facet reports the number of elements in the map.	15m
Distributed Data Microservice – Bytes transferred (in kb)	Cluster Metrics	com.ibm.team.foundation.counters:name=<< contextRoot>>, type=counterMetrics, group=Distributed Persistence Layer,facet=Bytes transferred (in kb) ,counterName=*	ClusterMetricsTask	This facet reports the size of data (in KB) transferred between persistence layer and distributed maps in memory.	15m

Related topics:

• JVM MBeans
• WebSphere Liberty MBeans

External links:

• IBM

Additional contributors: -- RichardWatts - 2018-03-20