IBM provides a number of free tools to assist in monitoring and diagnosing issues when running any Java application - from Hello World to IBM or third-party, middleware-based applications. This session introduces attendees to those tools, highlights how they have been extended with IBM middleware product knowledge, how they have been integrated into IBM’s development tools, and how to use them to investigate and resolve real-world problem scenarios Presented at the WebSphere Technical University 2014, Dusseldorf

1. A5: Introduction to the IBM
Monitoring and Diagnostic Tools
Chris Bailey
STSM, IBM Runtime Monitoring and Diagnostics

2. Please Note
IBM’s statements regarding its plans, directions, and intent are subject to change or withdrawal
without notice at IBM’s sole discretion. Information regarding potential future products is
intended to outline our general product direction and it should not be relied on in making a
purchasing decision.
The information mentioned regarding potential future products is not a commitment, promise,
or legal obligation to deliver any material, code or functionality. Information about potential
future products may not be incorporated into any contract. The development, release, and
timing of any future features or functionality described for our products remains at our sole
discretion
Performance is based on measurements and projections using standard IBM benchmarks in a
controlled environment. The actual throughput or performance that any user will experience
will vary depending upon many factors, including considerations such as the amount of
multiprogramming in the user’s job stream, the I/O configuration, the storage configuration, and
the workload processed. Therefore, no assurance can be given that an individual user will
achieve results similar to those stated here.
© 2014 IBM Corporation
2

3. Introduction to the Speaker
Chris Bailey
IBM Runtime Monitoring and Diagnostics Architect
 13 years experience developing and deploying Java SDKs
 1 years experience developing and deploying Node.js SDKs
3
 Recent work focus:
‒ Java and Node.js monitoring and diagnostics
‒ Java and Node.js integration into the cloud
‒ Highly resilient and scalable deployments
‒ Requirements gathering
 Contact Details:
‒ baileyc@uk.ibm.com
‒ http://www.linkedin.com/in/chrisbaileyibm
‒ http://www.slideshare.net/cnbailey/
‒ @Chris__Bailey

4. 4
What I hope to achieve in the next 60 mins
 Introduce the IBM tools for monitoring, debugging and diagnosing problems
 Understand the capabilities of each tool
 See how the tools can be extended tools with knowledge of applications or to build custom
tools
 See how IBM is building on top of the Java tools platform

5. Java Tools Overview

6. ● A free unified suite of tools to understand different aspects of applications
● Provides more than visualizations – also provides recommendations
● IBM supported and always current to latest IBM runtime levels
● Provides APIs to allow you to extend or create your own custom tools
6
IBM Monitoring and Diagnostic Tools for Java

7. 7
Where to use our tools
The IBM Monitoring and Diagnostic Tools fall into two groups
Reactive (Post-Mortem):
Information created at runtime and analyzed offline:
– Garbage Collection Memory Visualiser (GCMV)
– Memory Analyzer (MA)
– Interactive Diagnostic Dump Explorer (IDDE)
Proactive (Runtime):
Information created at runtime and analyzed immediately:
– Health Center

8. 8
How to get the tools: IBM Support Assistant (ISA)
A workbench for use by your technical personnel to:
 Expedite resolution of problems
 Automate collection of symptom
based “MustGather” data
 View and analyze collected data
 Leverage powerful tools to analyze
logs, JVM core and heap dumps,
config files, etc.

9. 9
How to get the tools: Eclipse Marketplace

10. Reactive Tools (Post-Mortem)

11. 11
Garbage Collector and Memory Visualizer (GCMV)
Analyses and visualizes:
● Process and system memory usage
● Java heap memory usage and performance
Compares multiple logs in the same plots
and reports
Many data views
 Reports
 Graphs
 Tables

12. 12
Garbage Collector and Memory Visualizer (GCMV)
Process and system memory usage:
#!/bin/sh
PID=$1
INTERVAL=3
# Echo time at start of monitoring.
echo timestamp = `date +%s`
# Echo the interval frequency.
echo "ps interval = $INTERVAL"
# Run the system command at intervals.
while ([ -d /proc/$PID ]) do
ps -p $PID -o pid,vsz,rss
sleep $INTERVAL
done

