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The important question about moving to the cloud is: am I getting a good deal? It is easy to ask, but if you start to think about it in detail you might fancy a long lie down in a darkened room.

For the purpose of this lightning tour of cloud economics, I’m making several big assumptions:

• The first is that you have access to the utilisation of your servers and the peakiness of demand.

• The second is that we live in a type of eternal present and the snapshot you take now represents something approaching the demand patterns you will experience in the future.

• The third is that pricing remains more or less the same, or at least changes in a predictable way.

• The fourth is that we are not complicating the argument with factors such as security, licensing costs and so on.

• The fifth is that we are not really distinguishing between different types of service, and dealing with software, infrastructure and platform in a generic way.

• The sixth is … well, you get the idea.

The price of eggs

That is why when you try to pin down cloud costs people will shrug and say “how long is a piece of string?” It is also why so many vendors grab for the sticker price: this much per seat/gigabyte/core-GHz per hour.

We can do better than that.

A word about our assumptions. Some are specific to your application – for example, the cost of downtime.

The cost of bringing your data centre up to 99.9 per cent availability, if you desire that, is both a capital expenditure and an operational overhead, but it is the type of calculation that many of you have been doing for a long time.

It has to be added into the calculations. Also, the cost of the service you specify may not be the cheapest. If the location of your cloud provider matters, then you do business only with the cloud providers that offer the service at the prices they offer.

One of the most controversial recent investigations of cloud economics was posted in August 2010 on Vijay Gill’s blog. The post compares the cost of Amazon EC2 with a dedicated collocated data centre, and even has a spreadsheet that you can download.

Ticket to ride

Vijay Gill

The blog comes to an entirely uncontroversial conclusion: “If you make the trip every day, then you are better off buying a car. The difference is the duty cycle. If you are running infrastructure with a duty cycle of 100 per cent, it may make sense to run in-house.”

In other words, if you use all your servers all the time, don’t move to EC2: it will cost $118,000 compared with $70,000 every month.

This made news because Gill was Google’s “network lord” at the time - he's now at Microsoft.

The flaw in Gill’s analysis is, as he admits, that he is talking about 100 per cent utilisation.

Another flaw pointed out by a commenter is that he uses on-demand pricing rather than the cheaper price you get if you reserve demand. It is the difference between using thetrainline.com to book your ticket and just turning up at the station.

In effect, he calculated the price that Amazon EC2 would charge Google if Gill turned up unannounced, wanted one of his data centres moved to EC2, and then didn’t demand the best rate. Nevertheless, his spreadsheet is a good starting point if you want to fiddle with pricing.

We can, however, delve deeper into ways of modelling cloud economics and reach some tentative conclusions.

Weinman: hard stuff for fun

If you love these things, go straight to the source: Cloudonomics, a blog written by Joe Weinman full of advanced statistical and economic ideas.

You can just read the blog, run his Monte Carlo simulations or download the working papers. He has statistical analysis on much of what follows, and a lot more.

Weinman’s day job is with HP and he really does this stuff for fun.

Let's examine those conclusions.

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