SlideShare a Scribd company logo
1 of 67
Download to read offline
© 2009 IBM
Corporation
IBM Integration Bus V10 Performance
How to analyse your system to optimise performance and throughput
Martin Ross - martin.ross@uk.ibm.com
© 2015 IBM
Corporation
14 July 2015
Overview
 The purpose of this presentation is to demonstrate how to find the cause of poor performance for an
IBM Integration Bus node (broker) for two different types of problem.
 The examples are obtained on a Windows system but the principles of investigation and problem
determination apply equally on all platforms. The system level tools will differ though.
© 2015 IBM
Corporation
14 July 2015
Agenda
 Introduction
 Tools
 Techniques
 Demonstration
© 2015 IBM
Corporation
14 July 2015
What are the main performance costs in message flows?
ZYX…CBA
Parsing Tree Navigation
Root.Body.Level1.Level2.
Level3.Description.Line[1];
Tree Copying
Set OutputRoot = InputRoot;
Resource Access Processing Logic
© 2015 IBM
Corporation
14 July 2015
Integration Bus Processes
Integration Node
Integration Server
Application Application
Message
flows
Message
flows
Libraries Libraries
Integration Server [n]
Application Application
Message
flows
Message
flows
Libraries Libraries
 Bipservice
– Lightweight and resilient process that starts
and monitors the bipbroker process
– If the bipbroker process fails, bipservice will
restart it
 Bipbroker
– A more substantial process. Contains the
deployment manager and administrative
agent. All commands, toolkit connections
and WebUI go through this process.
– Responsible for starting and monitoring the
biphttplistener, bipMQTT and
DataFlowEngine processes.
– If any process fail, bipbroker will restart
them.
 BipMQTT
– Handles MQTT events
 Biphttplistener
– Runs the brokerwide HTTP connector for
HTTP and SOAP nodes.
 DataFlowEngine
– Runtime engine for all deployed resources.
© 2015 IBM
Corporation
14 July 2015
Which resources and how much
 Understand typical resource utilisation – need to understand if resource utilisation is higher than
expected or running as normal...
 In busy times expect to use what is needed (!)
– Exactly what will depend on the configuration and the applications
– Typical to use CPU and memory plus I/O to some level
 In quiet times Message Broker and MQ processes
– Should use very little CPU
– Should use very little I/O capacity
– Will retain memory
 Some memory sizes whilst running the Coordinated Request Reply sample
– Bipservice 3.7 MB
– Bipbroker 112 MB
– Biphttplistener 35 MB
– DataFlowEngine 154 MB
• Can use from ~100 MB to GigaBytes depending on number of flows, complexity of the
message flow, the size of the messages
 MQ processes
– Expect it to be less than IBM Integration Bus (76 MB for a simple queue manager)
– Will depend on number of open queues, channels, queue buffer sizes etc.
© 2015 IBM
Corporation
14 July 2015
Tools that are needed
 Monitoring tools
– At the operating system level to observe
• System resource usage – CPU, memory, I/O activity
• Heaviest resource users
– At the component level to observe
• Behaviour within the particular component (MQ / IBM Integration Bus)
– Both types of tools are needed
• They have different views of the world
• They are complimentary
 Driving tools
– Needed to generate a continuous workload
• Important to assess performance after warm-up during sustained activity
© 2015 IBM
Corporation
14 July 2015
UNIX tools
 Vmstat
 Iostat
 Nmon
 filemon
System Configuration: lcpu=64 mem=8192MB
kthr memory page faults cpu
----- ----------- ------------------------ ------------ -----------
r b avm fre re pi po fr sr cy in sy cs us sy id wa
1 0 1977672 25823 0 0 0 0 0 0 3 958 696 4 0 96 0
1 0 1977838 25719 0 2 0 98 100 0 29 2941 2250 4 0 96 0
1 0 1977685 25872 0 0 0 0 0 0 2 636 483 4 0 96 0
System configuration: lcpu=64 drives=5 paths=6 vdisks=2
tty: tin tout avg-cpu: % user % sys % idle % iowait
0.0 29.5 3.6 0.1 96.2 0.0
Disks: % tm_act Kbps tps Kb_read Kb_wrtn
hdisk3 0.0 0.0 0.0 0 0
hdisk2 0.0 0.0 0.0 0 0
hdisk0 0.0 4.0 1.0 8 0
hdisk1 0.0 0.0 0.0 0 0
cd0 0.0 0.0 0.0 0 0
© 2015 IBM
Corporation
14 July 2015
Windows tools – Process Explorer
 Watch system activity in detail on Windows
 Watch
– CPU usage
– Commit charge
– I/O activity
– Physical memory history
– Summary information
– Individual processes
 Download from https://technet.microsoft.com/en-us/sysinternals/bb896653.aspx
© 2015 IBM
Corporation
14 July 2015
Process Explorer
 DataFlowEngine.exe:
– This is the Integration
Server
 amqzlaa0.exe
– This is the MQ agent for
LOCAL connections
(including the broker)
 amqrmppa.exe
– This is the MQ agent for
CLIENT connections
 Can quickly see system is busy
 Customise by selecting columns of choice
© 2015 IBM
Corporation
14 July 2015
Process Explorer – Task Information
© 2015 IBM
Corporation
14 July 2015
Find Integration Server name from PID
mqsilist DEMO -d2
-----------------------------------
BIP1286I: Integration server 'default' on integration node 'DEMO' is running.
Number of message flows that are enabled to run: '4'.
Number of applications that are enabled to run: '2'.
Process ID: '8248'
UUID: 'e1306ebc-3c3a-43c2-b18a-bbdb99e07d5c'
Short description: ''
Long description: ''
BIP8071I: Successful command completion.-----------------------------------
BIP1286I: Integration server 'default' on integration node 'DEMO' is running.
Number of message flows that are enabled to run: '4'.
Number of applications that are enabled to run: '2'.
Process ID: '8248'
UUID: 'e1306ebc-3c3a-43c2-b18a-bbdb99e07d5c'
Short description: ''
Long description: ''
BIP8071I: Successful command completion.
-bash-4.1$ ps -ef | grep DataFlowEngine
mqm 4331 4302 0 13:12 pts/0 00:00:00 grep DataFlowEngine
mqm 28788 28701 99 12:57 ? 00:41:56 DataFlowEngine CSIM d2cd939a-a7a3-46ce-8168-
b89c77744511 default
© 2015 IBM
Corporation
14 July 2015
Key tools at the component level
 Integration Bus
– User trace
– Trace nodes
– Activity Log
– WebUI
• Accounting & Statistics: Compare flow statistics at the node (broker), server (execution group),
container (application or library) or at an individual message flow level
• Resource Statistics: View resource use at the execution group level
 MQ Explorer
 Java Healthcenter
© 2015 IBM
Corporation
14 July 2015
Statistics scope
Node (broker)
Server (execution group)
Node
Message Flow
Thread
Message Model
Terminals
Resource
Statistics
Accounting &
Statistics
© 2015 IBM
Corporation
14 July 2015
Accounting & Statistics
 Dynamic reporting of message flow
usage for
• Problem determination
• Chargeback
• Profiling
 Data at two levels
1. Universal (CPU cost, IO, elapsed time)
2. Broker specific (messages, commits,
backouts)
 A Choice of intervals
• Short or snapshot
• Long or archive
 Attach a label to the
information
– AccountingOrigin to
collect data to identify
and collate this
information according to
the specific origin of a
message, even in
consolidated flows. Choice of destination
1. Trace
2. PubSub
3. SMF (z/OS only)
© 2015 IBM
Corporation
14 July 2015
Subscribing to Accounting & Statistics
 Publish/Subscribe data is published on the topic
$SYS/Broker/brokerName/StatisticsAccounting/recordType/executionGroupLabel/messageFlowLabel
A subscription for $SYS/Broker/+/StatisticsAccounting/+ receives all statistics for all brokers
Notes: The following three characters have a special meaning:
– The topic level separator "/"
– The multilevel wildcard "#"
– The single-level wildcard "+"
© 2015 IBM
Corporation
14 July 2015
Resource Statistics
 Dynamic reporting of the performance and operating details of
resources used by execution groups
• Problem determination
• Profiling
 Supported resources
1. CICS
2. CORBA
3. FTEAgenet
4. JDBCConnectionPools
5. JVM
6. ODBC
7. SOAPInput
8. Security
9. Outbound Sockets
 Data
• XML messages
distributed using
PubSub
• Access as raw data
or view in WebUI
 Regular reporting
• Data published approximately every 20 seconds
© 2015 IBM
Corporation
14 July 2015
Subscribing to Resource Statistics
 Data is published on the topic
$SYS/Broker/brokerName/ResourceStatistics/executionGroupLabel
A subscription for $SYS/Broker/+/ResourceStatistics/+ receives all statistics for all brokers
Notes: The following three characters have a special meaning:
– The topic level separator "/"
– The multilevel wildcard "#"
– The single-level wildcard "+"
© 2015 IBM
Corporation
14 July 2015
WebUI – Accounting & Statistics
 Using the WebUI in IBM Integration
Bus v10:
– Control statistics at all levels
– Easily view and compare flows,
helping to understand which are
processing the most messages or
have the highest elapsed time
– Easily view and compare nodes,
helping to understand which have
the highest CPU or elapsed times
– View all statistics metrics
available for each flow
– View historical flow data
© 2015 IBM
Corporation
14 July 2015
WebUI – Resource Statistics
 View resource statistics for resource managers in IIB such as:
– JVM
– ODBC
– JDBC
– parsers, etc.
© 2015 IBM
Corporation
14 July 2015
MQ Explorer
© 2015 IBM
Corporation
14 July 2015
IBM Support Assistant and Java Health Centre
 Java Health Centre is provided as part of the IBM Support Assistant
– Offers very low overhead monitoring tool
– Runs along side an IBM Java application
 Get visibility, monitoring and profiling in the following application areas:
– Performance
• Java method profiling
• Lock analysis
• Garbage collection
– Memory
– System
– Java Class
– File input and
– Object
 Enable the application JVM prior to use
– IBM_JAVA_OPTIONS=-Xhealthcenter
© 2015 IBM
Corporation
14 July 2015
Demonstration of analysing performance issues
 Identify problems in two message flows using
– Process Explorer
– WebUI Statistics
– MQ Explorer
– Java Healthcenter
Java Compute TransformCoordinated Request Reply
© 2015 IBM
Corporation
14 July 2015
Demonstration 1
Analysing a performance problem in the Coordinated Request Reply
Scenario
© 2015 IBM
Corporation
14 July 2015
Coordinated Request Reply message flows
 Consists of three message flows
– Request
• Converts incoming message from XML to CWF
• Saves the incoming message in a queue for subsequent reply processing
• Writes a message for the back end reply message flow
– BackendReplyApp
• Sets the completion time in the message
• Writes a reply message
– Reply
• Reads the message from the back end message flow
• Retrieves the original message saved by the request message flow
• Writes an output message
© 2015 IBM
Corporation
14 July 2015
Coordinated Request Reply queues
 The queues
– Request
– BackendReplyApp
– Reply
CSIM_SERVER_IN_Q
GET_REPTO_STORE
GET_REPTO_STORE
GET_BACKEND_REPGET_BACKEND_REQ
GET_BACKEND_REQ
GET_BACKEND_REP CSIM_COMMON_REPLY_Q
© 2015 IBM
Corporation
14 July 2015
Run and investigate
Steps
1. Ensure all components are started and the applications works as expected
- Message flows, databases, external applications etc.
2. Start a load generator [JMSPerfharness in this case]
3. Look at activity
- Is processing happening at the expected rate?
- Is CPU usage as expected?
- Is memory usage as expected?
4. If things do not seem as expected
- Look for build up of messages
- Poor service times
5. Enable and view statistics
6. Analyse statistics
7. Examine message flows
© 2015 IBM
Corporation
14 July 2015
Step 1 – Check flows are running using the WebUI
 Check the server is running
 Check the flows are running
 Check the event/sys log for any errors
 Processing messages and no errors
© 2015 IBM
Corporation
14 July 2015
Step 2 – Start a load generator
 Run JMSPerfharness
– Using 10 threads
 All threads start successfully
– Each thread PUTs a message then GETs a
message so should be no messages on
queues for any period of time
 Check event/sys log for any error messages
© 2015 IBM
Corporation
14 July 2015
Step 3 – Look at CPU activity