13. 13
Garbage Collector and Memory Visualizer (GCMV)
Process and system memory usage:
#!/bin/sh
PID=$1
INTERVAL=3
# Echo time at start of monitoring.
echo timestamp = `date +%s`
# Echo the interval frequency.
echo "ps interval = $INTERVAL"
# Run the system command at intervals.
while ([ -d /proc/$PID ]) do
ps -p $PID -o pid,vsz,rss
sleep $INTERVAL
done

14. 14
Garbage Collector and Memory Visualizer (GCMV)
Process and system memory usage:
#!/bin/sh
PID=$1
INTERVAL=3
# Echo time at start of monitoring.
echo timestamp = `date +%s`
# Echo the interval frequency.
echo "ps interval = $INTERVAL"
# Run the system command at intervals.
while ([ -d /proc/$PID ]) do
ps -p $PID -o pid,vsz,rss
sleep $INTERVAL
done
Java heap memory usage and performance
-verbose:gc
-Xverbosegclog:[DIR_PATH][FILE_NAME]
-Xverbosegclog:[DIR_PATH][FILE_NAME],X,Y
where:
X is the number of files to
Y is the number of GC cycles a file should contain

15. 15
Performance Overhead of Verbose:GC
Benchmark: DayTrader with 50 clients:
WebSphere 8.5.5 and IBM Java 7 SR7 on POWER 7
4 CPU machine, running at 100% utilization
Throughput Runs Min Max Stddev
Without verbose:gc 3743.953 8 3637.019 3855.971 71.6304964862
4000
3500
3000
2500
2000
1500
1000
500
0

16. 16
Performance Overhead of Verbose:GC
Benchmark: DayTrader with 50 clients:
WebSphere 8.5.5 and IBM Java 7 SR7 on POWER 7
4 CPU machine, running at 100% utilization
Throughput Runs Min Max Stddev
Without verbose:gc 3743.953 8 3637.019 3855.971 71.6304964862
With verbose:gc 3748.779 8 3654.9945 3877.9495 83.5641336842
4000
3500
3000
2500
2000
1500
1000
500
0

17. 17
Performance Overhead of Verbose:GC
Benchmark: DayTrader with 50 clients:
WebSphere 8.5.5 and IBM Java 7 SR7 on POWER 7
4 CPU machine, running at 100% utilization
Throughput Runs Min Max Stddev
Without verbose:gc 3743.953 8 3637.019 3855.971 71.6304964862
With verbose:gc 3748.779 8 3654.9945 3877.9495 83.5641336842
4000
3500
3000
2500
2000
1500
1000
500
0
0.1289% ?

18. 18
Memory Analyzer (based on Eclipse MAT)
Provides deep insights into Java Heaps
Powerful analytic capabilities to explore
heap sections, including “deep” and
“shallow” cost
Path to GC Roots
Provides the reference chain that
prevents an object being garbage
collected
Eclipse Equinox bundle explorer (works
with OSGI bundles for WebSphere)

19. Memory Analyzer Loads Data from Dumps
Processes PHD Heapdumps, HPROF Heapdumps and OS System Dumps
System dump writing speed is relatively quick:
~10s per GB providing physical memory is available
Otherwise dictated by disk write speed
Can be minimized by good configuration of system
System dumps compress very well:
Usually to 10% of original size
0 2000 4000 6000 8000 10000 12000 14000 16000
© 2014 IBM Corporation
350
300
250
200
150
100
50
0
Linux 64 bit PPC
Same Disk
RAM Disk
GB Netw ork
Core Size (MB)
Time to Generate (s)

20. 20
Memory Analyzer overview cont…
Overview:
Overview of the heapdump including size and total
number of objects.
Provides links to continued analysis
Path to GC Roots:
Provides the reference chain that prevents
an object being garbage collected.
Dominator Tree grouped by Class Loader:
Lists the biggest objects using a “keep alive tree”.
Grouping by Class
Loader limits the analysis to a single application in a
JEE environment

