Beyond Cloud ROI: Optimize Deployment for Application Efficiency

Jul 18 2013 | by Zev Schonberg

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AWSresAs enterprises get more comfortable in the cloud, the conversation is shifting from the focus on cost to a holistic business perspective. Obviously, keeping spending down for increased ROI remains the primary business driver. However, ignoring the big-picture business perspective risks missing other key benefits the cloud has to offer.

Show Me The Performance!

While focusing on getting the job done at the lowest possible cost will definitely make the bean counters happy, it could also be missing the point. Consider Two different AWS configurations that cost roughly the same, but vary dramatically in performance. That difference in efficiency will impact the bottom line, but won’t necessarily show up under “cloud spend” on the balance sheet. A Cloud monitoring and optimization solution must factor in cost AND performance metrics in order to accurately present the ‘state of the cloud’ and make actionable recommendations for improvement.

The Bigger The Data, The More Important The Performance Metrics

Imagine the chief architect of DataMonster Inc. is designing an application to run an EMR job, parceling out huge chunks of data stored in S3 to thousands of EC2 instances for processing. In this case, the capability to compare cloud consumption and performance metrics across instances would be critical to identify application inefficiencies. Add tagging into the mix, and application designers could aggregate performance metrics associated with geographical locations, specific business units, or even individual users. This would empower application developers to isolate and eliminate trough performance points in order to increase efficiency (and ultimately ROI).

pnlgraphUsing Cloudyn, application designers can assess each job’s efficiency and identify specific resources that are under-utilized or maxed out. These actionable recommendations enable you to match AWS resources to the most appropriate job type.

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