 Messages being processed but:
– Rate is low, much lower than expected
– Very little CPU being used
• Integration Server does not register any
CPU activity
© 2015 IBM
Corporation
14 July 2015
Step 4 – Look for a build up of messages
 Key queues are  Build up of messages on queues:
– GET_REPTO_STORE
– GET_BACKEND_REQ
 What does this mean?
GET_BACKEND_REQ
GET_BACKEND_REP
CSIM_SERVER_IN_Q
GET_REPTO_STORE
GET_BACKEND_REQ
GET_BACKEND_REP
GET_REPTO_STORE
CSIM_COMMON_REPLY_Q
Request
BackendReplyApp
Reply
© 2015 IBM
Corporation
14 July 2015
Step 4 – Look for a build up of messages...
 Looking at the flows
– Queue GET_REPTO_STORE is used by Request and Reply message flows
– Queue GET_BACKEND_REQ is used by BackendReplyApp message flow
– GET_REPTO_STORE is used mid-flow (so flows using this are less likely to be the problem)
– GET_BACKEND_REQ is the input queue for the BackendReplyApp
• Indicates flow is not running fast enough or not enough instances allocated
 Need to investigate what is happening with BackendReplyApp
– For this use WebUI flow statistics
© 2015 IBM
Corporation
14 July 2015
Step 5 – Enable flow statistics
 Start and stop statistics using the WebUI for:
– All flows in a server
– All flows in a container
– Individual flows
© 2015 IBM
Corporation
14 July 2015
Step 5 – View statistics
 Select the statistics view
 Drill down to the problem flow
 Start by comparing flows
 Flow analysis view for most detail
© 2015 IBM
Corporation
14 July 2015
Step 6 – Compare flows
 Compare flows to determine which one might be causing the problem
 We can see that the BackendReplyApp flow has an average elapsed time of 1,000.9 milliseconds. It
only has 1 active thread, and has processed 20 messages in the 20 second statistical snapshot
period.
 This matches the rate we see in JMSPerfHarness!
© 2015 IBM
Corporation
14 July 2015
Step 6 – Analyse the flow
 Display historical flow details such as message
rate, CPU and elapsed time
 View all nodes within the flow to determine and
sort by average elapsed and CPU times
 The compute node Modify_CompletionTime
seems to be a problem!
 What does high elapsed time and low CPU time
suggest the problem might be?
© 2015 IBM
Corporation
14 July 2015
Step 7 – Review the code
 Having worked out which node is causing the problem
 We can quickly see why the node is taking 1 second elapsed time but little CPU
© 2015 IBM
Corporation
14 July 2015
Problem found!!
 1 second sleep in the compute node within the message flow is causing slow processing times and no
CPU usage
– Matches the observations at the start
• Low CPU and low message rate
 Unlikely to be so easy in future but slow service times, like slow synchronous web service invocations
would have the same effect
 If it was slow web service response times then allocate more additional instances to improve
processing rate
© 2015 IBM
Corporation
14 July 2015
Summary of steps for this investigation
 Use a systemic approach
– Key steps used were
1.Ensure all components are started and the applications works as expected
- Message flows, databases, external applications etc.
2.Start a load generator [JMSPerfharness in this case]
3.Look at activity
- Is processing happening at the expected rate?
- Is CPU usage as expected?
- Is memory usage as expected?
4.If things do not seem as expected
- Look for build up of messages
- Poor service times
5.Enable and view statistics
6.Analyse statistics
7.Examine message flows
 It is very important to
– Use tools
• System level and component level
– Start at a high level – system level and then close-in on the problem
© 2015 IBM
Corporation
14 July 2015
Demonstration 2
Analysing a performance problem in the Java Compute Transform Scenario
© 2015 IBM
Corporation
14 July 2015
JavaComputeTransform message flows
 Consists of one message flow
– JavaCompute
• Reads an XML message
• Transforms to a different format using a Java Compute node
JAVA_COMPUTE_IN JAVA_COMPUTE_OUT
© 2015 IBM
Corporation
14 July 2015
What is the problem we need to solve?
 The problem is characterised by
– Low message rate
– High CPU usage at both system and Integration Server level
– Sufficient messages on the input queue
 Likely issue is one of high CPU usage in a message flow
– But which flow and which node?
© 2015 IBM
Corporation
14 July 2015
Compare the flows
 All of the elapsed and CPU time is in the JavaCompute message flow, so continue investigation here
© 2015 IBM
Corporation
14 July 2015
Finding the processing Node for investigation
 The majority of the elapsed and CPU time
within the flow is spent in the
JavaCompute Node
 What might cause this?
 As this is a Java Compute Node continue
investigation using the Java Healthcenter
© 2015 IBM
Corporation
14 July 2015
Find the Integration Server port for Java Health Center
Environment variable:
IBM_JAVA_OPTIONS=-Xhealthcenter
Opens ports starting 1972, the Integration Server
running the JavaComputeTransform scneario is
using port 1974
© 2015 IBM
Corporation
14 July 2015
Alternate method for finding the port number
> mqsilist DEMO -d2
-----------------------------------
BIP1286I: Integration server 'default' on integration node
'DEMO' is running.
Number of message flows that are enabled to run: '4'.
Number of applications that are enabled to run: '2'.
Process ID: '7284'
UUID: 'e1306ebc-3c3a-43c2-b18a-bbdb99e07d5c'
Short description: ''
Long description: ''
BIP8071I: Successful command completion.
> netstat -a -b -n -o
[runmqlsr.exe]
TCP [::]:1972 [::]:0 LISTENING 7352
[bipbroker.exe]
TCP [::]:1973 [::]:0 LISTENING 7748
[biphttplistener.exe]
TCP [::]:1974 [::]:0 LISTENING 7284
[DataFlowEngine.exe]
TCP [::]:4417 [::]:0 LISTENING 7352
[bipbroker.exe]
TCP [::]:49152 [::]:0 LISTENING 924
© 2015 IBM
Corporation
14 July 2015
Invoking the Java Health Center
© 2015 IBM
Corporation
14 July 2015
Attaching to the Integration Server JVM
© 2015 IBM
Corporation
14 July 2015
Connect to a port
© 2015 IBM
Corporation
14 July 2015
Connection complete and ready to analyse
© 2015 IBM
Corporation
14 July 2015
Analysis and Recommendations – CPU
© 2015 IBM
Corporation
14 July 2015
Analysis and Recommendations – Classes
© 2015 IBM
Corporation
14 July 2015
Analysis and Recommendations – Environment
© 2015 IBM
Corporation
14 July 2015
Analysis and Recommendations – Garbage Collection
© 2015 IBM
Corporation
14 July 2015
Analysis and Recommendations – I/O
© 2015 IBM
Corporation
14 July 2015
Analysis and Recommendations – Locking
© 2015 IBM
Corporation
14 July 2015
Analysis and Recommendations – Native Memory
© 2015 IBM
Corporation
14 July 2015
Analysis and Recommendations – Profiling
© 2015 IBM
Corporation
14 July 2015
The cause
 Having worked out which node is
causing the problem
 We can quickly see why the node is
consuming a lot of CPU
 A call to the method bubble_sort() just
before propagating out of the node is
sorting the entire output message
© 2015 IBM
Corporation
14 July 2015
If you suspect there is a product problem
 Identify the problem as best you can
 Find the simplest test that recreates the problem
 Collect the data identified in the Must Gather list
– For IIB http://www-01.ibm.com/support/docview.wss?rs=849&uid=swg21209857
– For MQ: http://www-01.ibm.com/support/docview.wss?uid=swg21229861#MG6
© 2015 IBM
Corporation
14 July 2015
Summary
 Wide range of tools available covering operating system and component performance
– Expect to use multiple tools
– After all it is important to understand what is happening at different levels
– Demonstration has shown how to use the key tools for MQ and IIB to debug a problem
 Practice before hand
– Being familiar with the tools is a great help in a crisis
– Learning a new tool and solving a crisis is not a good combination
 Know your applications and systems
– What is normal in terms of processing rate, CPU usage etc.
– This information allows to know whether there is a problem and to what extent
© 2015 IBM
Corporation
14 July 2015
Additional Information
 WebSphere Message Broker: Designing for Performance
– http://www-01.ibm.com/support/docview.wss?rs=849&uid=swg24006518
 WebSphere Message Broker: Message display, test & performance utilities (IH03)
– http://www-01.ibm.com/support/docview.wss?rs=171&uid=swg24000637
 IBM Monitoring and Diagnostic Tools for Java – Getting started with Health Center
– http://www.ibm.com/developerworks/java/jdk/tools/healthcenter/getting_started.html
 IBM Monitoring and Diagnostic Tools for Java – Health Center
– http://www.ibm.com/developerworks/java/jdk/tools/healthcenter/
 IBM Monitoring and Diagnostic Tools for Java – Knowledge Center
– http://www-01.ibm.com/support/knowledgecenter/#!/SS3KLZ/SS3KLZ/welcome_tools_family.html
© 2015 IBM
Corporation
14 July 2015
Backup chart
 MQ processes
 Additional Instances usage and tuning
© 2015 IBM
Corporation
14 July 2015
WebSphere MQ V7 Processes
Task Function
AMQALMPX The checkpoint processor that periodically takes journal checkpoints.
AMQZMUC0 Utility manager. This job executes critical queue manager utilities, for example the
journal chain manager.
AMQZXMA0 The execution controller that is the first job started by the queue manager. It handles
MQCONN requests, and starts agent processes to process WebSphere MQ API calls
AMQZFUMA Object authority manager (OAM)
AMQZLAA0 Queue manager agents that perform most of the work for applications that connect to
the queue manager using MQCNO_STANDARD_BINDING.
AMQZLAS0 Queue manager agent.
AMQZMUF0 Utility Manager
AMQZMGR0 Process controller. This job is used to start up and manage listeners and services.
AMQZMUR0 Utility manager. This job executes critical queue manager utilities, for example the
journal chain manager.
AMQZDMAA Deferred Message Processor
AMQFQPUB Publish/subscribe process.
AMQFCXBA Broker worker job.
RUNMQBRK Broker control job.
AMQRMPPA Channel process pooling job.
AMQCRSTA TCP/IP-invoked channel responder.
© 2015 IBM
Corporation
14 July 2015
WebSphere MQ V7 Processes
Task Function
AMQCRS6B LU62 receiver channel and client connection.
AMQRRMFA Repository manager for clusters.
AMQCLMAA Non-threaded TCP/IP listener.
AMQPCSEA PCF command processor that handles PCF and remote administration requests.
RUNMQTRM Trigger monitor.
RUNMQDLQ Dead letter queue handler.
RUNMQCHI The channel initiator.
RUNMQCHL Sender channel job that is started for each sender channel.
RUNMQLSR Threaded TCP/IP listener.
AMQXSSVN Shared memory servers.
AMQRCMLA Channel MQSC and PCF command processor.
AMQZTRCN Trace.
 Number present at any time will vary
– Dependent on configuration, applications running, etc.
– Some will always be present, such as AMGZXMA0 (Execution Controller)
© 2015 IBM
Corporation
14 July 2015
Additional Instances usage and tuning
 Integration Server level data contains the following data for each message flow in it:
– MessageFlowName
– TotalElapsedTime
– MaximumElapsedTime
– MinimumElapsedTime
– TotalCPUTime
– MaximumCPUTime
– MinimumCPUTime
– CPUTimeWaitingForInputMessage
– ElapsedTimeWaitingForInputMessage
– TotalInputMessages
– TotalNumberOfTimeOutsWaitingForRepliesToAggregateMessages
– TotalSizeOfInputMessages
– MaximumSizeOfInputMessages
– MinimumSizeOfInputMessages
– NumberOfThreadsInPool
– TimesMaximumNumberOfThreadsReached
– TotalNumberOfMQErrors
– TotalNumberOfMessagesWithErrors
– TotalNumberOfErrorsProcessingMessages
– TotalNumberOfCommits
– TotalNumberOfBackouts
 Fields NumberOfThreadsInPool and TimesMaximumNumberOfThreadsReached show for every
message flow the number of additional instances allocated and the number of times they were all used
– Use this data to determine if:
• More additional instances are required
• Too many are allocated
© 2015 IBM
Corporation
14 July 2015
Additional Instances usage and tuning
 % Time Thread Pool Limit Reached = TimesMaximumNumberOfThreadsReached / TotalInputMessages

