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13 ways the cloud has changed (since last you looked)

Peter Wayner | Feb. 9, 2016
New services and pricing models make cloud computing more powerful, complex, and cheaper than it was a few short years ago.

The natural solution is to charge different prices at different times based on demand, and the cloud companies are beginning to offer this option. Amazon now runs auctions for its machines, a process that allows prices for its instances to shift up and down with demand. If you’re able to run your jobs at off-hours and get out of the way when demand surges, you can save dramatically. If you need computing power when demand surges, you’re going to pay more.

Pre-emptable machines

Many cloud providers treat their renters as if they were owners. When you start up an instance, it’s yours until you release it. Unless there’s a terrible catastrophe or a strange violation of the terms of service, like spamming, your machine will run and run until you decide to shut it down or your credit card bounces.

Google looked at the challenge of variable demand and decided to solve it by offering a lower price for machines that could be shut down and survive. Your machine is your machine until some algorithm at Google decides that someone else will pay more. When demand is slack, you can pay much less, perhaps as little as 30 percent, but when demand soars you’ll be the first one they push out of the lifeboat. When demand ebbs again, they’ll let you back in.

It’s a great option for anyone who doesn’t need guarantees. The only challenge is writing your code so that it can survive crashes. But you’re probably doing that already, like the good programmer you are.

Algorithms not hardware

The first cloud instances were pretty much empty machines. If they came with any software at all, it was a stock distribution of a standard, open source operating system. They were a blank slate, and it was your job to fill it.

Some of the new offerings invert this model. Microsoft’s Azure, for instance, is bundling up machine learning and data analysis tools as services. You can store the data in Microsoft’s cloud, then fire up its software to crunch the numbers. The price of the hardware is bundled into the software. The Data Lake Analytics tool, for instance, bills by the minute and by the completed job. You concentrate on writing Microsoft’s U-SQL language for the analysis, and it sends you a bill after the queries are finished.

Microsoft’s Azure has more than a half-dozen services offering answers, not merely time on a machine.

Buying in advance

One of the challenges for the cloud company is predicting how much demand will really show up. The bean counters can watch Kevin Costner in “Field of Dreams” and say, “If you build it, they will come.” But that’s no guarantee.


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