A165 tools for java and javascript

IBM S oftware Univers ity 2015
WebS phere Tec hnic al Univers ity PL US
Mobile, BPM, Cloud, Integration, Application
Platform, IBM z Systems and Digital Experience
13 – 16 October 2015|Dublin, Ireland
A165
Introduction to the IBM Monitoring
and Diagnostic Tools for Java and
Javascript
Toby Corbin

© 2015 IBM Corporation 3
Java JavaScript Both
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PercentageofAudience
What languages do you use?

Health Center
Other performance tools
GCMV
Other GC tools
Memory Analyzer
Other Memory tools
IDDE
Other debugger tools
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What tools do you use?


Toby Corbin
IBM Runtime Monitoring and Diagnostics Architect
- 14 years working with Java and JVM technologies
- 8 years working with monitoring and
diagnostic tooling

Recent work focus:
- Java monitoring, diagnostics and troubleshooting
- Java integration into the cloud
- JavaScript monitoring, diagnostics and troubleshooting

My contact information:
- corbint@uk.ibm.com
Introduction to the Speaker

Agenda
●
Introduce the IBM tools for monitoring, debugging and diagnosing problems
●
Provide understand of the capabilities of each tool
●
Show how the tools can be used to solve real problems

8
●
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
IBM Monitoring and Diagnostic Tools

9
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)
– Interactive Diagnostic Dump Explorer (IDDE)
– Memory Analyzer (MA)
Proactive (Runtime):
Information created at runtime and analyzed immediately:
– Health Center
When to use the tools
Available for Java
Available for Node.js

10
How to get the tools:
Available from multiple routes:
●
Eclipse Marketplace
●
Liberty Repository
●
IBM Support Assistant

11
Reactive Tools
(Post-Mortem)

Offline memory monitoring capability for:
●
Java and Node.js Garbage Collection (GC)
●
Operating System memory usage
Provides ability to:
●
Monitor process and system memory usage
●
Identify application memory usage and leaks
●
Analyse and tune GC performance
Visualization provided via Eclipse Client UI
●
Available from Eclipse Marketplace
●
Available from Liberty Repository
●
Available from IBM Support Assistant
Headless/batch mode
●
Run automated analysis
Garbage Collection and Memory Visualizer (GCMV)

GCMV Capabilities
Available for Java
Garbage Collection
Garbage Collection performance and memory usage
Graphical visualization including cropping and zooming
Statistical analysis of data
Recommendations for tuning garbage collection
Memory leak detection
Memory Usage
Process and System memory usage
Graphical visualization including cropping and zooming
Statistical analysis of data
Memory leak detection

#!/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
#!/bin/sh
PID=$1
INTERVAL=3
echo "svmon interval = $INTERVAL"
while ([ -d /proc/$PID ]) do
svmon -r -m -P $PID
sleep $INTERVAL
done
#!/bin/sh
PID=$1
INTERVAL=3
echo "svmon interval = $INTERVAL"
while true ; do
ps -p $PID -o pid,vsz
sleep $INTERVAL
done
Run perfmon
Select “Performance Logs and Alerts > Counter Logs”
Create a log file name, eg. Memory Usage
Click “Add Counters...”
Select “Process > Virtual Bytes” from Counters
Select you process from Instances
Select “Add” and “Close”
Click “Log Files” and “Text File (Comma delimited)”
Select “Schedule” and then “Manually” in Start log
Start logging by clicking “Start”
Linux AIX
Windows zOS
Note: Scripts are provided in the Help documentation
Collecting Process Memory Data

-Xverbosegclog:[FILE_NAME] --trace_gc
--trace_gc_nvp
--trace_gc_verbose
Java : IBM SDKs Node.js
Java: Oracle and Open JDKs
Note: Scripts are provided in the Help documentation
Log verbose GC data to a given file name
-Xverbosegclog:[FILE_NAME],[FILES],[ENTRIES]
Log verbose GC data to a rolling number of files, each
With a maximum number of GC cycle entries
-Xverbosegclog:vgc.%Y%m%d.%H%M%S.%pid.txt
Log data to a file name including token substitutions
-XX:+PrintGCDateStamps
-XX:+PrintGCDetails
-XX:+PrintGCTimeStamps
-Xloggc:[FILE_NAME]
Log verbose GC data to a given file name
Enable collection of date and time stamped GC data
Log detailed verbose GC data to the console
--trace_gc
--trace_gc_nvp
--trace_gc_verbose
[APPLICATION] > [FILE_NAME] 2>&1
Capture the console to a given file name
Collecting Garbage Collection Data

Performance Overhead (IBM SDK for Java)
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
0
500
1000
1500
2000
2500
3000
3500
4000
Throughput Runs Min Max Stddev
Without verbose:gc 3743.953 8 3637.019 3855.971 71.6304964862
With verbose:gc

Performance Overhead (IBM SDK for Java)
0
500
1000
1500
2000
2500
3000
3500
4000
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
0.1289% ?

