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r2 - 2018-07-12 - 03:46:29 - RichardWattsYou are here: TWiki >  Deployment Web > DeploymentMonitoring > CLM605MXBeans

CLM 6.0.5 Monitoring Managed Beans Referencetodo.png

Authors: Vishwanath Ramaswamy, Vaughn Rokosz, Richard Watts
Build basis: CLM 6.0.5

This document outlines the managed beans available in the CLM 6.0.5 product suite.

Managed Beans

Common Beans

LQE 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

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

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