More Related Content

What's hot

CloudStack Best Practice in PPTV
CloudStack Best Practice in PPTVCloudStack Best Practice in PPTV
CloudStack Best Practice in PPTVgavin_lee
 
Effective admin and development in iib
Effective admin and development in iibEffective admin and development in iib
Effective admin and development in iibm16k
 
IBM MQ - High Availability and Disaster Recovery
IBM MQ - High Availability and Disaster RecoveryIBM MQ - High Availability and Disaster Recovery
IBM MQ - High Availability and Disaster RecoveryMarkTaylorIBM
 
Object Store V2 Workshop
Object Store V2 WorkshopObject Store V2 Workshop
Object Store V2 WorkshopMuleSoft
 
IBM MQ High Availability 2019
IBM MQ High Availability 2019IBM MQ High Availability 2019
IBM MQ High Availability 2019David Ware
 
Mule Runtime: Performance Tuning
Mule Runtime: Performance Tuning Mule Runtime: Performance Tuning
Mule Runtime: Performance Tuning MuleSoft
 
Introduction to Anypoint Runtime Fabric on Amazon Elastic Kubernetes Service ...
Introduction to Anypoint Runtime Fabric on Amazon Elastic Kubernetes Service ...Introduction to Anypoint Runtime Fabric on Amazon Elastic Kubernetes Service ...
Introduction to Anypoint Runtime Fabric on Amazon Elastic Kubernetes Service ...Anoop Ramachandran
 
Whats New in Integration What's New in IBM Integration Bus and IIB on Cloud
Whats New in Integration What's New in IBM Integration Bus and IIB on Cloud Whats New in Integration What's New in IBM Integration Bus and IIB on Cloud
Whats New in Integration What's New in IBM Integration Bus and IIB on Cloud Rob Convery
 
IBM WebSphere MQ: Managing Workloads, Scaling and Availability with MQ Clusters
IBM WebSphere MQ: Managing Workloads, Scaling and Availability with MQ ClustersIBM WebSphere MQ: Managing Workloads, Scaling and Availability with MQ Clusters
IBM WebSphere MQ: Managing Workloads, Scaling and Availability with MQ ClustersDavid Ware
 
Migrating from IBM API Connect v5 to v2018
Migrating from IBM API Connect v5 to v2018Migrating from IBM API Connect v5 to v2018
Migrating from IBM API Connect v5 to v2018Natalia Kataoka
 
MuleSoft Deployment Strategies (RTF vs Hybrid vs CloudHub)
MuleSoft Deployment Strategies (RTF vs Hybrid vs CloudHub)MuleSoft Deployment Strategies (RTF vs Hybrid vs CloudHub)
MuleSoft Deployment Strategies (RTF vs Hybrid vs CloudHub)Prashanth Kurimella
 
Consumer offset management in Kafka
Consumer offset management in KafkaConsumer offset management in Kafka
Consumer offset management in KafkaJoel Koshy
 
Overview - ESBs and IBM Integration Bus
Overview - ESBs and IBM Integration BusOverview - ESBs and IBM Integration Bus
Overview - ESBs and IBM Integration BusJuarez Junior
 
