Performance Monitoring of Java
Web Service-based Applications
Włodzimierz Funika,
Piotr Handzlik
Lechosław Trębacz
Institute of Computer Science, AGH, Krakow, Poland
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Computer Science
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Agenda
 Review of existing monitoring systems
• JIMS (JMX)
• Lemon (CERN)
• Mercury
 Concept of a system monitoring WebServices
•
•
•
•
idea (J-OMIS, OCM-G)
metrics
feasibility study
architecture
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Monitoring System Funcionality
Monitoring of application is observing, analyzing
and manipulating the execution of the
application, which gives information about
threads, CPU usage, memory usage,
informations about methods and classes.
A particular case is monitoring of distributed
applications where an additional issue is the
performance analysis of nodes.
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Functional requirements
 Goals
• monitoring Web Services
• distinguishing which objects are interface of WS
• accessing information about Web Services on a node
 Communication related performance data
• size of SOAP message
• time of communication
• time of parsing a SOAP message
 Events
• receive request
• start/end of creating/parsing SOAP message
 Basis
• use the J-OMIS interface
• hold the existing functionality of J-OCM
• make use of experience with extending OMIS/OCM for parallel
applications, grid computing and Java distributed programming.
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JMX Infrastructure Monitoring System
JIMS is a monitoring service for GRID’s, exposing
the following parameters to the outside world:

