Cloud review: Amazon, Microsoft, Google, IBM, and Joyent

The top five public clouds pile on the services and options, while adding unique twists

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There are options for the teams doing data analytics. Microsoft offers a number of big data crunching services that are integrated with the Azure cloud. Once you upload your data, the algorithms are ready to go. You push a few buttons and fancy graphs and deep insights pour out. Similarly, you can tap the power of Watson and predictive analytics tools on IBM’s Bluemix. Amazon offers a narrower set of machine learning capabilities, tailored to developers and business analysts. Google’s machine learning service was recently made available in a limited preview.

There are other sets of features that didn’t end up mattering to me. Some of the clouds are doing a better job with performance measurements and fancy graphical dashboards than others. These sucked me in at first, but then I stopped paying much attention to them. Knowing the overall load on the machine is helpful, but most developers will need to hack their own statistics to get a better feel for the throughput of their collection of machines. Your requirements may vary, though, and the extra features may be exactly what you need.

Another similar set of features may end up becoming more significant. Some of the newest features appearing on the clouds make it easier to automate vast armies of machines, then change the configuration on each of them a small amount. Amazon lets you create hundreds of new machines from the same image, then pass in configuration information that allows each of them to modify itself. There’s no need to log into each machine independently and configure it.

The value of features like this depends heavily on the kinds of jobs you’re running. If your stacks are fairly static, this feature won’t make much difference. But if you’re building up and tearing down big collections of machines, the ability to automate the configuration is essential. Expect more support for features like this to dominate the choices for the people who are working with sporadic bursts of big data to crunch.

The right cloud for you

If there’s one lesson from all of this, it’s that the answer is never cut and dried. The cheapest machine for you may not be the cheapest machine for me. The best bandwidth price plan for you might be prohibitively expensive for me. The benchmarks vary, as do the prices for data storage. Each of us is forced by the system to spend time crunching numbers and running tests before making a decision.

This is part of the fun. The cloud may appear to smooth over all the complexity involved in running a bunch of servers, but what the providers are really doing is solving all of the annoying problems while opening up the freedom to choose different architectures. The options are becoming more transparent and easier to make now that we don’t have to worry so much about backup generators and rack capacity. After spending a few months playing around with my vast empire, I’ve realized I’m not really finished.

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Copyright © 2016 IDG Communications, Inc.

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