On 02/02/2017 11:16 AM, Matthew Treinish wrote:
<snip>
> <oops, forgot to finish my though>
>
> We definitely aren't saying running a single worker is how we recommend people
> run OpenStack by doing this. But it just adds on to the differences between
> the
> gate and what we expect things actually look like.
I'm all for actually getting to the bottom of this, but honestly real
memory profiling is needed here. The growth across projects probably
means that some common libraries are some part of this. The ever growing
requirements list is demonstrative of that. Code reuse is good, but if
we are importing much of a library to get access to a couple of
functions, we're going to take a bunch of memory weight on that
(especially if that library has friendly auto imports in top level
__init__.py so we can't get only the parts we want).
Changing the worker count is just shuffling around deck chairs.
I'm not familiar enough with memory profiling tools in python to know
the right approach we should take there to get this down to individual
libraries / objects that are containing all our memory. Anyone more
skilled here able to help lead the way?
-Sean
--
Sean Dague
http://dague.net
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