Hardware based load balancing
A hardware load-balancing device, also known as a layer 4-7 router, is a computer appliance that is used to split network load across multiple servers based on factors such as CPU processor utilization, the number of connections or the overall server performance.
The use of an this kind of appliances minimizes the probability that any particular server will be overwhelmed and optimizes the bandwidth available to each computer or terminal. In addition, the use of an hardware load-balancing device can minimize network downtime, facilitate traffic prioritization, provide end-to-end application monitoring, provide user authentication, and help protect against malicious activity such as Denial-of-Service (DoS) attacks.
The basic principle is that network traffic is sent to a shared IP called a virtual IP (VIP), or listening IP and this address is attached to the load balancer. Once the load balancer receives a request on this VIP it will need to make a decision on where to send it and this decision is normally controlled by a load balancing algorithm, a server health check or a rule set.
The request is then sent to the appropriate server and the server will produce a response that, depending on the type of load balancer in use, will be sent either back to the load balancer, in the case of a Layer 7 device, or more typically with a Layer 4 device, directly back to the end user (normally via its default gateway).
In the case of a proxy based load balancer, the request from the web server can be returned to the load balancer and manipulated before being sent back to the user. This manipulation could involve content substitution or compression and some top end devices offer full scripting capability.
Load Balancing Algorithms
Load balancers use different algorithms to control traffic and with the specific goal of intelligently distribute load and/or maximize the utilization of all servers within the cluster.
In a random allocation, the traffic is assigned to any server picked randomly among the group of destination servers. In such a case, one of the servers may be assigned many more requests to process while the other servers are sitting idle. However, on average, each server gets an approximately equal share of the load due to the random selection. Although simple to implement it can lead to the overloading of one server or more while under-utilization of others.