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Clustering J2EE with Jini
A Conversation with Sean Neville, Part I
by Bill Venners
October 21, 2002

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Summary
Sean Neville, previously the lead architect of Macromedia's JRun application server, talks with Bill Venners about JRun's object clustering architecture, and how Jini facilitated its implementation.

Although Macromedia architect Sean Neville currently works on Flash-related rich application products for both .NET and J2EE platforms, he originally joined Macromedia to work on the JRun application server. As enterprise architect of JRun 4, Neville was involved with implementing many aspects of the J2EE (Java 2 Platform, Enterprise Edition) specifications, including EJB (Enterprise JavaBeans) containers, JNDI (Java Naming and Directory Interface) providers, JDBC (Java Database Connectivity) managers, and JTA (Java Transaction API) monitors. Neville also represents Macromedia on the JCP (Java Community Process) Executive Committee. In this two-part interview, Neville describes how he used Jini to enable clustering in the JRun 4 application server. In this first installment, Neville describes the object clustering architecture he wanted for the app server, and how Jini facilitated it.

Bill Venners: How did you add clustering functionality to the JRun app server?

Sean Neville: I came to Allaire before it was acquired by Macromedia, where JRun was primarily known for servlets and JSPs (JavaServer Pages) -- the J2EE Web tier. Created at Live Software, JRun was the world's first commercial servlet engine. Allaire had acquired a small company called Valto that built an embedded EJB server and JTA/JTS transaction processor. Allaire's developers had linked those two together in the JRun 3.0 product, which went well. But for several reasons, tacking the two technologies together wasn't the perfect solution, and when I came aboard we decided that the web and enterprise engines really ought to be built together upon a single common base architecture. So in many ways, building JRun 4 involved a comprehensive re-architecture of JRun.

While there were plenty of existing JRun 3 features we wanted to extend in JRun 4 -- such as taking our simplicity and classic RAD features for web developers and extending them into the enterprise -- there were also several things missing that we knew customers needed. One thing missing in JRun 3, which sat fairly prominently among a long list of features we wanted to add to the next version, was object clustering. We wanted to use object clustering as the building block for EJB clustering, JMX MBean (Management-Bean) clustering, JNDI clustering, service clustering, and so on.

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