
Michelangelo PyML: Uber’s Platform for Rapid Python ML Model - pplonski86
https://eng.uber.com/michelangelo-pyml/
======
mark_l_watson
I manage a ML team and the article has several ‘borrowable’ ideas, the primary
idea supporting model builders working on their local Linux device and
simplifying the process of transferring locally built models to a scalable
platform. If we were starting today to implement our in house system I might
just use Ubber’s system as a checklist for features to implement.

Not too off topic: after mostly building and training models on remote compute
(both at work and for my at home learning projects), I recently bought a fast
laptop for home use that has a 1070 GPU and the experience of using a local
device with a GPU makes me regret many years of SSHing to remote compute or
using Jupyter remotely for machine learning development. I mention this as a
lesson learned that may be helpful.

~~~
Michaelanjello
Uber's software doesn't exist in the public realm, and so there is nothing to
learn from it. It is imaginary fluff. I have posted a list of the ones that do
actually exist in another comment. And you should've at least got a 1080.

~~~
mmq
It actually gives a lot of idea and validation for concepts that I was
thinking about for my project
[https://github.com/polyaxon/polyaxon](https://github.com/polyaxon/polyaxon),
namely for going from trained model to serving those models on other platforms
in a seamless way. I also think that high-level articles like this one are
really good for people who are trying to build internal tools around ML/AI
ops, people can get more or less ideas about what and how other companies are
managing their ML pipelines and how they impact the productivity of their
teams.

~~~
Michaelanjello
You should be getting ideas from actual open source projects that actually
exist, not from imaginary/fake ones. There are numerous serving packages that
actually exist and offer ideas.

------
brylie
As it stands, this article strikes me more as a recruitment device than
something useful to ML practitioners outside of Uber. I'm hopeful Uber will
open-source parts of the Michelangelo stack, so it will be a contribution to
the broader community.

~~~
manojlds
Disagree. The article validates a lot of thought we have been putting in our
own company. Not everything has to be open sourced to have value.

------
canada_dry
Pretty slick, but more impressive is their well written overview of the tool.

It has some interesting model def features: _The model interfaces abstract
away where and how the model will be deployed so that the user can focus on
what they understand best: the data going in and out of the model._

~~~
Michaelanjello
Are you serious? There is no code for us, so there is no tool! The article is
as good as fake news.

~~~
throwaway77790
Not every company needs to open source their tools. Uber has contributed a
substantial amount of open source tools. This product is clearly new and 99%
likely ties to their stack meaning it is useless to you anyway.

Make your own tool and open source it if you are going to be so mean. I would
never want to share my hard work with people who act this way.

------
myegorov
Related meetup:

UBER : Big Data Infrastructure and Machine Learning Platform
[https://www.meetup.com/SF-Big-
Analytics/events/257037259/](https://www.meetup.com/SF-Big-
Analytics/events/257037259/)

------
marcyb5st
Anyone working at Uber that can highlight the non trivial differences between
this pyML Michelangelo and Kubeflow? I am very interested in hearing first
hand opinions about pros and cons

------
typon
I wish my company was cool enough such that our internal tools (even if
they're technically complex) would be of interest to people :(

------
Michaelanjello
Who cares about this garbage if the tool isn't even open source? There are
lots of ML deployment tools that are open source. I know haters will downvote
my post, but it's the truth. If I can't actually fork and evaluate a tool, it
is hyped up garbage to me.

Meanwhile, here is a list of open source ML deployment packages:

[https://github.com/oracle/graphpipe](https://github.com/oracle/graphpipe)

[https://github.com/eliorc/denzel](https://github.com/eliorc/denzel)

[https://github.com/tensorflow/serving](https://github.com/tensorflow/serving)

[https://github.com/ucbrise/clipper](https://github.com/ucbrise/clipper)

[https://github.com/DLHub-Argonne/dlhub_sdk](https://github.com/DLHub-
Argonne/dlhub_sdk)

[https://github.com/kubeflow/pipelines](https://github.com/kubeflow/pipelines)

~~~
zozbot123
FWIW, the "Guidelines" ask you to please not dismiss work out of hand.
Appearances matter, too - you can point out that a tool is proprietary and has
lots of plausible FLOSS alternatives without being uncivil about it
("garbage").

Edited: Commenting about the voting, especially in the way you did here, is
inappropriate too. We're here for substantive discussion.

~~~
mlthoughts2018
I agree with you, but I also think there’s room to point out that Uber has
lost credibility and it wouldn’t be surprising or inconsistent if it was just
a PR post for recruiting hype. Without details (not mere surface comments) on
how it is differentiated from the many other available solutions and deep
dives into what use cases it is specifically better suited for, it seems
reasonable to treat it with a lot of skepticism.

But to be clear, I totally agree in terms of the degree and tone. I don’t
think the parent comment you responded to was “uncivil” in any way, but overly
dismissive instead of just noting to be skeptical.

~~~
zozbot123
Skepticism is one thing, lack of civility is quite another (and I'm sorry, but
calling stuff "garbage" in such an off-hand way is clearly uncivil to me,
_especially_ when shallow dismissals are expressly pointed out as a problem).
See brylie's comment in this thread for how to do it right - take that, add a
stronger caveat about this tool's proprietary status, in contrast to so much
other stuff in this space being FLOSS, and it would make your point quite well
without degrading discussion.

~~~
mlthoughts2018
I didn’t write a comment calling anything garbage. In what way did my comment
degrade discussion?

~~~
grzm
I believe they’re referring to 'Michaelanjello’s comment upthread:

[https://news.ycombinator.com/item?id=18692801](https://news.ycombinator.com/item?id=18692801)

~~~
mlthoughts2018
Well my comment itself was downvoted, so I don’t agree it was a focus on the
original comment.

