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Wednesday, 1 April 2015

New Developments In The Arena Of Cloud Load Balancers

A recent study revealed that with cloud load balancing, a large sized enterprise company can actually make substantial power savings. Such a load-balancing system can drive the organizational goal mouths through assured power-efficiency routes.

A brand new ‘autoscaling’ procedure is a unique finding in the field of load balancing technology. Cloud industry experts unveiled that such a system includes power-efficient load balancing which has basically been deployed across multiple production clusters. These are set up across global data centers located in many countries. By deploying such cloud architecture, several companies have been able to demonstrate significant energy savings.

What exactly is load balancing? For the records, a load balancer distributes workloads across several computing resources such as servers. It optimizes resource usage so that every task gets completed on time.

Cloud load balancers deploy the same concept as a regular server linked one. They manage online traffic by distributing workloads across multiple servers and resources. This is done automatically and the same can be done on an on-demand basis. As a result, workload performances get maximized and overloads are prevented. Thus, users enjoy a seamless experience.

How does a load balancer work? The latest technology in load-balancing policy deployed by an industry leading cloud services provider confirms that a modified round-robin algorithm is used in servers. Roughly similar number of page requests is used to carry out the same amount of CPU workloads. Heavy workloads are concentrated onto just one server till medium-level workloads are managed. A typical Web server can consume about 60 watts of power and more than 100 watts during low-level CPU utilization. At medium CPU utilization levels, it can consume around 150 watts of power.

In order to manage overall workloads, load balancers deploy a subset of servers by batch-processing workloads. Some of them also use auto scaling to dynamically adjust active pool sizes. Hence, every request gets addressed within a stipulated time period.

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