Cloud providers Google(s GOOG), Amazon(s AMZN)Web Services (AWS) and Microsoft(s MSFT) are doing some spring-cleaning, and it’s out with the old, in with the new when it comes to pricing services. The latest cuts make it clear there’s a new business model driving cloud that is every bit as exponential in growth — with order of magnitude improvements to pricing — as Moore’s Law has been to computing.
If you need a refresher, Moore’s Law is “the observation that, over the history of computing hardware, the number of transistors on integrated circuits doubles approximately every two years.” I propose my own version, Bezos’s law. Named for Amazon CEO Jeff Bezos, I define it as the observation that, over the history of cloud, a unit of computing power price is reduced by 50 percent approximately every three years.
I’ll show the math below, but if Bezos’ law reflects reality, the only conclusion is that most enterprises should dump their data centers and move to the public cloud, thus saving money. Some savings occur over time by buying hardware subject to Moore’s Law, plus the fixed cost of maintenance, electrical power, cooling, building and labor to run a data center. In the end, I’ll show how prices are reduced by about 20 percent per year, cutting your bill in half every three years.
How we got here
Google was first to announce “deep” cuts in on-demand instance pricing across the board. To make the point that cloud pricing has been long overdue, Google’s Urs Hölzle showed in March just how much cloud pricing hasn’t followed Moore’s Law: Over the past five years, hardware costs decreased by 20 to 30 percent annually, but public cloud prices fell by just 8 percent annually:
Having watched AWS announce, by my count, 43 price cuts during the past eight years, the claim of merely a 6 to 8 percent drop for public cloud seems off. (That would be a 2 percent reduction 43 times to get an 8 percent trend line.)
Nevertheless, applying a Moore’s law approach to capture the rate of change for cloud, one would hold constant the compute unit, while the gains are expressed in terms of lower price. Thus, Bezos’s law is the observation that, over the history of cloud, a unit of computing power price is reduced by X percent approximately every Y years.
A bit of digging on Amazon’s Web Services blog shows how Amazon determined the percentage in computing power (X) and time period (Y) on May 29, 2008. The data from 2008 and the Amazon EC2 Spot Instances on April 1, 2014, shows that in six years, similar compute instance types have declined by 16 percent for medium instances and 20 percent for extra-large instances. Assuming a straight line, the pricing would have tracked as follows:
|2011||$0.410||$0.328||3 years, 50% reduction|
|2014||$0.210||3 years, 50% reduction from 2011|
|April 1, 2014||$0.210||6 years, 75% reduction from 2008|
For the AWS public cloud, X = 50 percent when Y = 3 years, supporting my claim: Bezos’ law is the observation that, over the history of cloud, a unit of computing power price is reduced by 50 percent approximately every three years.
Clearly, cloud, as opposed to building or maintaining a data center, is a much better economic delivery approach for most companies.
And how can an enterprise datacenter possibly keep up with the hyper-competitive innovation from Amazon, IBM, Google and Microsoft? Enterprising tech pros know how this is going to play out. They’re way ahead in asking: “Why should we continue to saddle our company with a huge cost anchor called a datacenter or private cloud?”
It looks as though being a cloud provider isn’t going to be like a retail business when it comes to profits, but it may be too early to tell. It’s a bit like the x86 server business IBM recently sold to Lenovo. There will likely be innovation above the core cloud platform for a long time, which might alter the profitability outlook.
Opinions aside, the math doesn’t lie. It’s not question of if we’re moving to the cloud but how — and when.
Greg O’Connor is CEO of AppZero, which specializes in migrating enterprise software applications to and from cloud computing services. Follow him on Twitter @gregoryjoconnor.
Feature image illustration adapted from Steve Jurvetson/Wikimedia Commons