Clusters
High-availability (HA) clusters
HA(High Availability Clusters ) The name itself gives us idea, the purpose is to provide availability of a particular service with no/minimal downtime at any given point of time. It is also called as FAILOVER CLUSTERS. Basically it works using 2 nodes one is active and one is passive but the data on both the nodes is always replicated i.e. it is always same so in case the primary node goes down for any reason the secondary node takes it over and provides the same services, In the mean time we can work over the primary and bring it back again. HA cluster implementations attempt to use redundancy of cluster components to eliminate single points of failure.
Load-balancing clusters
Load balancing is almost a special subset of the high availability. The idea is to create a set up where you have multiple systems all serving the same service at the same time because the demand for the service is more than a single server can handle. Load-balancing is when multiple computers are linked together to share computational workload or function as a single virtual computer. Logically, from the user side, they are multiple machines, but function as a single virtual machine. Requests initiated from the user are managed by, and distributed among, all the standalone computers to form a cluster. This results in balanced computational work among different machines, improving the performance of the cluster systems.
High Performance Computing/ Compute clusters
Also known as Beowulf clusters, the idea here is to hook a bunch of regular computers up to act in a coordinated way so that they can do calculations or jobs that are bigger than any single computer. In this way, you can build a supercomputer using Commodity Off The Shelf (COTS) hardware. These systems do everything from calculating the origins of the universe to modeling weather to rendering movie special effects.
Often clusters are used primarily for computational purposes, rather than handling IO-oriented operations such as web service or databases. For instance, a cluster might support computational simulations of weather or vehicle crashes. The primary distinction within computer clusters is how tightly-coupled the individual nodes are. For instance, a single computer job may require frequent communication among nodes - this implies that the cluster shares a dedicated network, is densely located, and probably has homogenous nodes.The other extreme is where a computer job uses one or few nodes, and needs little or no inter-node communication. This latter category is sometimes called "Grid" computing. Tightly-coupled compute clusters are designed for work that might traditionally have been called "supercomputing". Middleware such as MPI (Message Passing Interface) or PVM (Parallel Virtual Machine) permits compute clustering programs to be portable to a wide variety of clusters.
