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In this article we will gain a foundational understanding of clustering, clustering methods, and important cluster services. Because clustering approaches vary across the industry, we will examine the benefits and drawbacks of each approach. Further, we will discuss the important cluster-related features to look for in an application server.
To apply our newly acquired clustering knowledge to the real world, we will see how HP Bluestone Total-e-Server 7.2.1, Sybase Enterprise Application Server 3.6, SilverStream Application Server 3.7, and BEA WebLogic Server 6.0 each implement clusters.
In Part 2 of this series, we will cover programming and failover strategies for clusters, as well as test our four application server products to see how they scale and failover.
J2EE application server vendors define a cluster as a group of machines working together to transparently provide enterprise services (support for JNDI, EJB, JSP, HttpSession and component failover, and so on). They leave the definition purposely vague because each vendor implements clustering differently. At one end of the spectrum rest vendors who put a dispatcher in front of a group of independent machines, none of which has knowledge of the other machines in the cluster. In this scheme, the dispatcher receives an initial request from a user and replies with an HTTP redirect header to pin the client to a particular member server of the cluster. At the other end of the spectrum reside vendors who implement a federation of tightly integrated machines, with each machine totally aware of the other machines around it along with the objects on those machines.
In addition to machines, clusters can comprise redundant and failover-capable:
Regardless of how they are implemented, all clusters provide two main benefits: scalability and high availability (HA).
Scalability refers to an application's ability to support increasing numbers of users. Clusters allow you to provide extra capacity by adding extra servers, thus ensuring scalability.