21. Extensions for Memory Analyzer
Additional capabilities for debugging generic Java Applications
21
Extensions currently available for
 IBM Java SE runtime
 WebSphere Application Server
 CICS Transaction Gateway
Using these extensions will enable
 Visualization of application and IBM product code
 Confirm configuration of IBM Products
 Inspect size and contents of IBM products
Extensions are made available through ISA or installed directly into the Memory
Analyser application

22. 22
Interactive Diagnostic Data Explorer (IDDE)
The IBM JRE Dump artefacts provide insight into the health and integrity of your
application by providing a graphical view of a system dump file
Provides access to detailed
information contained dumps
Allows collaboration and user
defined extensions
Community of extensions and
add-ons
Ability to run Memory Analyzer
Extensions
Also supports Node.js

23. Proactive Tools (Runtime)

24. IBM Monitoring and Diagnostic Tools for Java™ Health Center
24
Answers vital questions:
 What is my JVM doing? Is everything ok?
 Why is my application running slowly? Why
is it not scaling?
 Am I using the right options?
Live monitoring with very low overhead
Diagnose potential problems, with
recommendations
Works at the JVM level, no domain-specific
(e.g. J2EE) information
Suitable for all Java applications
Special view for WebSphere Real Time
 Helps identify outlier events (class load,
compilation, GC, application method)

25. 25
Enabling Health Center
 Health Center enabled using the command line:
java -Xhealthcenter Heartbeat
 Health Center enabled at runtime using “Late Attach” to a running process:
java Heartbeat
java -jar healthcenter.jar
java -jar healthcenter.jar -PID=<pid>

26. Machine and Process CPU Usage
• Visualizes heap usage and gc pause times over time
• Identifies memory leaks
• Suggests command-line and tuning parameters
• Same recommendation logic as GCMV
26
Health Center Data: Operating System and Machine
Native Memory
• Detect native memory leaks in application
• Determine if external forces are using more memory
• View components using the most native memory
Environment reporting
• Detects invalid Java options
• Detects options which may hurt performance or
serviceability
• Useful for remote diagnosis of configuration-related
problems

27. 27
Health Center Data: Java Runtime
Garbage Collection visualization
 Visualizes heap usage and gc pause times over time
 Identifies memory leaks
 Suggests command-line and tuning parameters
 Same recommendation logic as GCMV
Object Allocation Profiling
 Understand what types of data is being allocated and
at what rate
 Determine which code is allocating data
Threads view
 List of current threads and states
 Number of threads over time
 See contended monitors

28. 28
Health Center Data: Java Runtime
Class loading visualization
 Shows all loaded classes
 Shows load time
 Identifies shared classes
 Live class histogram information
I/O
 Monitor application file open/close events as they
occur
 Lists currently open files

29. 29
Health Center Data: Application
Method Profiling
 Always-on profiling shows application activity
 Identifies the hottest methods in an application
 Full call stacks to identify where methods are being
called from and what methods they call
 No byte code instrumentation, no recompiling
Java Lock Profiling
 Always-on lock monitoring
 Quickly allows the usage of all locks to be profiled
 Helps to identify points of contention in the
application that are preventing scaling
Live control of application
 Trigger dumps
 Enable verbosegc collection

30. 105
100
95
90
85
Measured using WebSphere App Server and the DayTrader benchmark with 50 clients
Running WAS 8.5.5, IBM Java 7 SR5, AIX 7.1, POWER7
Throughput determined by number of completed transactions on 4 saturated CPUs
30
Health Center overhead
80
100
Baseline
Network Client
Headless
Headless with ZIP

31. 105
100
95
90
85
Measured using WebSphere App Server and the DayTrader benchmark with 50 clients
Running WAS 8.5.5, IBM Java 7 SR5, AIX 7.1, POWER7
Throughput determined by number of completed transactions on 4 saturated CPUs
31
Health Center overhead
80
100.4
Baseline
Network Client
Headless
Headless with ZIP

32. 105
100
95
90
85
Measured using WebSphere App Server and the DayTrader benchmark with 50 clients
Running WAS 8.5.5, IBM Java 7 SR5, AIX 7.1, POWER7
Throughput determined by number of completed transactions on 4 saturated CPUs
32
Health Center overhead
80
99.01
Baseline
Network Client
Headless
Headless with ZIP

