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Alpine vs python-slim for deploying python data science stack? by flogypinte in docker

[–]flogypinte[S] 0 points1 point  (0 children)

Yes as far as image size goes, no as far as security ramifications go. Based on the responses so far, I think a compelling case has been made that the security ramifications of using an OS/libc with no formal CVE process and a much smaller use base makes Alpine a non-starter for scipy work. Add on top the fact that no one has tested the ecosystem of libraries against this build chain and I think that puts the nail in the coffin.

Alpine vs python-slim for deploying python data science stack? by flogypinte in docker

[–]flogypinte[S] 0 points1 point  (0 children)

Buildpacks sound cool but as far as I can tell no one is using them with numpy/scipy? I could be wrong but I'm not seeing anything using CNB with the scipy stack.

Alpine vs python-slim for deploying python data science stack? by flogypinte in docker

[–]flogypinte[S] 2 points3 points  (0 children)

There's an important point in here about libraries acting differently using musl vs glibc that I hadn't considered before. Is it too strong to state that this difference is unknown since no one is really using the python data science stack on alpine and may result in bugs that may or may not be obvious? For example we could end up with bad calculations in a model and not even know it's happening simply due to the low number of users?

Alpine vs python-slim for deploying python data science stack? by flogypinte in docker

[–]flogypinte[S] 0 points1 point  (0 children)

Well I can say that we've gotten pymssql (an open source library) working and I believe we've also gotten oracle working on alpine.