GUI based, cross platform, dump debugger for use with
●
IBM SDKs for Java since Java 5
●
IBM SDKs for Node.js since v 1.1.0
●
Analyse crash dumps for root cause
●
View field and values store in objects
●
Understand the state of your application
●
●
Available from Liberty Repository
●
Supports analysis of dumps created on:
●
AIX, Linux, Windows or z/OS
Provides local or remote analysis using server/client
Interactive Diagnostics Data Explorer (IDDE)

IDDE: Example Process Commands
Available for Java
Search Memory
find <type> <value> <address> find a value in memory
findnext find the next instance
findall <type> <value> <address> find all instances
View Memory
ranges list available memory ranges
hexdump <address> dump memory as hex and ascii
<struct> <address> format memory as a struct
View Threads
threads list all threads
stack <thread> show stack trace for thread

IDDE: Example Runtime Commands
Available for Java
Runtime Overview
javaoverview Java information nodeoverview Node.js information
Memory Overview
javameminfo Java Memory summary jsmeminfo Node.js memory summary

IDDE: Example Object Commands
Available for Java
List Objects
javaobjects List Java objects jslistobjects List Node.js objects
Print Objects
javaobject Print Java object jsobject Print Node.js object

Generating Dump Files
Available for Java
Operating System Mechanisms
●
AIX: gencore
●
Linux: gcore
●
Windows: userdump.exe or Task Manager
●
z/OS SVCDUMP/Console Dump
Runtime Mechanisms
Java Dump Engine
Java Trace Engine
Java Dump API
Health Center
--abort-on-uncaught-exception

© IBM Corporation٢٠١٥ ٢٣
0 2000 4000 6000 8000 10000 12000 14000 16000
0
50
100
150
200
250
300
350
Linux 64 bit PPC
Same Disk
RAM Disk
GB Network
Core Size (MB)
TimetoGenerate(s)
Generating Dump Files
Dump writing speed dominated by IO performance:
~10s per GB providing physical memory is available
Otherwise dictated by disk write speed
Can be minimized by good configuration of system:
●
Memory assigned to file caching
●
Use of ramdisks
System dumps compress very well:
Usually to 10% of original size

24
Memory Analyzer
Application Memory Analysis Capability
●
Analyses dump files
●
Identify application memory leaks
●
Optimize memory usage
●
●
Vizualization provided by Web UI
●
Available in IBM Support Assistant
Headless/batch mode
●
Run automated analysis

25
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
Memory Analyzer Capabilities: General

26
Additional capabilities for debugging generic Java Applications
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
Memory Analyzer Capabilities: Product Specific

Proactive Tools
(Runtime)

Very low overhead live monitoring capability for Java and Node.js
●
Pre-installed in IBM SDKs for Java since Java 5
●
Pre-installed in IBM SDKs for Node.js since v 1.1.0.10
Provides insight into runtime and application execution, including
●
Memory and CPU usage
●
Garbage Collection
●
Application execution
●
●
Data access API provided
●
Allows creation of custom monitoring tools
●
Full API Javadoc available
IBM Monitoring and Diagnostics: Health Center

Available for Java
Memory Utilization
Detect native memory leaks in application
Determine if external forces are using more memory
View components using the most native memory
Environment
Hardware and Operating System Configuration
Process environment and configuration
Highlights incorrect or non-standard configurations
CPU Utilization
Visualizes process CPU usage over time
Visualizes system CPU usage over time

Available for Java
Object Allocations
Understand types of data being allocated
Determine which code is allocating data
Threads
List of current threads and states
Number of threads over time
See contended monitors
Garbage Collection
Visualizes heap usage and GC pause times
Identifies memory leaks
Suggests command-line and tuning parameters

Available for Java
Lock Profiling
Always-on lock monitoring
Allows the usage of all locks to be profiled
Identifies points of contention that affect scaling
Live runtime control
Trigger dumps
Enable additional data collection
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

IBM SDK for Java:
Using Command line:
Add -Xhealthcenter option
Using “late attach”
java -jar healthcenter.jar -PID=<pid>
Starting Health Center
IBM SDK for Node.js:
Command line:
Use node-hc executable
Programmatically:
require(“/usr/local/lib/node_modules
/healthcenter”).start()
Available for Java

Point to Point
Using JMX connection directly to application
Publish/Subscribe
Using MQTT messages and a pub/sub broker
Deployment Modes
Available for Java
Pub/Sub Broker
Topic namespace:
/ibm/healthcenter
/<namespace>/<agent_id>/<datatype>
Node.js
Application
Liberty
Java (J9)
Application
Liberty
Java (J9)
Application
JMX
MQTT
MQTT
MQTT
MQTT
MQTT

Performance Overhead (Java)
80
85
90
95
100
105
100
Baseline
Network Client
Headless
Headless with ZIP

80
85
90
95
100
105
100.4
Baseline
Network Client
Headless
Headless with ZIP

80
85
90
95
100
105
99.01
Baseline
Network Client
Headless
Headless with ZIP

80
85
90
95
100
105
96.99
Baseline
Network Client
Headless
Headless with ZIP

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());
Access Health Center data with the API

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

41

IBM is building a set of integrated monitoring and diagnostic tools
– Taking a ground up approach, integrating with the runtime

Working to make these common across runtimes
– Remove the need to “learn” how to monitor and diagnose new languages

What Next??
Summary

Toby Corbin
Thank you very much.
IBM
corbint@uk.ibm.com

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