The second decade of the cloud

In my talk at Bio-IT World this year, I made some comments about “cloud” technologies that I think bear repeating.

2017 is somewhere in the middle of the second decade of the cloud.

Of course, when I say “cloud,” I mean much more than mere virtualization. You don’t get the 2017-benefits of “going to the cloud” by just hosting your legacy architecture in Amazon’s east-coast-1 availability zone. Nor do you get them by putting your one-server-per-service enterprise on a fancy VMWare / ESX system, no matter how “hyperconverged” it may be. That’s the kind of misuse of the technology that has kept the “on-prem vs cloud” boondoggle alive so far past its expiration date.

Virtualization, of course, is a very good idea. Depending on how you define it, we’re in at least the third decade of OS level virtualization. That’s even more of a solved problem than the cloud.

The benefits of the cloud in 2017 accrue when you adopt cloud-native architectures. This entails substantially more work than porting a system to a hosted platform. It is also absolutely worth it for all but the longest of the long tail of legacy systems.

A bit of history: Amazon Web Services launched as a platform in 2002, and re-launched with EC2 and S3 in 2006. At the time, I worked for BioTeam. Less than a year later, in 2007, we noticed that every single member of the technical team had independently chosen at least one AWS based solution for a customer need. There was no corporate mandate – it was the right way to do the engineering.

At the time, I was responsible for many aspects of Bioteam’s “Inquiry” software product. By early 2008, we had ported our software to AWS and were offering it under license terms that still read pretty well, 9 years on.

While the FAQ above has aged well, that 2008 port of Inquiry looks pretty dusty in the bright lights of 2017. We took a legacy HPC / batch computing architecture and we virtualized it to run on AWS. There is certainly some forward-looking stuff in there, hosts that spin up and down in response to backlogs of work, and also some cleverness around staging data to and from S3. However, it bears little resemblance to the approach that one might take today.

Chris Dagdigian put it well at Bio-IT World: Many cloud-native system architectures do not have a direct “on-prem” analogue. In particular, Lambda and serverless architectures are challenging to explain in terms of the systems that we built in 2006.

As just one small example: On the Inquiry port, we spent a lot of time convincing our old faithful HPC job scheduler, Sun Grid Engine to be okay with hosts appearing and disappearing all the time. In our hosted, legacy architecture, SGE interpreted many aspects of the cloud as repeated failure. Compare that with even the most basic autoscaling architectures – to say nothing of the wizardry behind tools like Amazon’s Athena. Athena is frankly a bit mind-bending for somebody who made a good living less than 10 years ago making less-usable systems to do less-robust data analysis.

I find it clarifying to think about “cloud” from the perspective of a non technologist. When the CFO, COO, or CSO think of “cloud,” or articulate a “cloud first” strategy, they almost certainly have business or scientific metrics in mind, rather than technical niceties like where the metal happens to live. When executives ask for “cloud,” in my experience they are asking for things like:

  • Remove an entire category of off-mission task from the in-house team.
  • Make technology updates totally seamless and automatic.
  • Vastly simplify licensing and budgeting – budget in terms of headcount, not opaque version numbers and product families
  • Scale without limit, even in the event of a “success catastrophe.”

Note that merely virtualizing a legacy architecture onto Amazon, Google, or Microsoft (or yes, even one of the at-least-six-way-tie-for-fourth-place other public cloud providers) provides zero of the benefits for which we are sent off to “cloud.”

The good news: These benefits are, in fact, possible for scientific and high performance computing. It will not be as easy as it was with human resources or office productivity tools, but we will do it. And it will not be as simple as moving everything to AWS east-coast-1.

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