|By Greg O'Connor||
|April 25, 2014 09:00 AM EDT||
Cloud providers Google, AWS and Microsoft are doing some spring-cleaning - out with the old, in with the new - when it comes to pricing services.
With the latest cuts, here's a news flash: 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. Let's call it "Bezos' Law," and go straight to the math
Bezos' law is the observation that, over the history of cloud, a unit of computing power price is reduced by 50% approximately every 3 years
If Bezos' law reflects reality, most enterprises should dump their datacenters and move to the public cloud. Let's factor in recent events.
Google was first to announce "deep" cuts in on-demand instance pricing across the board. GigaOm's Barb Darrow was quick to capture the excitement: And bam: Google cuts on-demand cloud prices by a third, demos live migration for its cloud
To make the point that cloud pricing has been long overdue, Google's Urs Hölzle showed just how much cloud pricing hasn't followed Moore's Law. Over the past five years, hardware costs decreased by 20-30 percent annually, but public cloud prices fell at just 8% annually.
Having watched AWS announce, by my count, 43 price cuts during the past eight years, the claim of merely a 6-8% drop for public cloud seems off.
A look at Wikipedia defines Moore's Law.
If you were to apply a Moore's Law approach to capture the rate of change for cloud, you could hold constant the compute unit, while the gains are expressed in terms of lower price.
Bezos' law is the observation that, over the history of cloud, a unit of computing power price is reduced by X% approximately every Y years.
Bezos' law is the observation that, over the history of cloud, a unit of computing power is increased by X% approximately every Y years at a fixed price.
Either approach illustrates what is happening to computing power and cost over time.
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:
Clearly, cloud, as opposed to building or maintaining a data center, is a much better economic delivery approach for most companies.
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?"
Opinions may differ, but the math doesn't lie. It's not question of if we're moving to the cloud but how - and when. If you are moving enterprise applications to the cloud, AppZero is the fastest, most flexible solution. You can learn more here and watch an actual migration (video) here.
In a recent research, analyst firm IDC found that the average cost of a critical application failure is $500,000 to $1 million per hour and the average total cost of unplanned application downtime is $1.25 billion to $2.5 billion per year for Fortune 1000 companies. In addition to the findings on the cost of the downtime, the research also highlighted best practices for development, testing, application support, infrastructure, and operations teams.
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