33. 105
100
95
90
85
Measured using WebSphere App Server and the DayTrader benchmark with 50 clients
Running WAS 8.5.5, IBM Java 7 SR5, AIX 7.1, POWER7
Throughput determined by number of completed transactions on 4 saturated CPUs
33
Health Center overhead
80
96.99
Baseline
Network Client
Headless
Headless with ZIP

34. Access Health Center data with the API
The 2.2 release of Health Center provides an API
● Allows developers to access Health Center data in their applications
// Create the connection object:
ConnectionProperties conn1 = new ConnectionProperties("localhost", 1973);
// Connect to the Health Center agent, using the previous connection
// settings:
HealthCenter hcObject = HealthCenterFactory.connect(conn1, true);
// Get garbage collection data and print:
GCData gcData = hcObject.getGCData();
System.out.println("GC Mode is " + gcData.getGCMode().toString());

35. RAD v9 Usage of Health Center Data
 Enable “Health Center Agent”
 Select “Sample based profiling”
 Method CPU usage collected
 Displayed in real time
 Accessed using API

36. IBM Support Assistant 5

37. Browser Browser
Browser Browser
37
ISA 5.0 Team Server
Server-based model
Install once - shared by many team
members via browser
Web 2.0 browser interface
Remote execution of PD tools
Off-load analysis processing
Collaboration on PD
Case Management
Tool Management
Single-user option available
Available at www.ibm.com/software/support/isa
ISA
Team Server
IBM Support Assistant (ISA) 5.0

38. Automation of Upload of Data to ISA 5.0
■ ISA Provide a REST interface for some of its functions:
■ Case creation:
curl --user user1:user1password -X POST -H Content-Type:application/x-www-form-urlencoded
-v -o /home/dumps/curl.log --url http://myISA5TeamServer.mydomain.net/rest/1/tickets -d
"summary={case summary}&description={case description}"
■ File upload:
curl --user user1:user1password -X POST -v -k -o /home/dumps/curl.log -F file=@'{}' --url
http://myISA5TeamServer.mydomain.net/rest/1/files/${caseno}/file_upload?path=/${caseno}/
■ Can be combined with IBM JDKs “-Xdump” options to run automatically:
-Xdump:tool:events=systhrow,filter=java/lang/OutOfMemoryError,exec="dumpUpload.sh %pid”
● Where dumpUpload.sh contains:
find . -name '*$1*' -exec curl -X POST -v -k -o curl.log -F file=@'{}' --url
https://myISAServer.mydomain.net:10943/rest/1/files/0001/file_upload?path=/0001/ ;
© 2014 IBM Corporation 38

39. Demo Time

40. 40
Summary
 IBM is building a set of integrated monitoring and diagnostic tools
 Taking a ground up approach
 Working across teams, products and brands
 Providing a consistent user experience
 What Next??

41. 41
Questions?

42. Your feedback is valuable - please complete your session
or lab evaluation!
Session number
[A5]
Provide your evaluations by:
Evaluation forms:
Fill out a form at the end of each session
Paper forms are located in each of the session or lab rooms
Place the completed form in the tray as you exit the room
- Or –
Complete the session survey on Event Connect Portal:
ibmeventconnect.eu/euxdx
Select Sessions, then Session Finder, and complete the
survey

43. 43
Where to find more information
 IBM Monitoring and Diagnostic Tools for Java™ on developerWorks
http://www.ibm.com/developerworks/java/jdk/tools/
 IBM Support Assistant (ISA)
http://www.ibm.com/software/support/isa
 Email javatool@uk.ibm.com

44. Visit WASdev.net for downloads and other resources
WASdev.net

45. For Additional Information
© 2014 IBM Corporation
 IBM Training
http://www.ibm.com/training
 IBM WebSphere
http://www-01.ibm.com/software/be/websphere/
 IBM developerWorks
www.ibm.com/developerworks/websphere/websphere2.html
 WebSphere forums and community
www.ibm.com/developerworks/websphere/community/
45