Dynamically Scaling Resources: How to Save 60% on Costs with Cloud Hosting for Allegro – Lexology (registration)

Reducing Cloud Hosting Costs for Allegro with Dynamically Scaling Resources

With the increasing popularity and availability of cloud computing in todays business marketplace, many companies are considering cloud hosted solutions as opposed to the more traditional option of managing servers in-house. Coupled with high reliability, a cloud server grid offers the benefit of having complete control over creating, starting, stopping, and scaling servers instantly while only paying for the servers when they are running. By utilizing this functionality in an Allegro implementation, a business can drastically increase server grid performance while minimizing server up time, thereby greatly, reducing the overall cost of hosting. At one of Opportunes retail power clients, costs were reduced by 60%!

Over the course of each day and week, there will be distinct periods of high and low system resource usage in any ETRM implementation. Traditionally, the periods of high server resource usage dictate the total amount of resources which need to be dedicated to the environment on a full-time basis. One of the typical side effects of this approach is long periods of time in which the environments system resources are not being utilized or are being underutilized. In a cloud implementation, underutilization means you are paying by the minute for something you are not using!

Allegro Dynamically Scaling Resources

Coupling the power of Allegro class events with the versatility of a cloud environment, it is possible to dynamically scale your infrastructure in order to have resources available when they are required and turned off when they are no longer needed. Control of the cloud servers is accomplished by integrating your cloud providers API into Allegro and then utilizing triggers to turn the cloud servers on and off at the appropriate times. Given the flexibility of Allegro class events, the triggers can range from simple to very complex. A few examples are:

The triggers for dynamically scaling resources can be modified to meet the needs of any organization hosting Allegro in the cloud with any number of servers.

Case Study of Cost Reduction

When you analyze server up time over the course of one month, it becomes apparent that there is a very high potential for reducing hosting costs by dynamically scaling resources. To illustrate this point, consider a company that has an Allegro grid of 3 web servers. For the majority of the week, this particular company does not need to be running more than one server at a time, but 2 nights per week they run a very large valuation that requires 3 grid servers to finish on time for business the following day. In a traditional environment, it would be necessary to run all three servers full time even though two of them are only truly needed twice a week for a few hours. A cloud environment allows the possibility to run one of those servers full-time, and the other two for only five hours per week each. Over a one-month period, that equates to reducing approximately 1400 hours of time or 60% from your hosting costs.

Click here for graph

Value Added

Utilizing cloud hosting for an Allegro implementation offers a wide variety of inherent advantages, but those advantages come at a cost that is charged on a minute by minute basis. By implementing dynamically scaling resources, your organization has the potential to drastically reduce its hosting costs, while actually increasing the performance of your Allegro grid. Whether your organization is starting a new Allegro implementation, upgrading an existing Allegro implementation, or considering transitioning an existing Allegro environment to cloud hosting, the cost saving potential of dynamically scaling resources is so substantial that your company should take advantage of the opportunity right away.

Click here for graph

More here:
Dynamically Scaling Resources: How to Save 60% on Costs with Cloud Hosting for Allegro - Lexology (registration)

Related Posts

Comments are closed.