Hardware versus software load balancing

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Continued use of the site after the effective date of a posted revision evidences acceptance. Please contact us if you have questions or concerns about the Privacy Notice or any objection to any revisions. All rights reserved. Join Sign In. Date: Feb 28, Chapter Description This sample chapter will concentrate on what you need to know about scaling with Cold-Fusion MX: scaling considerations, writing ColdFusion MX applications that will scale, keeping server data in sync, the differences between hardware and software load-balancing options, scaling with ClusterCATS, and scaling with hardware-based load-balancing devices.

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Cookies and Related Technologies This site uses cookies and similar technologies to personalize content, measure traffic patterns, control security, track use and access of information on this site, and provide interest-based messages and advertising. Load balancers are usually deployed in pairs in case one fails. Most enterprises also deploy load balancers and servers in multiple locations, a procedure known as global server load balancing GSLB.

GSLB not only provides optimized response times, but also ensures high availability in disaster recovery situations. If one data center fails, GSLB systems can redirect network traffic to other available sites, minimizing the impact on end-users.

The most obvious difference between hardware vs. Network load balancer hardware is typically over provisioned — in other words, they are sized to be able to handle occasional peak traffic loads. In addition, each hardware device must be paired with an additional device for high availability in case the other load balancer fails. Another critical difference between hardware and software load balancers lies in the ability to scale. As network traffic grows, data centers must provision enough load balancers to meet peak demand.

For many enterprises, this means that most load balancers stay idle until peak traffic times e. Black Friday. If traffic volumes unexpectedly exceed capacity, end-user experiences are significantly impacted. On the other hand, software load balancers are able to scale elastically to meet demand. Whether network traffic is low or high, software load balancers can simply autoscale in real time, eliminating over-provisioning costs and worries about unexpected traffic surges.