But cloud, because cloud and cloud cloud!

We recently did the math on some cloud database solutions vs. warehousing data ourselves and using Glacier as a last-resort backup. Turns out it's orders of magnitude cheaper to DIY and would remain so unless we needed -- as you say -- a whole lot of burstable compute. In that case we could always upload (or ship) all the data to the cloud if we wanted.

Cloud is cheaper for some work loads and use cases but not others. You have to analyze your own problem and see what works best.

What cloud vendors have managed to do is put a ton of marketing hype out there to the point that cloud has captured the entire discourse. Today if it's not cloud it's not cloud and that means it's not cloud, because cloud. I've heard many stories recently of companies spending 2-4X what they currently spend on IT to put it in the cloud in order to save money. It's hilarious.

While there's arguments on both side for TCO of Cloud, I'll offer one idea - a solution like BigQuery is zero-Ops, lets you scale to thousands of cores in a second, and you pay per-second. This is both cheaper, faster, and easier to use, simply because it breaks many assumptions folks make when doing TCO comparisons:

https://cloud.google.com/blog/big-data/2016/02/understanding...

For our app the killer was storage costs.

Of course our app is probably different from your app. For us we are doing real-time network testing and diagnostics of a bunch of distributed networks and dumping the data into a series of tables for analysis and diagnostic use. We can also use that data to improve our software in the long term.

A lot of data is generated, but if we lose a little bit it won't kill us. The analytics we want to do right now are fairly consistent in terms of load.

For this work load the cheapest option by far is to buy a RAID array and warehouse it locally. It can also be backed up very cheaply in Glacier so that if we do lose some we can get it back if we want it.

But of course like I said our app is probably not like yours. My point was that you have to do the analysis for your exact specific problem to decide what approach -- cloud or not -- is the best fit.

I saw this at RBI (part of reed Elsevier) I had to port a small system I built from linode to AWS and it was 10x the cost on AWS.

But it was on AWS, so it was enterprise.

Ah the old spend millions out sourcing to save hundreds of thousands of internal budget.

He implies that it's cheaper than, for example, buying HP+EMC+Oracle...

And then, not directly, roughly saying that scaling up on cheap commodity type hardware is only possible because of the efforts of Amazon/Google/Facebook.

He doesn't directly compare AWS versus, say Rackspace.

I'm not comparing it to Rackspace. I'm telling you I've run the numbers, and I can do it cheaper on prem with HP + EMC or Cisco + NetApp than I can in AWS. Unless I'm running compute at less than 50% capacity and storage at less than 60% capacity, it's far cheaper to do it on prem.

Well, netflix just migrated all their servers to amazon EC2. I'm sure it was cheaper for them.

And Spotify moved to Google Cloud. However, these are isolated cases that don't reflect on the average experience. For one, they most likely got a much, much better deal because of sheer volume. It still doesn't change the reality for companies with a handful, or even a few tens or hundreds of servers.

Netflix is also scaling up and down capacity based on time of day. Not to mention what they're paying isn't anything close to what you're going to pay. They negotiated pricing that would be cost effective for them, and I guarantee Amazon isn't making anywhere near the margin - they just want the brand recognition.

Or the finance director brought into the hype and there is some nasty costs lurking that netfix haven't thought about.