The Lighter Side Of The Cloud – Disorganized
The Lighter Side Of The Cloud – Disaster Recovery Plan
The Lighter Side Of The Cloud – Brain Clutter
The Lighter Side Of The Cloud – PRISM
The Lighter Side Of The Cloud – Cost Savings

Looking Back at Joe Weinman’s 10 Laws of Cloudonomics

Looking Back at Joe Weinman’s 10 Laws of Cloudonomics

Back in September 2008, Joe Weinman, Strategic Solutions Sales VP for AT&T Global Business Services, came up with a new term “Cloudonomics” to describe the economic effects of cloud computing. At that time, cloud computing hadn’t entered the popular lexicon and his definition went a long way towards popularizing the technology.

During this time, Weinman also came up with what he called “The 10 Laws of Cloudonomics.” Now, two and a half years later when cloud computing has somewhat matured as a technology, it will be interesting to look back at these “laws” in the current context.

1. Utility services cost less even though they cost more.
When a company goes on to the cloud, it may pay more per unit of the service than if it owned the resources itself. But, with cloud computing’s on-demand revenue model, it doesn’t pay anything when those services are not required. This works out much cheaper in the long run.  (See: How Cloud Computing Can Save You Money)

2. On-demand trumps forecasting.
Services can be easily scaled up, and just as importantly, scaled down as per demand with cloud computing. However, forecasting demand is tricky at best and hence, servicing such demand with traditional IT infrastructure often results in waste of resources if overestimated, and not being able to meet requirements if underestimated. (See: Fighting Above Your Weight Class Through Cloud Computing)

3. The peak of the sum is never greater than the sum of the peaks.
Companies allocate resources to meet peak demands – April 15 for tax firms, Black Friday for retailers, etc. Hence, resources allocated add up to the sum of these individual peaks. However, with cloud computing’s flexibility, the same resources may be allocated across companies with different peak periods. Consequently, resources required are lower.

4. Aggregate demand is smoother than individual.
This is a derivative of the third law. Multiple users smooth out the demand curve, thereby ensuring maximum utilization of resources.

5. Average unit costs are reduced by distributing fixed costs over more units of output.
This is the application of an accepted theory of economics – economies of scale. Cloud computing service providers can utilize economies of scale which even the largest companies cannot with their internal IT infrastructures.

6. Superiority in numbers is the most important factor in the result of a combat (Clausewitz).
Quoting the expert war strategist, Weinman argues that large cloud providers are much better equipped to ward off distributed denial of service (DDoS) attacks than individual companies’ internal IT systems. See: (Cloud Computing Risks (And How to Deal With Them)

7. Space-time is a continuum (Einstein/Minkowski).
The success of a business often depends on the rapidity of its decision-making. Often, this process can be accelerated by processing several queries in parallel. With cloud computing allowing for parallel processing of the highest order, it can make businesses more successful. On a similar note, I had explored how smaller universities can access supercomputing power through cloud computing. (See: How Can Cloud Computing Help In Education?)

8. Dispersion is the inverse square of latency.
Latency is the delay between making a request and getting a response. Reduction in latency is directly proportional to square of the nodes servicing that request. With cloud computing, this is much easier to implement.

9. Don’t put all your eggs in one basket.
This law deals with redundancy, an idea I had mentioned several times in earlier articles. (See: Is Cloud Computing Secure? Yes, Another Perspective) To put this into perspective, consider that the reliability of a system with n redundant components, each with reliability r, is 1-(1-r) x n. So if the reliability of a single data center is 99%, two data centers provide 99.99% reliability and three data centers provide 99.9999% reliability. With multiple data centers, you can get almost close to 100% reliability.

10. An object at rest tends to stay at rest (Newton).
Once a traditional IT infrastructure setup is established, a company is locked into that location for a long period of time. Even if other locations prove more advantageous in the near future, relocation costs prevent migration. With cloud computing, there’s no such restriction.

By Sourya Biswas

sourya

Sourya Biswas is a former risk analyst who has worked with several financial organizations of international repute, besides being a freelance journalist with several articles published online. After 6 years of work, he has decided to pursue further studies at the University of Notre Dame, where he has completed his MBA. He holds a Bachelors in Engineering from the Indian Institute of Information Technology. He is also a member of high-IQ organizations Mensa and Triple Nine Society and has been a prolific writer to CloudTweaks over the years... http://www.cloudtweaks.com/author/sourya/

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