J2EE Application Server Deployment and Performance Optimization for Enterprise

Application Service

Thesis presentation19.05.2009

Author: Xiaoyang Wang Supervisor: Professor Jukka Manner

Instructor: Pasi Salonen

Content

Background Research aspects Research methods Role of application server in three-tier infrastructure J2EE application server Implementation (Setup) Test cases and optimization Results Conclusion Future research

Background

Conducted by International Business Machines Corp. (IBM) in Helsinki

Topic J2EE application server Deployment setup Performance optimization

Application Server J2EE application server solution Microsoft solution Open source solution

IBM WebSphere Application Server (WAS) is the representative product researched in this thesis.

Research aspects

What is the role of application server in the infrastructure for enterprise application?

How should the application server be deployed and managed?

What affects the performance of the application server?

How should the performance be optimized?

Research methods Literature study

Web-based three-tier architecture Application Server->J2EE application Server->WAS

Implementation: Network structure design Environment setup Test cases

Executed test cases: Single application server

Web container pool size JVM heap size JDBC connection pool size

Integrated environment Comparison between “single” and “integrated”

environment

Role of application server in three-tier infrastructure

Web-based three-tier architecture

Separates applications from the underlying-based mechanism (operating system and database)

Reusability of business logic and components

High Performance (Transaction service, Messaging service, High availability, etc.)

Reliability (Failover, Hot Deployment)

J2EE application server Java standardization

J2EE services & technologies: JSP and Servlet containers, EJB containers, Java Database Connectivity (JDBC), Java Naming and Directory Interface (JNDI), Java Transaction Service / Java Transaction API (JTS /

JTA), Java Messaging Service (JMS)

Compatibility (cross-platform)

Portability (write once, run anywhere)

Implementation (Setup) 1/3

Front-end servers Caching proxy - IBM Edge components Web server with Plugin- IBM Http Server (IHS)

Middle server J2EE application server - WebSphere Application Server

(WAS) Back-end

LDAP Database – Cloudscape and IBM DB2

Implementation (Setup) 2/3

Cell An administrative domain contains a grouping of nodes

Dmgr AppServer instance for management the cell Administrative onsole

TestNode Nodeagent

bridge between the Dmgr and AppServer instance in the same node

Server1 AppServer instance where application deployed

TestCellTestNode

Dmgr Nodeagent Server1

Implementation (Setup) 3/3 Application ”PlantsByWebSphere”– Sample application built-

in WAS

35 requests 28 ShoppingServlet requests 3 HTML requests 3 AccountServlet requests 1 login JSP request

Test cases and optimization

Scenario 1 – Single application server Web container pool size JVM

Heap size Garbage collection

JDBC connection pool size

Scenario 2 – Integrated environment with other servers Comparison the different performance between two

scenarios.

Successful test requirement Error rate <= 0.11%

Results – Web container pool size

JVM heap size Min = 64 MB Max = 1024 MB

Largest threads =276

Results – JVM heap size

JVM heap size Min = 64 MB Max = 1024 MB

Heap size = 177MB

initialHSmaxHSGCCUsaveRTminRTmaxRT ervalGCintaverageGC

Results – JDBC connection pool size

Default

After optimized

Results – Scenario1 vs. Scenario2

Caching proxy (default) MaxActiveThreads = 100 MaxPersistRequest = 5

HIS (default) MaxClients = 600

Conclusion

The statistics from the test cases meet the purpose of the thesis

Approaches could be referred. However, the optimal value of the parameters are only for the specified case we have in the thesis.

Future research Optimization for messaging services. The performance tuning between

remote database and application server.

The network topology could be optimized as well.

Improvement on load balance, reliability, security and so on.