The 10 Laws of Cloudonomics

The 10 Laws of Cloudonomics

In 2008, Joe Weinman, then Strategic Solutions Sales VP for AT&T Global Business Services, created the 10 Laws of Cloudonomics22 that still, after two and a half years, are the foundation for the economics of Cloud Computing. We’ve reproduced an abridged version of the Cloudonomics laws below.

Cloudonomics Law #1: Utility services cost less even though they cost more. Although utilities cost more when they are used, they cost nothing when they are not. Consequently, customers save money by replacing fixed infrastructure with Clouds when workloads are spiky, specifically when the peak-to-average ratio is greater than the utility premium. Cloudonomics Law #2: On-demand trumps forecasting. Forecasting is often wrong, the ability to up and down scale to meet unpredictable demand spikes allows for revenue and cost optimalities. Cloudonomics Law #3: The peak of the sum is never greater than the sum of the peaks. Enterprises deploy capacity to handle their peak demands. Under this strategy, the total capacity deployed is the sum of these individual peaks. However, since Clouds can reallocate resources across many enterprises with different peak periods, a Cloud needs to deploy less capacity. Cloudonomics Law #4: Aggregate demand is smoother than

Cloudonomics Law #2: On-demand trumps forecasting. Forecasting is often wrong, the ability to up and down scale to meet unpredictable demand spikes allows for revenue and cost optimalities. Cloudonomics Law #3: The peak of the sum is never greater than the sum of the peaks. Enterprises deploy capacity to handle their peak demands. Under this strategy, the total capacity deployed is the sum of these individual peaks. However, since Clouds can reallocate resources across many enterprises with different peak periods, a Cloud needs to deploy less capacity. Cloudonomics Law #4: Aggregate demand is smoother than

Cloudonomics Law #3: The peak of the sum is never greater than the sum of the peaks. Enterprises deploy capacity to handle their peak demands. Under this strategy, the total capacity deployed is the sum of these individual peaks. However, since Clouds can reallocate resources across many enterprises with different peak periods, a Cloud needs to deploy less capacity. Cloudonomics Law #4: Aggregate demand is smoother than

Cloudonomics Law #4: Aggregate demand is smoother than individual. Aggregating demand from multiple customers tends to smooth out variation. Therefore, Clouds get higher utilization, enabling better economics.

Cloudonomics Law #5: Average unit costs are reduced by distributing fixed costs over more units of output. Larger Cloud providers can therefore achieve some economies of scale. Cloudonomics Law #6: Superiority in numbers is the most important factor in the result of a combat (Clausewitz). Service providers have the scale to fight rogue attacks.

Cloudonomics Law #6: Superiority in numbers is the most important factor in the result of a combat (Clausewitz). Service providers have the scale to fight rogue attacks.

Cloudonomics Law #7: Space-time is a continuum. Organizations derive competitive advantage from responding to changing business conditions faster than the competition. With Cloud scalability, for the same cost, a business can accelerate its information processing and decision-making. Cloudonomics Law #8: Dispersion is the inverse square of latency. Reduced latency is increasingly essential to modern applications. A Cloud Computing provider is able to provide more nodes, and hence reduced

Cloudonomics Law #8: Dispersion is the inverse square of latency. Reduced latency is increasingly essential to modern applications. A Cloud Computing provider is able to provide more nodes, and hence reduced latency, than an enterprise would want to deploy.

Cloudonomics Law #9: Don’t put all your eggs in one basket. The reliability of a system increases with the addition of redundant, geographically dispersed components such as data centers. Cloud Computing vendors have the scale and diversity to do so.

Cloudonomics Law #10: An object at rest tends to stay at rest. A data center is a very large object. Private data centers tend to remain in locations for reasons such as where the company was founded, or where they got a good deal on property. A Cloud service provider can locate greenfield sites optimally.

 

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