A good read on realities behind cloud computing

In this article on the venerable Next Platform site, Addison Snell makes a case against some of the presumed truths of cloud computing. One of the points he makes is specifically something we run into all the time with customers, and yet this particular untruth isn’t really being reported the way our customers look at it.
Sure, you are paying for the unused capacity. This is how utility models work. Tenancy is the most important measure to the business providing the systems. The more virtual machines they can cram on a single system, the better for them.
But … but …
This paying for vacancy/unused cycles isn’t really the expensive part.
The part that is expensive is getting your data out, or having significant volumes of data reside there for a long time. Its designed to be expensive. And capture data. This is a rent seeking model … generally held to be non-productive use of assets. It exists to generate time-extended monetization of assets. Like license fees for software you require to run your business.
We’ve worked through analyses for a number of customers based upon their use cases. Compared a few different cloud vendors with accurate usage models taken from their existing day to day work. One of the things we discovered rapidly, for a bursting big data analytics effort, with a sizeable on site storage (a few hundred TB, pulling back 10% of the data per month), was that the cloud models, using specifically the most aggressive pricing models available, were more expensive (on a monthly basis) … often significantly … than the fully burdened cost (power/cooling, space/building, staff, network, …) of hosting an equivalent (and often far better/faster/more productive) system in house.
The major difference is that one of these is a capital expense (capex) and one is an operational expense (opex), and they come from different areas of the budget.
For occasional bursts, without a great deal of onsite data storage, and data return, clouds are great. This isn’t traditionally the HPC use case though. Nor is it the analytical services use case.
Interesting read on the article, and the other points are also quite good. But as noted, the vacancy cost is important, but not the only cost involved, nor even the dominant one.

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