CPU load,

Number of processes,

Memory usage,

Network interface utilization.
It uses Java Native Interface, Java Management
Extension, Dynamic Discovery Service and
Web Services
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JIMS Architecture
Cluster
JIMS
Node
RMI
JIMS
User
SOAP
SOAP
RMI
Node
Gateway
RMI
JIMS
Node
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LEMON (CERN)
Lemon is a scalable and flexible fabric monitoring system.
Distributed clients launch and control local sensors, schedule
measurements, collect data and send them to one or several
repositories. The system provides sensors for common
performance and exception monitoring.
Main parts of Lemon are:
 Monitoring Sensor measures data
 Monitoring Sensor Agent exists on all nodes and provides
transport to MR
 Monitoring Repository (MR) with backend to Oracle, MySQL, flat
file,…
 Alarm Broker – daemon for handling exceptions and
communication between alarm GUI and MR
 Round Robin Database – is used to store and to manipulate data
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Lemon architecture
Alarm GUI
Monitoring repository
backend
Alarm Broker
Monitoring repository
Monitoring Sensor
Agent
Monitoring
Sensor
RRD Tool Framework
USERS
Monitoring
Sensor
Node
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Lemon - Performance Monitoring
 In Lemon there are several types of data:
• Performance metrics:
• CPU usage, load averages, memory usage, disk
usage/performance, sockets, network, …
• Exceptions:
• High load, swap usage over 90%, service down,…
• Status information:
• Uptime, boot time, kernel version,…
• Heartbeat
 Data is gathered with different frequencies from
60s to 1 day/on boot
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Mercury (GridLab)
The architecture of Mercury Monitor is based on the Grid
Monitoring Architecture proposed by Global Grid Forum
(GGF), and implemented in a modular way.
The Mercury Monitor provides:
 monitoring data as metrics,
 pull and push model,
 performance monitoring and steering,
 monitoring of grid entities such as resources and
applications,
 emphasis on simplicity, efficiency, portability and low
intrusiveness.
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Mercury (GridLab)
The input of the monitoring system consists of
measurements generated by sensors.
Sensors are implemented as shared objects that are
dynamically loaded at run-time depending on
configuration and incoming requests for different
measurements.
Local monitor employs a set of sensors, implemented as
loadable modules, to collect information about the local
node, including host status, applications, etc., and
sends it to the main monitor.
The monitoring service sends requests to local monitors.
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Mercury architecture
Tool
MM
LM
LM
Sensor
Sensor
node 1
Sensor
Sensor
node 2
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Idea
Our monitoring system will be based on J-OMIS interface
and its implementation, J-OCM.
The work dates back to 1995 when OMIS, a monitor/tool
interface specification was released.
Java-bound OMIS is a monitor extension to OMIS for Java
applications intended to support the development of
Java distributed applications with on-line tools.
J-OMIS specifies three types of services:
 information (providing information about an object)
 manipulation (allowing to change the state of an object)
 event (trigger arbitrary actions whenever a matching
event takes place)
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J-OCM architecture
Tool 1
Tool 2
Node Distribution Unit
Local Monitor
Local Monitor
(RMI Ext, JVM Ext)
(RMI Ext, JVM Ext)
agent
agent
agent
agent
JVM
JVM
JVM
JVM
Node
Node
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J-OCM
Node Distribution Unit is part, which is still responsible for
distributing requests and assembling replies.
Local Monitor is a monitor process. LM’s extension
provides new services defined by J-OMIS, which control
Java Virtual Machine via agent. LM stores information
about the target Java application’s object, such as
JVMs, threads, classes, interfaces, objects, methods,
etc., referred to by tokens.
Agent uses JVM native interfaces such as JVM Profiler
Interface, JVM Debugging Interface, Java Native
Interface to access low-level mechanism for interactive
monitoring of JVM.
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Grid-enabled OMIS-based Monitor
The OCM-G is a decentralized, distributed system,
consists of two types of components:
 Service Managers (SM)
 Local Monitors (LM)
SMs reside permanently, one on each site of the Grid,
where are application processes to be monitored.
LMs execute OMIS request accepted from SMs and send
the results back. LMs handle only objects which are on
the same host. The LMs use OS mechanisms to control
the application processes.
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OCM-G Monitoring Services
The OCM-G provides:
 Debugging services (services for suspending/continuing
process, reading/writing processes’ memory, etc.)
 Performance analysis services, for example:
• services for detecting the beginnings and ends of function
calls,
• services for handling probes, which are used by the user
to define and detect arbitrary events in an application,
• services for the creation and management of counters
and integrators - efficient data structures which allow to
buffer and preprocess monitoring information in the
context of the application.
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Components of our system
It contains three kinds of components:
 application monitor (AM),
 node's local monitor (LM),
 service monitor (SM).
AM is embedded into the application (in our case Web Service
or application, which use Web Services). It is used to
perform monitoring activities in the context of the application.
It uses JVM Tool Interface, starting with JDK 1.5, for
monitoring JVM.
Node's local monitor is created on each node, where there are
Web Services to be monitored. LM receives requests from
Service monitor and transfers this request to AM. LM sends
a reply from AM to SM.
Service Monitor resides permanently and exposes the
monitoring services to tools.
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Metrics
Our monitoring system have two types of metrics:
 static – for WebServices, intended for observation and
analysis of SOAP messages sended to and from a Web
Service (requests and responses):
• number of WebServices on a node
• request time, transport time, cache access time, response
time, SOAP create/parsing time, computing time
• size of SOAP message (sent, received)
• usage (node resources)
 dynamic – oriented towards applications which use
WebServices:
• function call, service invocation
• number of exceptions (errors)
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Feasibility study
To build the Web Service we use Jakarta Tomcat and Apache
Axis.
Jakarta Tomcat is the servlet container:
 open source,
 reference platform,
 simplicity of use,
 universal tool for deploying web applications.
Apache Axis is an implementation of the SOAP protocol and
enables creation of web services on Tomcat.
J-OCM will be a low-level layer of the architecture extended by
a special extension for web services.
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Architecture
Tools
WebService
Service monitor
Service monitor
node's local monitor
node's local monitor
AM
AM
AM
AM
WebService
Tomcat+Axis
WebService
Tomcat+Axis
WebService
Tomcat+Axis
WebService
Tomcat+Axis
Node
Node
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Thank You !
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