Musing on Springs, Cloud Stiffness and K

Congratulations to our friends at Dropbox that announced earlier last week plans to raise $500 million through an initial public offering . Well done!

Dozens of news articles and blog posts talked about this upcoming event however, I would like to to focus on GeekWire’s article that was highlighting one specific topic reported in the S1 document: How Dropbox saved almost $75 million over two years by building its own tech infrastructure .

After making the decision to roll its own infrastructure and reduce its dependence on Amazon Web Services, Dropbox reduced its operating costs by $74.6 million over the next two years. 

 

GeekWire’s Tom Krazit added that:

… once certain startups turn into big companies with hundreds of millions of users, with computing needs that they’ve come to intimately understand, it can be far more efficient to set up computing infrastructure designed exactly with those needs in mind.

…But I knew that…

About 10 years ago I was puzzled with a similar phenomenon when I noticed that some of my largest customers and prospects at the time are moving workloads to and from their data center. (Do you even remember how it was 10 years ago :-). AWS was first to market with a modern cloud infrastructure service when it launched Amazon Elastic Compute Cloud in August 2006 but only handful of fast growing companies were using it at scale.  Migration was a very painful process at the time and it wasn’t common to move workloads and applications back from the cloud to a traditional  data center.  

The laws of physics apply everywhere

When I investigated further, I discovered what I have named as “the cloud’s K variable”. A concept taken from Hooke’s law in physics :

Hooke’s law is a principle of physics that states that the force (F) needed to extend or compress a spring by some distance X scales linearly with respect to that distance. Or in simple words, F=kX. 

F = kX, where k is a constant factor characteristic of the spring: its stiffness, and X is the extension of the spring. 

If X is your cloud, then its “K-variable” is a constant that represents the energy needed to adopt, run and operate your cloud implementation.  It is unique per application on any given cloud.

Think about F as the pain that is forcing you to change a public or private cloud infrastructure.  The pain can be measured in terms of the cost, time to develop new applications, time to provision or to develop and implement security controls.

Similar to the characteristic of a spring in Hooke’s law, K represents the cloud stiffness factor  – how simple it would be for you to change providers given the the war between cloud vendors continues to heat upThe Cloud’s “K variable” is becoming an important factor for both the data center and cloud providers as well as the enterprises, as it changes the economics that drive cloud migration.

What’s Next?

In my next post  I’ll write about the security component of the  “K variable” – how independent security controls attached directly to workloads, regardless of provider, platform or location reduces security complexity and simplifies the decision to migrate to the cloud.

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