Introduction to kubernetes
Introduction to kubernetesIntroduction to kubernetes
Introduction to kubernetesRishabh Indoria
 
July OpenNTF Webinar - HCL Presents Keep, a new API for Domino
July OpenNTF Webinar - HCL Presents Keep, a new API for DominoJuly OpenNTF Webinar - HCL Presents Keep, a new API for Domino
July OpenNTF Webinar - HCL Presents Keep, a new API for DominoHoward Greenberg
 
Kafka Reliability - When it absolutely, positively has to be there
Kafka Reliability - When it absolutely, positively has to be thereKafka Reliability - When it absolutely, positively has to be there
Kafka Reliability - When it absolutely, positively has to be thereGwen (Chen) Shapira
 

What's hot (20)

CloudStack Best Practice in PPTV
CloudStack Best Practice in PPTVCloudStack Best Practice in PPTV
CloudStack Best Practice in PPTV
 
Effective admin and development in iib
Effective admin and development in iibEffective admin and development in iib
Effective admin and development in iib
 
IBM MQ - High Availability and Disaster Recovery
IBM MQ - High Availability and Disaster RecoveryIBM MQ - High Availability and Disaster Recovery
IBM MQ - High Availability and Disaster Recovery
 
Object Store V2 Workshop
Object Store V2 WorkshopObject Store V2 Workshop
Object Store V2 Workshop
 
IBM MQ High Availability 2019
IBM MQ High Availability 2019IBM MQ High Availability 2019
IBM MQ High Availability 2019
 
Mule Runtime: Performance Tuning
Mule Runtime: Performance Tuning Mule Runtime: Performance Tuning
Mule Runtime: Performance Tuning
 
Introduction to Anypoint Runtime Fabric on Amazon Elastic Kubernetes Service ...
Introduction to Anypoint Runtime Fabric on Amazon Elastic Kubernetes Service ...Introduction to Anypoint Runtime Fabric on Amazon Elastic Kubernetes Service ...
Introduction to Anypoint Runtime Fabric on Amazon Elastic Kubernetes Service ...
 
Whats New in Integration What's New in IBM Integration Bus and IIB on Cloud
Whats New in Integration What's New in IBM Integration Bus and IIB on Cloud Whats New in Integration What's New in IBM Integration Bus and IIB on Cloud
Whats New in Integration What's New in IBM Integration Bus and IIB on Cloud
 
IBM WebSphere MQ: Managing Workloads, Scaling and Availability with MQ Clusters
IBM WebSphere MQ: Managing Workloads, Scaling and Availability with MQ ClustersIBM WebSphere MQ: Managing Workloads, Scaling and Availability with MQ Clusters
IBM WebSphere MQ: Managing Workloads, Scaling and Availability with MQ Clusters
 
Migrating from IBM API Connect v5 to v2018
Migrating from IBM API Connect v5 to v2018Migrating from IBM API Connect v5 to v2018
Migrating from IBM API Connect v5 to v2018
 
MuleSoft Deployment Strategies (RTF vs Hybrid vs CloudHub)
MuleSoft Deployment Strategies (RTF vs Hybrid vs CloudHub)MuleSoft Deployment Strategies (RTF vs Hybrid vs CloudHub)
MuleSoft Deployment Strategies (RTF vs Hybrid vs CloudHub)
 
Kafka presentation
Kafka presentationKafka presentation
Kafka presentation
 
Consumer offset management in Kafka
Consumer offset management in KafkaConsumer offset management in Kafka
Consumer offset management in Kafka
 
Overview - ESBs and IBM Integration Bus
Overview - ESBs and IBM Integration BusOverview - ESBs and IBM Integration Bus
Overview - ESBs and IBM Integration Bus
 
Cloudhub 2.0
Cloudhub 2.0Cloudhub 2.0
Cloudhub 2.0
 
Kafka 101
Kafka 101Kafka 101
Kafka 101
 
Introduction to kubernetes
Introduction to kubernetesIntroduction to kubernetes
Introduction to kubernetes
 
July OpenNTF Webinar - HCL Presents Keep, a new API for Domino
July OpenNTF Webinar - HCL Presents Keep, a new API for DominoJuly OpenNTF Webinar - HCL Presents Keep, a new API for Domino
July OpenNTF Webinar - HCL Presents Keep, a new API for Domino
 
Ansible Automation - Enterprise Use Cases | Juncheng Anthony Lin
Ansible Automation - Enterprise Use Cases | Juncheng Anthony LinAnsible Automation - Enterprise Use Cases | Juncheng Anthony Lin
Ansible Automation - Enterprise Use Cases | Juncheng Anthony Lin
 
Kafka Reliability - When it absolutely, positively has to be there
Kafka Reliability - When it absolutely, positively has to be thereKafka Reliability - When it absolutely, positively has to be there
Kafka Reliability - When it absolutely, positively has to be there
 

Similar to Iib v10 performance problem determination examples

Operational and business monitoring with IBM Integration Bus-Sanjay Nagchowdhury
Operational and business monitoring with IBM Integration Bus-Sanjay NagchowdhuryOperational and business monitoring with IBM Integration Bus-Sanjay Nagchowdhury
Operational and business monitoring with IBM Integration Bus-Sanjay NagchowdhuryKaren Broughton-Mabbitt
 
Importance of ‘Centralized Event collection’ and BigData platform for Analysis !
Importance of ‘Centralized Event collection’ and BigData platform for Analysis !Importance of ‘Centralized Event collection’ and BigData platform for Analysis !
Importance of ‘Centralized Event collection’ and BigData platform for Analysis !Piyush Kumar
 
Architecting and Tuning IIB/eXtreme Scale for Maximum Performance and Reliabi...
Architecting and Tuning IIB/eXtreme Scale for Maximum Performance and Reliabi...Architecting and Tuning IIB/eXtreme Scale for Maximum Performance and Reliabi...
Architecting and Tuning IIB/eXtreme Scale for Maximum Performance and Reliabi...Prolifics
 
Actionable Insights - Thompson
Actionable Insights - ThompsonActionable Insights - Thompson
Actionable Insights - ThompsonProlifics
 
IBM Monitoring and Event Management Solutions
IBM Monitoring and Event Management SolutionsIBM Monitoring and Event Management Solutions
IBM Monitoring and Event Management SolutionsIBM Danmark
 
MuleSoft Manchester Meetup #4 slides 11th February 2021
MuleSoft Manchester Meetup #4 slides 11th February 2021MuleSoft Manchester Meetup #4 slides 11th February 2021
MuleSoft Manchester Meetup #4 slides 11th February 2021Ieva Navickaite
 
Functioning incessantly of Data Science Platform with Kubeflow - Albert Lewan...
Functioning incessantly of Data Science Platform with Kubeflow - Albert Lewan...Functioning incessantly of Data Science Platform with Kubeflow - Albert Lewan...
Functioning incessantly of Data Science Platform with Kubeflow - Albert Lewan...GetInData
 
Volta: Logging, Metrics, and Monitoring as a Service
Volta: Logging, Metrics, and Monitoring as a ServiceVolta: Logging, Metrics, and Monitoring as a Service
Volta: Logging, Metrics, and Monitoring as a ServiceLN Renganarayana
 
IBM Performance and Accounting
IBM Performance and AccountingIBM Performance and Accounting
IBM Performance and AccountingIBM Systems UKI
 
IMCSummit 2015 - Day 1 Developer Track - Implementing Operational Intelligenc...
IMCSummit 2015 - Day 1 Developer Track - Implementing Operational Intelligenc...IMCSummit 2015 - Day 1 Developer Track - Implementing Operational Intelligenc...
IMCSummit 2015 - Day 1 Developer Track - Implementing Operational Intelligenc...In-Memory Computing Summit
 
What's new in informix v11.70
What's new in informix v11.70What's new in informix v11.70
What's new in informix v11.70am_prasanna
 
TIBCO vs MuleSoft Differentiators
TIBCO vs MuleSoft DifferentiatorsTIBCO vs MuleSoft Differentiators
TIBCO vs MuleSoft DifferentiatorsSatish Nannapaneni
 
SmartCloud Monitoring and Capacity Planning
SmartCloud Monitoring and Capacity PlanningSmartCloud Monitoring and Capacity Planning
SmartCloud Monitoring and Capacity PlanningIBM Danmark
 
Spring and Pivotal Application Service - SpringOne Tour Dallas
Spring and Pivotal Application Service - SpringOne Tour DallasSpring and Pivotal Application Service - SpringOne Tour Dallas
Spring and Pivotal Application Service - SpringOne Tour DallasVMware Tanzu
 
Monitoring Node.js Microservices on CloudFoundry with Open Source Tools and a...
Monitoring Node.js Microservices on CloudFoundry with Open Source Tools and a...Monitoring Node.js Microservices on CloudFoundry with Open Source Tools and a...
Monitoring Node.js Microservices on CloudFoundry with Open Source Tools and a...Tony Erwin
 
IMCSummit 2015 - Day 1 Developer Track - In-memory Computing for Iterative CP...
IMCSummit 2015 - Day 1 Developer Track - In-memory Computing for Iterative CP...IMCSummit 2015 - Day 1 Developer Track - In-memory Computing for Iterative CP...
IMCSummit 2015 - Day 1 Developer Track - In-memory Computing for Iterative CP...In-Memory Computing Summit
 
MuleSoft Manchester Meetup #2 slides 29th October 2019
MuleSoft Manchester Meetup #2 slides 29th October 2019MuleSoft Manchester Meetup #2 slides 29th October 2019
MuleSoft Manchester Meetup #2 slides 29th October 2019Ieva Navickaite
 
Brief summary of onTune [teemstone]
Brief summary of onTune [teemstone]Brief summary of onTune [teemstone]
Brief summary of onTune [teemstone]TeemStone Pty Ltd
 

Similar to Iib v10 performance problem determination examples (20)

Operational and business monitoring with IBM Integration Bus-Sanjay Nagchowdhury
Operational and business monitoring with IBM Integration Bus-Sanjay NagchowdhuryOperational and business monitoring with IBM Integration Bus-Sanjay Nagchowdhury
Operational and business monitoring with IBM Integration Bus-Sanjay Nagchowdhury
 
Distributed Systems in Data Engineering
Distributed Systems in Data EngineeringDistributed Systems in Data Engineering
Distributed Systems in Data Engineering
 
Importance of ‘Centralized Event collection’ and BigData platform for Analysis !
Importance of ‘Centralized Event collection’ and BigData platform for Analysis !Importance of ‘Centralized Event collection’ and BigData platform for Analysis !
Importance of ‘Centralized Event collection’ and BigData platform for Analysis !
 
