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But the ski rental problem as described there misses the same factors as the AWS example: it does not account for the additional costs of ownership vs renting.

But the ski rental problem as described there misses the same factors as the AWS example: it does not account for the additional costs of ownership vs renting. The analogy doesn't quite map for all aspects so I'll stick with the ski example to show it's not specific to cloud computing: Owning skis has a load of associated costs ranging from simple to more complex: storage, maintenance, carrying them to and from the airport, having to spend a lot of energy on the decision of which pair to buy as it will be expensive to change my decision later, having the general background burden of owning another thing that I have to think about on some level even when I am not skiing. All these things are ultimately paid for with money directly, or time, or mental energy that I could be spending on other things. What's the cost of all those combined? It's really hard to say and may even extend beyond a simple economic function and get into the philosophical arena. But you can't deny there is a cost and you can't ignore that cost when evaluating if renting is more or less expensive than owning, over an arbitrary time period.

bunderbunder 8y ago
Concrete example: I own skis. But if I'm going on a ski vacation instead of a day trip, I rent them. That decision has nothing to do with the cost to rent skis vs. what they sell for, and everything to do with the fact that I can rent skis for about the same as what it would cost me to transport my own skis and boots to Breckenridge and back. I suspect that there is something like that (only not at all) going on with machine learning kit: If you've got exactly one person training models, and they're doing it all the time, then yeah, it's cheaper to own your own hardware. If you've got several people all trying to share the training rig, then you start having to worry about all the costs associated with scheduling time, delays if someone else got their first (especially if they're doing deep learning and will be monopolizing the server for upwards of a week), etc. Once you factor all those full-lifecycle costs in, the cloud might start to look relatively cheaper.

bunderbunder 8y ago

Concrete example: I own skis. But if I'm going on a ski vacation instead of a day trip, I rent them. That decision has nothing to do with the cost to rent skis vs. what they sell for, and everything to do with the fact that I can rent skis for about the same as what it would cost me to transport my own skis and boots to Breckenridge and back. I suspect that there is something like that (only not at all) going on with machine learning kit: If you've got exactly one person training models, and they're doing it all the time, then yeah, it's cheaper to own your own hardware. If you've got several people all trying to share the training rig, then you start having to worry about all the costs associated with scheduling time, delays if someone else got their first (especially if they're doing deep learning and will be monopolizing the server for upwards of a week), etc. Once you factor all those full-lifecycle costs in, the cloud might start to look relatively cheaper.