1187SSR Understanding Cloud Infrastructure Costs: Navigating for Savings

1187SSR March 7, 2013, 15 pages, Charlie Burns and Bruce Guptill, $1,295.00 (Single User License)

What does it really cost to move IT workloads into the Cloud? What are the real economic benefits to the enterprise? And which types of workloads are better off running in traditional environments?

Saugatuck Technology research continues to indicate that too many enterprise Business and IT leaders overlook or underestimate Cloud’s true, core costs at the enterprise workload level. Widespread “workload ignorance” thus leads to under-estimating enterprise Cloud costs, over-spending on Cloud services, increasing the actual costs of using and managing IT resources, and reducing the effectiveness of IT resources and departments.

The latest strategic research report from Saugatuck Technology, Understanding Cloud Infrastructure Costs: Navigating for Savings, presents a carefully detailed model and approach for IT leaders and managers to use in assessing the suitability and costs of various workloads for Cloud. The report uses Saugatuck’s real-world, enterprise IT research and analysis to examine and explain how the costs of Cloud IT resource use differ by workload, and to ascertain the impact of that on Cloud TCO, by comparing combinations of workload type, size, and IT operating efficiencies.

Readers of this report will learn the following:

• What types and sizes of workloads will cost less running on-premises versus in the Cloud?
• How can, and should, workload types be categorized and characterized in order to realistically compare their on-premise and Cloud costs?
• What role does IT environment and workload optimization play in comparing and managing workloads and costs?

“An important area of consideration when evaluating the TCO of any Cloud IT infrastructure is how it compares to the efficiency and optimization of relevant, traditional IT infrastructure. While significant savings are achievable, we caution companies to deeply understand their workloads – as the savings very much depend on the pre-existing level of resource utilization and levels of optimization,” concludes report lead author Charlie Burns.