Architecting and Tuning IIB/eXtreme Scale for Maximum Performance and Reliabi...
Architecting and Tuning IIB/eXtreme Scale for Maximum Performance and Reliabi...Architecting and Tuning IIB/eXtreme Scale for Maximum Performance and Reliabi...
Architecting and Tuning IIB/eXtreme Scale for Maximum Performance and Reliabi...
 
Actionable Insights - Thompson
Actionable Insights - ThompsonActionable Insights - Thompson
Actionable Insights - Thompson
 
IBM Monitoring and Event Management Solutions
IBM Monitoring and Event Management SolutionsIBM Monitoring and Event Management Solutions
IBM Monitoring and Event Management Solutions
 
MuleSoft Manchester Meetup #4 slides 11th February 2021
MuleSoft Manchester Meetup #4 slides 11th February 2021MuleSoft Manchester Meetup #4 slides 11th February 2021
MuleSoft Manchester Meetup #4 slides 11th February 2021
 
Functioning incessantly of Data Science Platform with Kubeflow - Albert Lewan...
Functioning incessantly of Data Science Platform with Kubeflow - Albert Lewan...Functioning incessantly of Data Science Platform with Kubeflow - Albert Lewan...
Functioning incessantly of Data Science Platform with Kubeflow - Albert Lewan...
 
Volta: Logging, Metrics, and Monitoring as a Service
Volta: Logging, Metrics, and Monitoring as a ServiceVolta: Logging, Metrics, and Monitoring as a Service
Volta: Logging, Metrics, and Monitoring as a Service
 
IBM Performance and Accounting
IBM Performance and AccountingIBM Performance and Accounting
IBM Performance and Accounting
 
How to Monitor IIS
How to Monitor IISHow to Monitor IIS
How to Monitor IIS
 
IMCSummit 2015 - Day 1 Developer Track - Implementing Operational Intelligenc...
IMCSummit 2015 - Day 1 Developer Track - Implementing Operational Intelligenc...IMCSummit 2015 - Day 1 Developer Track - Implementing Operational Intelligenc...
IMCSummit 2015 - Day 1 Developer Track - Implementing Operational Intelligenc...
 
What's new in informix v11.70
What's new in informix v11.70What's new in informix v11.70
What's new in informix v11.70
 
TIBCO vs MuleSoft Differentiators
TIBCO vs MuleSoft DifferentiatorsTIBCO vs MuleSoft Differentiators
TIBCO vs MuleSoft Differentiators
 
SmartCloud Monitoring and Capacity Planning
SmartCloud Monitoring and Capacity PlanningSmartCloud Monitoring and Capacity Planning
SmartCloud Monitoring and Capacity Planning
 
Spring and Pivotal Application Service - SpringOne Tour Dallas
Spring and Pivotal Application Service - SpringOne Tour DallasSpring and Pivotal Application Service - SpringOne Tour Dallas
Spring and Pivotal Application Service - SpringOne Tour Dallas
 
Monitoring Node.js Microservices on CloudFoundry with Open Source Tools and a...
Monitoring Node.js Microservices on CloudFoundry with Open Source Tools and a...Monitoring Node.js Microservices on CloudFoundry with Open Source Tools and a...
Monitoring Node.js Microservices on CloudFoundry with Open Source Tools and a...
 
IMCSummit 2015 - Day 1 Developer Track - In-memory Computing for Iterative CP...
IMCSummit 2015 - Day 1 Developer Track - In-memory Computing for Iterative CP...IMCSummit 2015 - Day 1 Developer Track - In-memory Computing for Iterative CP...
IMCSummit 2015 - Day 1 Developer Track - In-memory Computing for Iterative CP...
 
MuleSoft Manchester Meetup #2 slides 29th October 2019
MuleSoft Manchester Meetup #2 slides 29th October 2019MuleSoft Manchester Meetup #2 slides 29th October 2019
MuleSoft Manchester Meetup #2 slides 29th October 2019
 
Brief summary of onTune [teemstone]
Brief summary of onTune [teemstone]Brief summary of onTune [teemstone]
Brief summary of onTune [teemstone]
 

Recently uploaded

TECUNIQUE: Success Stories: IT Service provider
TECUNIQUE: Success Stories: IT Service providerTECUNIQUE: Success Stories: IT Service provider
TECUNIQUE: Success Stories: IT Service providermohitmore19
 
+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...
+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...
+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...Health
 
How To Troubleshoot Collaboration Apps for the Modern Connected Worker
How To Troubleshoot Collaboration Apps for the Modern Connected WorkerHow To Troubleshoot Collaboration Apps for the Modern Connected Worker
How To Troubleshoot Collaboration Apps for the Modern Connected WorkerThousandEyes
 
W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...
W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...
W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...panagenda
 
Hand gesture recognition PROJECT PPT.pptx
Hand gesture recognition PROJECT PPT.pptxHand gesture recognition PROJECT PPT.pptx
Hand gesture recognition PROJECT PPT.pptxbodapatigopi8531
 
Software Quality Assurance Interview Questions
Software Quality Assurance Interview QuestionsSoftware Quality Assurance Interview Questions
Software Quality Assurance Interview QuestionsArshad QA
 
Right Money Management App For Your Financial Goals
Right Money Management App For Your Financial GoalsRight Money Management App For Your Financial Goals
Right Money Management App For Your Financial GoalsJhone kinadey
 
Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...
Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...
Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...harshavardhanraghave
 
A Secure and Reliable Document Management System is Essential.docx
A Secure and Reliable Document Management System is Essential.docxA Secure and Reliable Document Management System is Essential.docx
A Secure and Reliable Document Management System is Essential.docxComplianceQuest1
 
Unlocking the Future of AI Agents with Large Language Models
Unlocking the Future of AI Agents with Large Language ModelsUnlocking the Future of AI Agents with Large Language Models
Unlocking the Future of AI Agents with Large Language Modelsaagamshah0812
 
Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time ApplicationsUnveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time ApplicationsAlberto González Trastoy
 
The Ultimate Test Automation Guide_ Best Practices and Tips.pdf
The Ultimate Test Automation Guide_ Best Practices and Tips.pdfThe Ultimate Test Automation Guide_ Best Practices and Tips.pdf
The Ultimate Test Automation Guide_ Best Practices and Tips.pdfkalichargn70th171
 
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...ICS
 
How To Use Server-Side Rendering with Nuxt.js
How To Use Server-Side Rendering with Nuxt.jsHow To Use Server-Side Rendering with Nuxt.js
How To Use Server-Side Rendering with Nuxt.jsAndolasoft Inc
 
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...MyIntelliSource, Inc.
 
SyndBuddy AI 2k Review 2024: Revolutionizing Content Syndication with AI
SyndBuddy AI 2k Review 2024: Revolutionizing Content Syndication with AISyndBuddy AI 2k Review 2024: Revolutionizing Content Syndication with AI
SyndBuddy AI 2k Review 2024: Revolutionizing Content Syndication with AIABDERRAOUF MEHENNI
 
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...Steffen Staab
 
HR Software Buyers Guide in 2024 - HRSoftware.com
HR Software Buyers Guide in 2024 - HRSoftware.comHR Software Buyers Guide in 2024 - HRSoftware.com
HR Software Buyers Guide in 2024 - HRSoftware.comFatema Valibhai
 

Recently uploaded (20)

Vip Call Girls Noida ➡️ Delhi ➡️ 9999965857 No Advance 24HRS Live
Vip Call Girls Noida ➡️ Delhi ➡️ 9999965857 No Advance 24HRS LiveVip Call Girls Noida ➡️ Delhi ➡️ 9999965857 No Advance 24HRS Live
Vip Call Girls Noida ➡️ Delhi ➡️ 9999965857 No Advance 24HRS Live
 
TECUNIQUE: Success Stories: IT Service provider
TECUNIQUE: Success Stories: IT Service providerTECUNIQUE: Success Stories: IT Service provider
TECUNIQUE: Success Stories: IT Service provider
 
+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...
+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...
+971565801893>>SAFE AND ORIGINAL ABORTION PILLS FOR SALE IN DUBAI AND ABUDHAB...
 
