During that presentation to Wall Street, one of the participants asked me if I had heard of the NYSE Community Cloud. I had not.
Beyond the "low latency / high frequency" use case, the real driver of where applications run and how they are designed is the data. If data is in the Cloud, it exerts a force, like matter, on everything within its field. And in the case of the Cloud, the presence of Big Data, such as the giant data sets maintained by Xignite and NASDAQ on Amazon AWS, this data draws still more web services and still more data to the AWS Cloud. The "closer" a service is to the data, the better the application performs, the better it utilizes the network, and the more effectively the application can scale.
According to Metcalfe the value of a network is the square of the number of connections. In this sense it seems that "closing" a network severely limits the number of connections. How does this impact the economics of the Cloud?
I concur with Reed that while a compelling and ready starting point Metcalfe's Law applied to the internet does not begin to express the dramatic force of scale. For a lively discussion please see:
Metcalfe's Law is Wrong - IEEE Spectrum
It's All In Your Head - Forbes.com ( by Robert M. Metcalfe)
In economics and business, a network effect (also called network externality or demand-side economies of scale) is the effect that one user of a good or service has on the value of that product to other people. When network effect is present, the value of a product or service is dependent on the number of others using it.
|From Robert M. Metcalfe's article It's in Your Head, Forbes 05.05.07|
- Leverage existing services available in the Public Cloud, thereby accelerating time to market and minimizing costs while maximizing customer value by leveraging Xignite's proven successful platform
- Build NASDAQ Data On Demand on Xignite platform in Amazon AWS Cloud.
- NASDAQ data + Xignite Platform + Xignite Catalog of Market Data + accelerate an ecosystem of market data value multiplying web services = much greater than the sum of its parts
- Build a Community Cloud on VMware / EMC technology ensuring vendor accountability and presuming a high degree of control and so forth.
- Build a data platform?,
- Benefit from other web services running in the community cloud?
- Maintain tight control and focus on a particular industry and provide very low latency for those firms who can leverage it or that prefer it.
In this case we see how in the Cloud, the real value of the Cloud isn't even just the server TCO, but a much more powerful Network Effect upon the information and services in the Public Cloud. For this reason, I don't discourage firms from building Private or Community Clouds, but I can't help feel it's important to underscore the Network Effect of the Public Cloud data and web services and how this could dramatically alter the economics and outcomes for certain firms
I think a lot of firms recognize the value of these large data sets for use cases such as algorithmic trading system back-testing. And I think you identify a key force in Cloud Economics when you name the types of powerful applications that can use large data sets if the data and the applications are "close" enough so that the latency of moving this data doesn't hobble the application.