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Managed Services Authors: Pat Romanski, Elizabeth White, Rajeev Gupta, AppNeta Blog, Liz McMillan

Related Topics: Cloud Computing, Virtualization Magazine, Enterprise Architecture, Cloud Interoperability, Infrastructure On Demand, SSL Journal, Cloudonomics Journal, Infrastructure 2.0 Journal

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Load balancing is key to successful cloud-based (dynamic) architectures

Much of the dialogue today surrounding cloud computing and virtualization is still taking the 50,000 foot view. It's all conceptual; it's all about business value, justification, interoperability, and use cases. These are all good conversations that need to happen in order for cloud computing and virtualization-based architectures to mature, but as is often the case that leaves the folks tasked with building something right now a bit on their own.

So let's ignore the high-level view for just a bit and talk reality. Many folks are being tasked, now, with designing or even implementing some form of a cloud computing architecture - usually based around virtualization technology like VMWare (a March 2008 Gartner Research report predicted VMWare would likely hold 85% of the virtualization market by the end of 2008).

But architecting a cloud-based environment requires more than just deploying virtual images and walking away. Cloud-based computing is going to require that architects broaden their understanding of the role that infrastructure like load balancers play in enterprise architecture because they are a key component to a successful cloud-based implementation, whether that's a small proof of concept or a complex, enterprise-wide architectural revolution.

The goal of a cloud-based architecture is to provide some form of elasticity, the ability to expand and contract capacity on-demand. The implication is that at some point additional instances of an application will be needed in order for the architecture to scale and meet demand. That means there needs to be some mechanism in place to balance requests between two or more instances of that application. The mechanism most likely to be successful in performing such a task is a load balancer.

The challenges of attempting to build such an architecture without a load balancer are staggering. There's no other good way to take advantage of additional capacity introduced by multiple instances of an application that's also efficient in terms of configuration and deployment. All other methods require modifications and changes to multiple network devices in order to properly distribute requests across multiple instances of an application. Likewise, when the additional instances of that application are de-provisioned, the changes to the network configuration need to be reversed.

Obviously a manual process would be time consuming and inefficient, effectively erasing the benefits gained by introducing a cloud-based architecture in the first place.

load-balancingA load balancer provides the means by which instances of applications can be provisioned and de-provisioned automatically, without requiring changes to the network or its configuration. It automatically handles the increases and decreases in capacity and adapts its distribution decisions based on the capacity available at the time a request is made.

Because the end-user is always directed to a virtual server, or IP address, on the load balancer the increase or decrease of capacity provided by the provisioning and de-provisioning of application instances is non-disruptive. As is required by even the most basic of cloud computing definitions, the end user is abstracted by the load balancer from the actual implementation and needs not care about the actual implementation. The load balancer makes one, two, or two-hundred resources - whether physical or virtual - appear to be one resource; this decouples the user from the physical implementation of the application and allows the internal implementation to grow, to shrink, and to change without any obvious affect on the user.

Choosing the right load balancer at the beginning of such an initiative is imperative to the success of more complex implementations later. The right load balancer will be able to provide the basics required to lay the foundation for more advanced cloud computing architectures in the future, while supporting even the most basic architectures today. The right load balancer will be extensible.

When first implementing a cloud-based architecture you need simple load balancing capabilities, and little more. But as your environment grows more complex there will likely be a need for more advanced features, like layer 7 switching, acceleration, optimization, SSL termination and redirection, application security, and secure access. The right load balancing solution will allow you to start with the basics but be able to easily provide more advanced functionality as you need it - without requiring new devices or solutions that often require re-architecture of the network or application infrastructure. 

A load balancer is a key component to building out any cloud computing architecture, whether it's just a simple proof of concept or an advanced, provider-oriented implementation

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More Stories By Lori MacVittie

Lori MacVittie is responsible for education and evangelism of application services available across F5’s entire product suite. Her role includes authorship of technical materials and participation in a number of community-based forums and industry standards organizations, among other efforts. MacVittie has extensive programming experience as an application architect, as well as network and systems development and administration expertise. Prior to joining F5, MacVittie was an award-winning Senior Technology Editor at Network Computing Magazine, where she conducted product research and evaluation focused on integration with application and network architectures, and authored articles on a variety of topics aimed at IT professionals. Her most recent area of focus included SOA-related products and architectures. She holds a B.S. in Information and Computing Science from the University of Wisconsin at Green Bay, and an M.S. in Computer Science from Nova Southeastern University.