How To Troubleshoot Collaboration Apps for the Modern Connected Worker
How To Troubleshoot Collaboration Apps for the Modern Connected WorkerHow To Troubleshoot Collaboration Apps for the Modern Connected Worker
How To Troubleshoot Collaboration Apps for the Modern Connected Worker
 
W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...
W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...
W01_panagenda_Navigating-the-Future-with-The-Hitchhikers-Guide-to-Notes-and-D...
 
Hand gesture recognition PROJECT PPT.pptx
Hand gesture recognition PROJECT PPT.pptxHand gesture recognition PROJECT PPT.pptx
Hand gesture recognition PROJECT PPT.pptx
 
Software Quality Assurance Interview Questions
Software Quality Assurance Interview QuestionsSoftware Quality Assurance Interview Questions
Software Quality Assurance Interview Questions
 
Right Money Management App For Your Financial Goals
Right Money Management App For Your Financial GoalsRight Money Management App For Your Financial Goals
Right Money Management App For Your Financial Goals
 
Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...
Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...
Reassessing the Bedrock of Clinical Function Models: An Examination of Large ...
 
A Secure and Reliable Document Management System is Essential.docx
A Secure and Reliable Document Management System is Essential.docxA Secure and Reliable Document Management System is Essential.docx
A Secure and Reliable Document Management System is Essential.docx
 
CHEAP Call Girls in Pushp Vihar (-DELHI )🔝 9953056974🔝(=)/CALL GIRLS SERVICE
CHEAP Call Girls in Pushp Vihar (-DELHI )🔝 9953056974🔝(=)/CALL GIRLS SERVICECHEAP Call Girls in Pushp Vihar (-DELHI )🔝 9953056974🔝(=)/CALL GIRLS SERVICE
CHEAP Call Girls in Pushp Vihar (-DELHI )🔝 9953056974🔝(=)/CALL GIRLS SERVICE
 
Unlocking the Future of AI Agents with Large Language Models
Unlocking the Future of AI Agents with Large Language ModelsUnlocking the Future of AI Agents with Large Language Models
Unlocking the Future of AI Agents with Large Language Models
 
Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time ApplicationsUnveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
Unveiling the Tech Salsa of LAMs with Janus in Real-Time Applications
 
The Ultimate Test Automation Guide_ Best Practices and Tips.pdf
The Ultimate Test Automation Guide_ Best Practices and Tips.pdfThe Ultimate Test Automation Guide_ Best Practices and Tips.pdf
The Ultimate Test Automation Guide_ Best Practices and Tips.pdf
 
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...
The Real-World Challenges of Medical Device Cybersecurity- Mitigating Vulnera...
 
How To Use Server-Side Rendering with Nuxt.js
How To Use Server-Side Rendering with Nuxt.jsHow To Use Server-Side Rendering with Nuxt.js
How To Use Server-Side Rendering with Nuxt.js
 
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
Steps To Getting Up And Running Quickly With MyTimeClock Employee Scheduling ...
 
SyndBuddy AI 2k Review 2024: Revolutionizing Content Syndication with AI
SyndBuddy AI 2k Review 2024: Revolutionizing Content Syndication with AISyndBuddy AI 2k Review 2024: Revolutionizing Content Syndication with AI
SyndBuddy AI 2k Review 2024: Revolutionizing Content Syndication with AI
 
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...
Shapes for Sharing between Graph Data Spaces - and Epistemic Querying of RDF-...
 
HR Software Buyers Guide in 2024 - HRSoftware.com
HR Software Buyers Guide in 2024 - HRSoftware.comHR Software Buyers Guide in 2024 - HRSoftware.com
HR Software Buyers Guide in 2024 - HRSoftware.com
 

