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Comparing the price and performance of various clouds is like trying to nail Jello to the wall — this is a very fluid and messy market, with lots of players, lots of options, lots of price changes. Not that that keeps folks from trying — Cloud Spectator came out with its take last week and RBC Capital Markets came out with its own comprehensive analysis on Sunday.
Much of RBC’s report confirms a lot of what we think we know: Clouds that offer little customization or support tend to be cheaper than those with more enterprise-y hand holding and other niceties that CIOs have come to expect. It doesn’t help that the lines blur all the time — Amazon Web Services(s amzn) for example, adding more enterprise type support options while HP(s hpq), Microsoft(s msft), VMware(s vmw) and others push their respective enterprise clouds as massively scalable alternatives to AWS.
The research also confirms that in cloud, as in life, price isn’t everything, even though people tend to focus on perceived cost savings from cloud over traditional IT deployment. According to the report — by RBC analyst Jonathan Atkin and colleagues — price/volume elasticity often leads to “minimal scale benefit — except for storage.”
“For memory and CPU, we found mostly flat pricing in relation to volume. At some vendors, we found negative scale effects, suggesting that some customers are forced to overbundle services as requirements increase.”
What this means is that all those price cuts we keep hearing about don’t necessarily amount to a hill of beans since cloud spending encompasses so many components — bandwidth, storage, I/O. A price slice in one area may not do much overall.
And, RBC found that scaling up a workload did not necessarily decrease unit pricing of a single resource, as might be expected. That does tend to happen with object storage, where typically the cost per GB of RAM falls as the workload grows. But the price curve for other resources can be flat or even rise as the workload grows.
“… to our surprise, many of the non-storage pricing curves are flat, meaning that unit costs (e.g., for memory or CPU) do not decline as configurations increase in size. Many vendors fall into this category, including HP(s hpq), Rackspace(s rax), Joyent, Google(s goog), CloudSigma, and Amazon(s aws). Even more surprising is the upward sloping price curve we encounter in some cases, e.g., with IBM/Softlayer, where unit costs increase for local storage and CPU for larger workloads.”
RBC said this happens when vendors “overbundle” or offer the customer a bigger overall configuration to handle the increased load. That would be fine and cost-efficient if all those resources get used but, in reality, the customer often ends up using just a part of all that extra capacity.