Load Balancing 101 The Evolution to Application Delivery Controllers

Written by KJ (Ken) Salchow, Jr. | Manager, Product Management Load Balancing 101: The Evolution to Application Delivery Controllers
Introduction One of the unfortunate effects of the continued evolution of the load balancer into today's application delivery controller (ADC) is that it is often too easy to forget the basic problem for which load balancers were originally created-producing highly available, scalable, and predictable application services. We get too lost in the realm of intelligent application routing, virtualized application services, and shared infrastructure deployments to remember that none of these things are possible without a firm basis in basic load balancing technology. So how important is load balancing, and how do its effects lead to streamlined application delivery?
Load Balancing Drivers The entire intent of load balancing is to create a system that virtualizes the "service" from the physical servers that actually run that service. A more basic definition is to balance the load across a bunch of physical servers and make those servers look like one great big server to the outside world. There are many reasons to do this, but the primary drivers can be summarized as "scalability," "high availability," and "predictability." Scalability is the capability of dynamically, or easily, adapting to increased load without impacting existing performance. Service virtualization presented an interesting opportunity for scalability; if the service, or the point of user contact, was separated from the actual servers, scaling of the application would simply mean adding more servers which would not be visible to the end user. High Availability (HA) is the capability of a site to remain available and accessible even during the failure of one or more systems. Service virtualization also presented an opportunity for HA; if the point of user contact was separated from the actual servers, the failure of an individual server would not render the entire application unavailable. Predictability is a little less clear as it represents pieces of HA as well as some lessons learned along the way. However, predictability can best be described as the capability of having confidence and control in how the services are being delivered and when they are being delivered in regards to availability, performance, and so on.
Load Balancing: A Historical Perspective Back in the early days of the commercial Internet, many would-be dot-com millionaires discovered a serious problem in their plans. Mainframes didn't have web server software (not until the AS/400e, anyway) and even if they did, they couldn't afford them on their start-up budgets. What they could afford was standard, off-the-shelf server hardware from one of the ubiquitous PC manufacturers. The problem for most of them? There was no way that a single PC-based server was ever going to handle the amount of traffic their idea would generate and if it went down, they were offline and out of business. Fortunately, some of those folks actually had plans to make their millions by solving that particular problem; thus was born the load balancing market.
In the Beginning, There Was DNS Before there were any commercially available, purpose-built load balancing devices, there were many attempts to utilize existing technology to achieve the goals of scalability and HA. The most prevalent, and still used, technology was DNS round-robin. Domain name system (DNS) is the service that translates human-readable names (www.example.com) into machine recognized IP addresses. DNS also provided a way in which each request for name resolution could be answered with multiple IP addresses in different order.
F5 Networks, Inc. - 1 - © Jul-07 Written by KJ (Ken) Salchow, Jr. | Manager, Product Management
The first time a user requested resolution for www.example.com, the DNS server would hand back multiple addresses (one for each server that hosted the application) in order, say 1, 2, and 3. The next time, the DNS server would give back the same addresses, but this time as 2, 3, and 1. This solution was simple and provided the basic characteristics of what customer were looking for by distributing users sequentially across multiple physical machines using the name as the virtualization point. From a scalability standpoint, this solution worked remarkable well; probably the reason why derivatives of this method are still in u... [download for more]