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WebLogic Clustering - Failover,and Load Balancing

Bryan Ferrel and Ramarao DesarajuCS 522

Computer CommunicationsDecember 4, 2002

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Introduction

What is Clustering? Close cooperation of two or more replicated servers to

ensure fast, continuous service to users.

Clustering must provide the following: No bottlenecks to scaling No single point of failure Transparency to application developers Single-system image to administrators

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Clustering

Benefits of Clustering High-Availability and Scalability

Key Capabilities of Clustering Failover

New object can take over for the failed object Load Balancing

Even distribution of jobs

Challenges Replication without increasing load Propagating changes to servers participating in the

cluster

Complex setup

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WebLogic Clustering

What is WebLogic? J2EE Application Server that is a platform for

developing distributed applications

A hosting environment for EJBs Provides several services such as: JMS, JNDI, JDBC,Transaction control, etc

WebLogic Clustering

Consists of multiple copies of the WL Server workingtogether so that there are alternative objects to do thesame job.

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WebLogic Clustering

Types of objects that can be clustered Servlets and JSPs EJBs RMI objects JMS destinations JDBC Connections

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Replica-aware stubs created at compile time Contains load-balancing algorithm

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Typical Clustered Multi-Tier Architecture

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Load Balancing

Algorithms used: Round-Robin

Cycles through instances in order

Weight-Based Allocation of requests based upon relative weights

Random

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What we did

Set up a WL server in a clustered environment 2 Nodes and 1 Admin. server

Deploy an EJB Stateful Session Bean that is replicated on the cluster

Simulate the action of multiple clients Remote Java client that creates multiple threads and

sends off requests in quick succession

Server logs client requests Used for gathering statistics

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Test Setup

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Results

Most effective algorithm was Round-Robin Weight-based is useful when there are differences

in the cluster hardware

Degenerates to Round-Robin when using identicalweights in the cluster.

Random was close to Round-Robin Scalability

1 server results in cacheful exceptions Adding another node to the cluster removed this

problem with identical clients

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0250500750

10001250150017502000225025002750300032503500375040004250450047505000525055005750

60006250650067507000

Round-Robin Weight-Based Random

Algorithm

R e q u e s

t s p e r

R u n Dante-1

Dante-2Dante-3

DanteCl2-1DanteCl2-2DanteCl2-3

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References

Girdley, Woollen, Emerson, J2EE Applicationsand BEA WebLogic Server, Prentice Hall, UpperSaddle River, NJ, 2002

On Line References: http://e-docs.bea.com/wls/docs70/cluster/ http://www.getgamma.com/wlscert/wls6clustering.html http://www.distributedobjex.com/resources/techbriefs_

BEA.htm http://java.sun.com/j2ee

http://e-docs.bea.com/wls/docs70/cluster/http://www.getgamma.com/wlscert/wls6clustering.htmlhttp://www.distributedobjex.com/resources/techbriefs_BEA.htmhttp://www.distributedobjex.com/resources/techbriefs_BEA.htmhttp://www.distributedobjex.com/resources/techbriefs_BEA.htmhttp://www.distributedobjex.com/resources/techbriefs_BEA.htmhttp://www.getgamma.com/wlscert/wls6clustering.htmlhttp://e-docs.bea.com/wls/docs70/cluster/http://e-docs.bea.com/wls/docs70/cluster/http://e-docs.bea.com/wls/docs70/cluster/