What does it take to profitably compete against Amazon Web Services?

I've been concerned about this question for the past decade. I did not realize it until after Amazon's Web Services became popular. How is that possible? Allow me to explain.

I joined Sun Microsystems over a decade ago intrigued by Jim Waldo, Bill Joy, and others' vision of how computing would change as low-cost CPUs, storage and networks emerge, and as distributing computing becomes accessible to large numbers of developers. A key question was 'how would businesses make money?' The particular technology and business that we imagined did not pan out as we had hoped. As it turns out, we were too early.

Fast forward to a few years ago as many explored how utility and grid computing capabilities could be monetized. Sun Grid and the 'dollar per CPU hour' was advanced as a possible Infrastructure-As-A-Service (IAAS) model. The Sun CTO organization began a research effort, dubbed Project Caroline, to investigate technology for the not-yet-named Platform-As-A-Service (PAAS) space. As part of the Project Caroline effort, we built a model data center to evaluate the technology's potential. Still, the question, 'how to make money?', loomed.

Shortly afterward, Amazon Web Services began rolling out their offerings. They instantly appealed to developers. They captured the early IAAS market with fast-paced growth to the dominant position. Their offerings were straight forward and aggressively priced.

It clicked. I needed to understand how an IAAS could compete against Amazon Web Services. There are good strategies for competing against an early leader an emerging market. Going head-to-head with the leader in a low-margin, capital intensive market is an unlikely strategy. However, knowing what it would take to directly compete with Amazon Web Services would be informative and instructive.

As I talked with people, the complexity became overwhelming. I decided to construct a model to allow evaluation of many potential scenarios. For example, what if I wanted to get to market quickly by using a 24x7 operations center staffed by people who manage the configuration and management of the customer resources? What if, I purchased software to automate their tasks? What if I built the software? Another example, what if I used 'pizza box' systems for customer nodes? What about mid-range systems? What about blade systems? On the operations side, what if power rates doubled? What if I doubled capacity? How much does utilization play a factor? Rich Zippel joined the modeling effort.

As we refined the model, a few findings stood out. For example, utilization of the customer resources, equipment selection, software license costs paid by the IAAS provider, and the level of automation of customer resource configuration/management are major factors in determining profitability. Other factors such as, power costs and automation of infrastructure systems' management are factors that have less of an impact than we had expected.

I presented some of the scenarios and findings last night at the Boston Cloud Services meet up. The audience had great questions and suggestions. For example, is there any way to increase utilization beyond 100% (overbooking as airlines do) knowing full well that you'll deny someone's request when they access their resource? This could be modeled, however, the answer would have to play to the customer satisfaction and SLA requirements. Would more power systems be more cost effective than the low-end HP systems modeled? The model allows various system types and their infrastructure impacts to be compared. I modeled the lower-end systems because they, in general, ended up being more cost effective compared to types of systems. However, modeling of more systems should be done.

If you have other questions or suggestions, feel free to let me know.