Some argue a consensus measure of compute resources represents a long standing and unfulfilled utopian dream. The “MIPS” seems like an existence proof and served this purpose in the 80′s and early 90′s. Processors eventually got more complicated with multiple cores and various performance enhancement strategies. The issue is not only not utopian, it a fundamental obstacle to progress. The cloud industry will not move beyond experimentation if there is no consensus measure of what we are selling? The electric utility industry does not exist if the utility does not provide customers a measure of what they are receiving?Would people be willing to buy gasoline from a gas station that does not give them a reliable metric to know what they are buying? Does it make sense for different gas stations to use different metrics? Does it seem likely customers would be happy if the cloud computing industry decided to replace GB as the measure of Memory or TB as the measure of storage or GB as the measure of bandwidth with some vague abstractions as Amazon did with the ECU regarding compute resources?
Consider a small sample of the ways companies are characterizing compute resources: Amazon (ECU), Softlayer (Cores), OpSource (CPU Hours), Rackspace (No compute options), Terremark (VPU), Linode (Linodes), ThePlanet (vCPU), Liquidweb (CPU’s), and EngineYard (small, medium, large). Customers can buy on-premise computer equipment without a compute metric because the unit of compute is the processor itself. This is not the case with cloud computing where processor resources get sliced and diced.
The bulk of the present momentum in infrastructure as a service cloud adoption involves exploratory projects. There is no uncertainty about the utility of Amazon’s hourly pricing when it comes to playing around. Amazon EC2 nonetheless remains expensive relative to traditional dedicated servers and well-executed premise based implementations. The 98% of compute resources that address the non-playing around activities benefit very little from the hourly pricing. Converting exploratory projects into a mass migration toward the cloud requires the cloud to be cost competitive with on-premise options. This means enabling and exposing cloud offers to price performance competiton.
