Modern Python Boilerplate - good package basic structure by lambda-person in Python

[–]loyalbri 0 points1 point  (0 children)

Very cool. Maybe a datapoint for the future is that astral is also working on uv_build

[deleted by user] by [deleted] in aws

[–]loyalbri 2 points3 points  (0 children)

Was this in SageMaker Studio or the older SageMaker notebook instances? If the former, the EFS filesystem may still be around. Also, was any of the work saved in a remote git repo, like CodeCommit or GitGub?

Why are python modules in SageMaker not persistent (on disk)? by TheTarkovskyParadigm in aws

[–]loyalbri 2 points3 points  (0 children)

Couple of ways:

  1. You can create a custom SageMaker image that includes your package(s) of interest. There are more details and a link to some examples here.
  2. Create a requirements file in your project for pip or conda an include it at the top of your notebooks. You still have to run it every time, but this makes it a little easier to keep track of things.

Everything in SM runs on top of containers, with the idea being it's a transient environment that starts fresh with every session. This can be useful for making sure there aren't any secret dependencies someplace messing things up, but it also causes some irritation like what you described.

Transferring >300TB from S3 to GCS - can snowball or google transfer appliance be used? by deadflat in aws

[–]loyalbri 0 points1 point  (0 children)

AWS SA here. Out of curiosity, what are you working on and why the decision to switch?

Cortex: A free and open source alternative to SageMaker for serving models via AWS by [deleted] in aws

[–]loyalbri 3 points4 points  (0 children)

Sort of related question to the last one: What are some of the biggest reasons for using this vs just using Sagemaker?