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Server Clustering

In today’s dynamic environment, server clustering is extremely essential to provide round the clock availability and scalability. The exhaustive requirement demands resilience in LAN/WAN systems, network operating systems and application systems. We, at Wizertech, provide both technical consultancy support & successful implementation to provide an integrated solution for your critical requirements.

Introduction :

Server clustering is integrating a group of servers to improve performance and availability over one single server. The USP of server clustering is to provide the client constant access to important server-based resources. In a server cluster, each server owns and manages its local devices and has a copy of the operating system and the applications or services that the cluster is managing. Devices common to the cluster, such as disks in common disk arrays and the connection media for accessing those disks, are owned and managed by only one server at a time. For most server clusters, the application data is stored on disks in one of the common disk arrays, and this data is accessible only to the server that currently owns the corresponding application or service.

Types of Server Cluster

Though there are several types of server clustering based on client usage and purpose, primarily there are three types of server clustering.

  1. Load Balancing Cluster: Load balancing exists when numerous computers are linked together to work as one virtual computer to share computational workload. It is commonly used for high traffic websites such as OS manufacturers and Facebook. In such an architecture, the cluster manager acts as a firewall. It filters and directs requests to one of the servers below it, as shown in the diagram. The result is balanced computational work distributed evenly among different servers
  2. Compute Cluster: 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 compute clusters is how tightly-coupled the individual nodes are. For instance, a single compute job may require frequent communication among nodes – this implies that the cluster shares a dedicated network, is densely located, and probably has homogenous nodes. This cluster design is usually referred to as Beowulf Cluster. The other extreme is where a compute 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.
  3. High Availability or Failover cluster: High-availability clusters (also known as Failover Clusters) are implemented primarily for the purpose of improving the availability of services that the cluster provides. They operate by having redundant nodes, which are then used to provide service when system components fail. The most common size for an HA cluster is two nodes, which is the minimum requirement to provide redundancy. HA cluster implementations attempt to use redundancy of cluster components to eliminate single points of failure.