Iib v10 performance problem determination examples

  • 1. © 2009 IBM Corporation IBM Integration Bus V10 Performance How to analyse your system to optimise performance and throughput Martin Ross - martin.ross@uk.ibm.com
  • 2. © 2015 IBM Corporation 14 July 2015 Overview  The purpose of this presentation is to demonstrate how to find the cause of poor performance for an IBM Integration Bus node (broker) for two different types of problem.  The examples are obtained on a Windows system but the principles of investigation and problem determination apply equally on all platforms. The system level tools will differ though.
  • 3. © 2015 IBM Corporation 14 July 2015 Agenda  Introduction  Tools  Techniques  Demonstration
  • 4. © 2015 IBM Corporation 14 July 2015 What are the main performance costs in message flows? ZYX…CBA Parsing Tree Navigation Root.Body.Level1.Level2. Level3.Description.Line[1]; Tree Copying Set OutputRoot = InputRoot; Resource Access Processing Logic
  • 5. © 2015 IBM Corporation 14 July 2015 Integration Bus Processes Integration Node Integration Server Application Application Message flows Message flows Libraries Libraries Integration Server [n] Application Application Message flows Message flows Libraries Libraries  Bipservice – Lightweight and resilient process that starts and monitors the bipbroker process – If the bipbroker process fails, bipservice will restart it  Bipbroker – A more substantial process. Contains the deployment manager and administrative agent. All commands, toolkit connections and WebUI go through this process. – Responsible for starting and monitoring the biphttplistener, bipMQTT and DataFlowEngine processes. – If any process fail, bipbroker will restart them.  BipMQTT – Handles MQTT events  Biphttplistener – Runs the brokerwide HTTP connector for HTTP and SOAP nodes.  DataFlowEngine – Runtime engine for all deployed resources.
  • 6. © 2015 IBM Corporation 14 July 2015 Which resources and how much  Understand typical resource utilisation – need to understand if resource utilisation is higher than expected or running as normal...  In busy times expect to use what is needed (!) – Exactly what will depend on the configuration and the applications – Typical to use CPU and memory plus I/O to some level  In quiet times Message Broker and MQ processes – Should use very little CPU – Should use very little I/O capacity – Will retain memory  Some memory sizes whilst running the Coordinated Request Reply sample – Bipservice 3.7 MB – Bipbroker 112 MB – Biphttplistener 35 MB – DataFlowEngine 154 MB • Can use from ~100 MB to GigaBytes depending on number of flows, complexity of the message flow, the size of the messages  MQ processes – Expect it to be less than IBM Integration Bus (76 MB for a simple queue manager) – Will depend on number of open queues, channels, queue buffer sizes etc.
  • 7. © 2015 IBM Corporation 14 July 2015 Tools that are needed  Monitoring tools – At the operating system level to observe • System resource usage – CPU, memory, I/O activity • Heaviest resource users – At the component level to observe • Behaviour within the particular component (MQ / IBM Integration Bus) – Both types of tools are needed • They have different views of the world • They are complimentary  Driving tools – Needed to generate a continuous workload • Important to assess performance after warm-up during sustained activity
  • 8. © 2015 IBM Corporation 14 July 2015 UNIX tools  Vmstat  Iostat  Nmon  filemon System Configuration: lcpu=64 mem=8192MB kthr memory page faults cpu ----- ----------- ------------------------ ------------ ----------- r b avm fre re pi po fr sr cy in sy cs us sy id wa 1 0 1977672 25823 0 0 0 0 0 0 3 958 696 4 0 96 0 1 0 1977838 25719 0 2 0 98 100 0 29 2941 2250 4 0 96 0 1 0 1977685 25872 0 0 0 0 0 0 2 636 483 4 0 96 0 System configuration: lcpu=64 drives=5 paths=6 vdisks=2 tty: tin tout avg-cpu: % user % sys % idle % iowait 0.0 29.5 3.6 0.1 96.2 0.0 Disks: % tm_act Kbps tps Kb_read Kb_wrtn hdisk3 0.0 0.0 0.0 0 0 hdisk2 0.0 0.0 0.0 0 0 hdisk0 0.0 4.0 1.0 8 0 hdisk1 0.0 0.0 0.0 0 0 cd0 0.0 0.0 0.0 0 0
  • 9. © 2015 IBM Corporation 14 July 2015 Windows tools – Process Explorer  Watch system activity in detail on Windows  Watch – CPU usage – Commit charge – I/O activity – Physical memory history – Summary information – Individual processes  Download from https://technet.microsoft.com/en-us/sysinternals/bb896653.aspx
  • 10. © 2015 IBM Corporation 14 July 2015 Process Explorer  DataFlowEngine.exe: – This is the Integration Server  amqzlaa0.exe – This is the MQ agent for LOCAL connections (including the broker)  amqrmppa.exe – This is the MQ agent for CLIENT connections  Can quickly see system is busy  Customise by selecting columns of choice
  • 11. © 2015 IBM Corporation 14 July 2015 Process Explorer – Task Information
  • 12. © 2015 IBM Corporation 14 July 2015 Find Integration Server name from PID mqsilist DEMO -d2 ----------------------------------- BIP1286I: Integration server 'default' on integration node 'DEMO' is running. Number of message flows that are enabled to run: '4'. Number of applications that are enabled to run: '2'. Process ID: '8248' UUID: 'e1306ebc-3c3a-43c2-b18a-bbdb99e07d5c' Short description: '' Long description: '' BIP8071I: Successful command completion.----------------------------------- BIP1286I: Integration server 'default' on integration node 'DEMO' is running. Number of message flows that are enabled to run: '4'. Number of applications that are enabled to run: '2'. Process ID: '8248' UUID: 'e1306ebc-3c3a-43c2-b18a-bbdb99e07d5c' Short description: '' Long description: '' BIP8071I: Successful command completion. -bash-4.1$ ps -ef | grep DataFlowEngine mqm 4331 4302 0 13:12 pts/0 00:00:00 grep DataFlowEngine mqm 28788 28701 99 12:57 ? 00:41:56 DataFlowEngine CSIM d2cd939a-a7a3-46ce-8168- b89c77744511 default
  • 13. © 2015 IBM Corporation 14 July 2015 Key tools at the component level  Integration Bus – User trace – Trace nodes – Activity Log – WebUI • Accounting & Statistics: Compare flow statistics at the node (broker), server (execution group), container (application or library) or at an individual message flow level • Resource Statistics: View resource use at the execution group level  MQ Explorer  Java Healthcenter
  • 14. © 2015 IBM Corporation 14 July 2015 Statistics scope Node (broker) Server (execution group) Node Message Flow Thread Message Model Terminals Resource Statistics Accounting & Statistics
  • 15. © 2015 IBM Corporation 14 July 2015 Accounting & Statistics  Dynamic reporting of message flow usage for • Problem determination • Chargeback • Profiling  Data at two levels 1. Universal (CPU cost, IO, elapsed time) 2. Broker specific (messages, commits, backouts)  A Choice of intervals • Short or snapshot • Long or archive  Attach a label to the information – AccountingOrigin to collect data to identify and collate this information according to the specific origin of a message, even in consolidated flows. Choice of destination 1. Trace 2. PubSub 3. SMF (z/OS only)
  • 16. © 2015 IBM Corporation 14 July 2015 Subscribing to Accounting & Statistics  Publish/Subscribe data is published on the topic $SYS/Broker/brokerName/StatisticsAccounting/recordType/executionGroupLabel/messageFlowLabel A subscription for $SYS/Broker/+/StatisticsAccounting/+ receives all statistics for all brokers Notes: The following three characters have a special meaning: – The topic level separator "/" – The multilevel wildcard "#" – The single-level wildcard "+"
  • 17. © 2015 IBM Corporation 14 July 2015 Resource Statistics  Dynamic reporting of the performance and operating details of resources used by execution groups • Problem determination • Profiling  Supported resources 1. CICS 2. CORBA 3. FTEAgenet 4. JDBCConnectionPools 5. JVM 6. ODBC 7. SOAPInput 8. Security 9. Outbound Sockets  Data • XML messages distributed using PubSub • Access as raw data or view in WebUI  Regular reporting • Data published approximately every 20 seconds
  • 18. © 2015 IBM Corporation 14 July 2015 Subscribing to Resource Statistics  Data is published on the topic $SYS/Broker/brokerName/ResourceStatistics/executionGroupLabel A subscription for $SYS/Broker/+/ResourceStatistics/+ receives all statistics for all brokers Notes: The following three characters have a special meaning: – The topic level separator "/" – The multilevel wildcard "#" – The single-level wildcard "+"
  • 19. © 2015 IBM Corporation 14 July 2015 WebUI – Accounting & Statistics  Using the WebUI in IBM Integration Bus v10: – Control statistics at all levels – Easily view and compare flows, helping to understand which are processing the most messages or have the highest elapsed time – Easily view and compare nodes, helping to understand which have the highest CPU or elapsed times – View all statistics metrics available for each flow – View historical flow data
  • 20. © 2015 IBM Corporation 14 July 2015 WebUI – Resource Statistics  View resource statistics for resource managers in IIB such as: – JVM – ODBC – JDBC – parsers, etc.
  • 21. © 2015 IBM Corporation 14 July 2015 MQ Explorer
  • 22. © 2015 IBM Corporation 14 July 2015 IBM Support Assistant and Java Health Centre  Java Health Centre is provided as part of the IBM Support Assistant – Offers very low overhead monitoring tool – Runs along side an IBM Java application  Get visibility, monitoring and profiling in the following application areas: – Performance • Java method profiling • Lock analysis • Garbage collection – Memory – System – Java Class – File input and – Object  Enable the application JVM prior to use – IBM_JAVA_OPTIONS=-Xhealthcenter
  • 23. © 2015 IBM Corporation 14 July 2015 Demonstration of analysing performance issues  Identify problems in two message flows using – Process Explorer – WebUI Statistics – MQ Explorer – Java Healthcenter Java Compute TransformCoordinated Request Reply
  • 24. © 2015 IBM Corporation 14 July 2015 Demonstration 1 Analysing a performance problem in the Coordinated Request Reply Scenario
  • 25. © 2015 IBM Corporation 14 July 2015 Coordinated Request Reply message flows  Consists of three message flows – Request • Converts incoming message from XML to CWF • Saves the incoming message in a queue for subsequent reply processing • Writes a message for the back end reply message flow – BackendReplyApp • Sets the completion time in the message • Writes a reply message – Reply • Reads the message from the back end message flow • Retrieves the original message saved by the request message flow • Writes an output message
  • 26. © 2015 IBM Corporation 14 July 2015 Coordinated Request Reply queues  The queues – Request – BackendReplyApp – Reply CSIM_SERVER_IN_Q GET_REPTO_STORE GET_REPTO_STORE GET_BACKEND_REPGET_BACKEND_REQ GET_BACKEND_REQ GET_BACKEND_REP CSIM_COMMON_REPLY_Q
  • 27. © 2015 IBM Corporation 14 July 2015 Run and investigate Steps 1. Ensure all components are started and the applications works as expected - Message flows, databases, external applications etc. 2. Start a load generator [JMSPerfharness in this case] 3. Look at activity - Is processing happening at the expected rate? - Is CPU usage as expected? - Is memory usage as expected? 4. If things do not seem as expected - Look for build up of messages - Poor service times 5. Enable and view statistics 6. Analyse statistics 7. Examine message flows
  • 28. © 2015 IBM Corporation 14 July 2015 Step 1 – Check flows are running using the WebUI  Check the server is running  Check the flows are running  Check the event/sys log for any errors  Processing messages and no errors
  • 29. © 2015 IBM Corporation 14 July 2015 Step 2 – Start a load generator  Run JMSPerfharness – Using 10 threads  All threads start successfully – Each thread PUTs a message then GETs a message so should be no messages on queues for any period of time  Check event/sys log for any error messages
