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Cloud Balancing: The Next Generation of Global Server Load Balancing

While many organizations are still trying to get their arms around cloud computing concepts and terminology, "cloud balancing" might seem like just one more piece of jargon to add to the confusion. In fact, cloud balancing is an important concept that will play a significant role in cloud deployments, opening up new possibilities for organizations with limited resources to benefit from cloud computing.

So, what is cloud balancing? Think of it as the next generation of global server load balancing; it extends into the cloud the architectural deployment model currently used in global server load balancing.

With cloud balancing, application requests are distributed across application deployments in multiple data centers and in the cloud, thereby increasing the number of available locations from which an application can be delivered.

With traditional global server load balancing, the technical goals are to deliver high availability at maximum performance. Application routing decisions are made based on variables such as application response time, application availability at a given location, current and total capacity of the data center and cloud computing environment, user location, and time of day.

Increasingly, however, customers want to make application routing decisions based on other variables, such as the cost to execute a request by location, total cost to deliver the request, regulatory requirements, and the services required to fulfill a request per SLAs. High availability and performance are still important, but they also want to deliver applications using the least amount of resources at the lowest possible cost. To do that, they need a way to supply those additional variables to the global application delivery solution. Cloud balancing itself doesn't provide the technical framework for collecting these variables; what's required is a global application delivery solution that is context-aware--one that integrates the network, application, and business variables into the decision-making process. When these additional business-driven variables are available, cloud balancing becomes a viable solution for organizations to optimally deliver applications at the lowest possible cost with the fewest amount of resources.

Challenges persist with cloud balancing, some due to the immaturity of current cloud-based offerings and will eventually correct themselves with maturity; others will inevitably call for new standards to be written:

  • Finding the right cloud provider remains one of the most difficult and time-consuming challenges. With cloud computing still so new to many organizations, it's difficult for organizations to sort through the myriad services, comparing one provider's offerings to another. Compounding that problem is that offerings change as market demands change.
  • Application portability ranges from difficult to impossible because there are no standards among cloud providers for migrating applications. Lack of interoperability at the application layer compounds this problem. Proprietary platforms make it difficult to incorporate local data center deployments into a cloud balancing solution. In contrast, commercial platforms potentially make it easier to implement a cloud balancing solution, but only if the virtualization platforms are the same. If not, this hurdle may prove just as challenging as that of proprietary platforms.
  • Lack of integration between the global and the local application delivery solutions makes cloud balancing solutions impossible. Cloud balancing requires variables supplied by the local environment, so the global and local environments must be able to share information. One way to get this integration is to use a single vendor, but many organizations don't want to be locked in. What's needed is a dynamic, cross-environment, vendor-neutral solution, which will most likely emerge from standards-based APIs and Infrastructure 2.0 efforts. Until then, however, organizations will need to leverage existing component APIs to integrate variables.
  • Architectural and operational differences between global and local application delivery solutions present similar kinds of issues. Virtual appliances are helpful, but only to a point, because many cloud computing models are based on proprietary virtualization technologies. That makes it difficult for organizations to replicate architectures across cloud deployments.
       Deploying a virtual application delivery controller (vADC) along with the application in the cloud can help solve some of the architectural inconsistencies. A vADC provides the local load balancing component that's needed to implement a cloud architecture. With a vADC, an organization has the means by which to monitor and manage the health of the cloud-based deployment. A vADC also solves the integration issue, providing a way for the global application delivery controller to include the variables used in cloud balancing and choose the best location from which to serve applications.

For organizations that want to improve application performance, ensure application availability, and implement a strategic disaster recovery plan, cloud computing is a cost-effective alternative to building additional data centers. Cloud balancing extends those advantages by enabling organizations to leverage cloud deployments along with their local application delivery deployments. As a result, smaller organizations with limited resources will have the same opportunities as large organizations to optimize application delivery.

Posted by Karl Triebes on 06/18/2010 at 12:47 PM


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