Until now, when evaluating datacenter compute resources and estimating costs in the cloud has been a challenge. Typically we�re looking at a physical or virtual machine configuration such as CPU size, memory, disk space and so on. However, there are other resources that are more difficult to estimate such as bandwidth usage, storage transactions, and estimated future capacity.
Imagine having 50, 100, or more servers. Performing estimates for 100�s of servers would not only be time consuming, it would be difficult because we�re only looking at a snapshot in time. We know over the course of a day or week a server�s consumption model of resources will change. We may end up missing critical information that could end up in underestimating the cost of a VM or service in the cloud. Underestimating resources could lead to unexpected charges. Not an ideal situation when we�re looking to either reduce costs or migrate resources to the cloud.
You will find the tool and more information here: http://blogs.technet.com/b/cbernier/archive/2014/08/05/microsoft-azure-iaas-cost-estimator-tool.aspx
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