  • 30. © 2015 IBM Corporation 14 July 2015 Step 3 – Look at CPU activity  Messages being processed but: – Rate is low, much lower than expected – Very little CPU being used • Integration Server does not register any CPU activity
  • 31. © 2015 IBM Corporation 14 July 2015 Step 4 – Look for a build up of messages  Key queues are  Build up of messages on queues: – GET_REPTO_STORE – GET_BACKEND_REQ  What does this mean? GET_BACKEND_REQ GET_BACKEND_REP CSIM_SERVER_IN_Q GET_REPTO_STORE GET_BACKEND_REQ GET_BACKEND_REP GET_REPTO_STORE CSIM_COMMON_REPLY_Q Request BackendReplyApp Reply
  • 32. © 2015 IBM Corporation 14 July 2015 Step 4 – Look for a build up of messages...  Looking at the flows – Queue GET_REPTO_STORE is used by Request and Reply message flows – Queue GET_BACKEND_REQ is used by BackendReplyApp message flow – GET_REPTO_STORE is used mid-flow (so flows using this are less likely to be the problem) – GET_BACKEND_REQ is the input queue for the BackendReplyApp • Indicates flow is not running fast enough or not enough instances allocated  Need to investigate what is happening with BackendReplyApp – For this use WebUI flow statistics
  • 33. © 2015 IBM Corporation 14 July 2015 Step 5 – Enable flow statistics  Start and stop statistics using the WebUI for: – All flows in a server – All flows in a container – Individual flows
  • 34. © 2015 IBM Corporation 14 July 2015 Step 5 – View statistics  Select the statistics view  Drill down to the problem flow  Start by comparing flows  Flow analysis view for most detail
  • 35. © 2015 IBM Corporation 14 July 2015 Step 6 – Compare flows  Compare flows to determine which one might be causing the problem  We can see that the BackendReplyApp flow has an average elapsed time of 1,000.9 milliseconds. It only has 1 active thread, and has processed 20 messages in the 20 second statistical snapshot period.  This matches the rate we see in JMSPerfHarness!
  • 36. © 2015 IBM Corporation 14 July 2015 Step 6 – Analyse the flow  Display historical flow details such as message rate, CPU and elapsed time  View all nodes within the flow to determine and sort by average elapsed and CPU times  The compute node Modify_CompletionTime seems to be a problem!  What does high elapsed time and low CPU time suggest the problem might be?
  • 37. © 2015 IBM Corporation 14 July 2015 Step 7 – Review the code  Having worked out which node is causing the problem  We can quickly see why the node is taking 1 second elapsed time but little CPU
  • 38. © 2015 IBM Corporation 14 July 2015 Problem found!!  1 second sleep in the compute node within the message flow is causing slow processing times and no CPU usage – Matches the observations at the start • Low CPU and low message rate  Unlikely to be so easy in future but slow service times, like slow synchronous web service invocations would have the same effect  If it was slow web service response times then allocate more additional instances to improve processing rate
  • 39. © 2015 IBM Corporation 14 July 2015 Summary of steps for this investigation  Use a systemic approach – Key steps used were 1.Ensure all components are started and the applications works as expected - Message flows, databases, external applications etc. 2.Start a load generator [JMSPerfharness in this case] 3.Look at activity - Is processing happening at the expected rate? - Is CPU usage as expected? - Is memory usage as expected? 4.If things do not seem as expected - Look for build up of messages - Poor service times 5.Enable and view statistics 6.Analyse statistics 7.Examine message flows  It is very important to – Use tools • System level and component level – Start at a high level – system level and then close-in on the problem
  • 40. © 2015 IBM Corporation 14 July 2015 Demonstration 2 Analysing a performance problem in the Java Compute Transform Scenario
  • 41. © 2015 IBM Corporation 14 July 2015 JavaComputeTransform message flows  Consists of one message flow – JavaCompute • Reads an XML message • Transforms to a different format using a Java Compute node JAVA_COMPUTE_IN JAVA_COMPUTE_OUT
  • 42. © 2015 IBM Corporation 14 July 2015 What is the problem we need to solve?  The problem is characterised by – Low message rate – High CPU usage at both system and Integration Server level – Sufficient messages on the input queue  Likely issue is one of high CPU usage in a message flow – But which flow and which node?
  • 43. © 2015 IBM Corporation 14 July 2015 Compare the flows  All of the elapsed and CPU time is in the JavaCompute message flow, so continue investigation here
  • 44. © 2015 IBM Corporation 14 July 2015 Finding the processing Node for investigation  The majority of the elapsed and CPU time within the flow is spent in the JavaCompute Node  What might cause this?  As this is a Java Compute Node continue investigation using the Java Healthcenter
  • 45. © 2015 IBM Corporation 14 July 2015 Find the Integration Server port for Java Health Center Environment variable: IBM_JAVA_OPTIONS=-Xhealthcenter Opens ports starting 1972, the Integration Server running the JavaComputeTransform scneario is using port 1974
  • 46. © 2015 IBM Corporation 14 July 2015 Alternate method for finding the port number > mqsilist DEMO -d2 ----------------------------------- BIP1286I: Integration server 'default' on integration node 'DEMO' is running. Number of message flows that are enabled to run: '4'. Number of applications that are enabled to run: '2'. Process ID: '7284' UUID: 'e1306ebc-3c3a-43c2-b18a-bbdb99e07d5c' Short description: '' Long description: '' BIP8071I: Successful command completion. > netstat -a -b -n -o [runmqlsr.exe] TCP [::]:1972 [::]:0 LISTENING 7352 [bipbroker.exe] TCP [::]:1973 [::]:0 LISTENING 7748 [biphttplistener.exe] TCP [::]:1974 [::]:0 LISTENING 7284 [DataFlowEngine.exe] TCP [::]:4417 [::]:0 LISTENING 7352 [bipbroker.exe] TCP [::]:49152 [::]:0 LISTENING 924
  • 47. © 2015 IBM Corporation 14 July 2015 Invoking the Java Health Center
  • 48. © 2015 IBM Corporation 14 July 2015 Attaching to the Integration Server JVM
  • 49. © 2015 IBM Corporation 14 July 2015 Connect to a port
  • 50. © 2015 IBM Corporation 14 July 2015 Connection complete and ready to analyse
  • 51. © 2015 IBM Corporation 14 July 2015 Analysis and Recommendations – CPU
  • 52. © 2015 IBM Corporation 14 July 2015 Analysis and Recommendations – Classes
  • 53. © 2015 IBM Corporation 14 July 2015 Analysis and Recommendations – Environment
  • 54. © 2015 IBM Corporation 14 July 2015 Analysis and Recommendations – Garbage Collection
  • 55. © 2015 IBM Corporation 14 July 2015 Analysis and Recommendations – I/O
  • 56. © 2015 IBM Corporation 14 July 2015 Analysis and Recommendations – Locking
  • 57. © 2015 IBM Corporation 14 July 2015 Analysis and Recommendations – Native Memory
  • 58. © 2015 IBM Corporation 14 July 2015 Analysis and Recommendations – Profiling
  • 59. © 2015 IBM Corporation 14 July 2015 The cause  Having worked out which node is causing the problem  We can quickly see why the node is consuming a lot of CPU  A call to the method bubble_sort() just before propagating out of the node is sorting the entire output message
  • 60. © 2015 IBM Corporation 14 July 2015 If you suspect there is a product problem  Identify the problem as best you can  Find the simplest test that recreates the problem  Collect the data identified in the Must Gather list – For IIB http://www-01.ibm.com/support/docview.wss?rs=849&uid=swg21209857 – For MQ: http://www-01.ibm.com/support/docview.wss?uid=swg21229861#MG6
  • 61. © 2015 IBM Corporation 14 July 2015 Summary  Wide range of tools available covering operating system and component performance – Expect to use multiple tools – After all it is important to understand what is happening at different levels – Demonstration has shown how to use the key tools for MQ and IIB to debug a problem  Practice before hand – Being familiar with the tools is a great help in a crisis – Learning a new tool and solving a crisis is not a good combination  Know your applications and systems – What is normal in terms of processing rate, CPU usage etc. – This information allows to know whether there is a problem and to what extent
  • 62. © 2015 IBM Corporation 14 July 2015 Additional Information  WebSphere Message Broker: Designing for Performance – http://www-01.ibm.com/support/docview.wss?rs=849&uid=swg24006518  WebSphere Message Broker: Message display, test & performance utilities (IH03) – http://www-01.ibm.com/support/docview.wss?rs=171&uid=swg24000637  IBM Monitoring and Diagnostic Tools for Java – Getting started with Health Center – http://www.ibm.com/developerworks/java/jdk/tools/healthcenter/getting_started.html  IBM Monitoring and Diagnostic Tools for Java – Health Center – http://www.ibm.com/developerworks/java/jdk/tools/healthcenter/  IBM Monitoring and Diagnostic Tools for Java – Knowledge Center – http://www-01.ibm.com/support/knowledgecenter/#!/SS3KLZ/SS3KLZ/welcome_tools_family.html
  • 63. © 2015 IBM Corporation 14 July 2015 Backup chart  MQ processes  Additional Instances usage and tuning
  • 64. © 2015 IBM Corporation 14 July 2015 WebSphere MQ V7 Processes Task Function AMQALMPX The checkpoint processor that periodically takes journal checkpoints. AMQZMUC0 Utility manager. This job executes critical queue manager utilities, for example the journal chain manager. AMQZXMA0 The execution controller that is the first job started by the queue manager. It handles MQCONN requests, and starts agent processes to process WebSphere MQ API calls AMQZFUMA Object authority manager (OAM) AMQZLAA0 Queue manager agents that perform most of the work for applications that connect to the queue manager using MQCNO_STANDARD_BINDING. AMQZLAS0 Queue manager agent. AMQZMUF0 Utility Manager AMQZMGR0 Process controller. This job is used to start up and manage listeners and services. AMQZMUR0 Utility manager. This job executes critical queue manager utilities, for example the journal chain manager. AMQZDMAA Deferred Message Processor AMQFQPUB Publish/subscribe process. AMQFCXBA Broker worker job. RUNMQBRK Broker control job. AMQRMPPA Channel process pooling job. AMQCRSTA TCP/IP-invoked channel responder.
  • 65. © 2015 IBM Corporation 14 July 2015 WebSphere MQ V7 Processes Task Function AMQCRS6B LU62 receiver channel and client connection. AMQRRMFA Repository manager for clusters. AMQCLMAA Non-threaded TCP/IP listener. AMQPCSEA PCF command processor that handles PCF and remote administration requests. RUNMQTRM Trigger monitor. RUNMQDLQ Dead letter queue handler. RUNMQCHI The channel initiator. RUNMQCHL Sender channel job that is started for each sender channel. RUNMQLSR Threaded TCP/IP listener. AMQXSSVN Shared memory servers. AMQRCMLA Channel MQSC and PCF command processor. AMQZTRCN Trace.  Number present at any time will vary – Dependent on configuration, applications running, etc. – Some will always be present, such as AMGZXMA0 (Execution Controller)
  • 66. © 2015 IBM Corporation 14 July 2015 Additional Instances usage and tuning  Integration Server level data contains the following data for each message flow in it: – MessageFlowName – TotalElapsedTime – MaximumElapsedTime – MinimumElapsedTime – TotalCPUTime – MaximumCPUTime – MinimumCPUTime – CPUTimeWaitingForInputMessage – ElapsedTimeWaitingForInputMessage – TotalInputMessages – TotalNumberOfTimeOutsWaitingForRepliesToAggregateMessages – TotalSizeOfInputMessages – MaximumSizeOfInputMessages – MinimumSizeOfInputMessages – NumberOfThreadsInPool – TimesMaximumNumberOfThreadsReached – TotalNumberOfMQErrors – TotalNumberOfMessagesWithErrors – TotalNumberOfErrorsProcessingMessages – TotalNumberOfCommits – TotalNumberOfBackouts  Fields NumberOfThreadsInPool and TimesMaximumNumberOfThreadsReached show for every message flow the number of additional instances allocated and the number of times they were all used – Use this data to determine if: • More additional instances are required • Too many are allocated
  • 67. © 2015 IBM Corporation 14 July 2015 Additional Instances usage and tuning  % Time Thread Pool Limit Reached = TimesMaximumNumberOfThreadsReached / TotalInputMessages