Hi
My company is considering setting up some infrastructure for ML. Right now
we're either using our own laptops / google comput engine. Has anyone done
this/found good tools for it? I was considering looking into GCE/amazon and
auto scaling, maybe having it setup another ipython notebook (probably by
starting a docker container), and then tearing it down on idle.
The problem as I see it is the "tearing it down" bit, I don't want the jobs
shutting down before the user has had a chance to get the resulting data,
but I suspect if we let users shut them down themselfes a lot of them will
sit around for no reason.
I considered one huge box that's on 24/7, but I want a setup where we let
people use as much memory as possible, and still avoid having users crash
eachothers jobs if they allocate too much. So that's tricky as well.
Has anyone done anything like this? Any tips?
--
Best regards
Anders Aagaard
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