The term "clustering" actually refers to a number of different technologies and configurations.

When many people hear the words "clustering" or "server cluster," they think of high performance groups of computers used for scientific research. However, this is just one of the types of clustering available. The basic idea behind the "performance clustering" approach is to make a large number of individual machines act like a single very powerful machine. This type of cluster is best applied to large and complex problems that require tons of computing horsepower. Applications such as weather prediction, astronomy, and cryptographic research are prime candidates for high-performance clusters.

A second type of clustering technology allows a network of servers to share the load of traffic from clients. By load balancing this traffic across an array of servers, access times improve and reliability increases. Additionally, since many servers are handling the work, one failure will not cause a catastrophic breakdown. This kind of service has tremendous value to companies with extremely high-traffic Web sites.

The last major type of clustering involves having the servers act as live backups of each other. This is called "high availability clustering" (HA clustering) or "redundancy clustering." By constantly tracking the performance and stability of the other servers, a high availability cluster allows for greatly improved system uptimes. This can be crucial in high traffic e-business sites and for other mission critical applications. Load balancing and high availability clusters share many common components, and some clusters make use of both types of clustering.

By sharing a common data source, the backup server can instantly take over for the primary server in case of failure. If the backup server doesn't receive a pulse signal from the primary server, it will instantly reconfigure its network interface and take over the traffic load. For extra redundancy, the data source can also be set up as a cluster.