Hello, I’m wondering how involved it would be to extend the sagemaker plugin to support additional task types like batch transforms and creating/updating endpoint configurations. Is this something that can be done purely in python (flytekit)?

@Andrew Achkar it wont be too much work

So with the python only approach would you suggest to use boto3 or sagemaker sdk directly?

Whatever you prefer

Going to piggyback off this q... if we wanted to extend the sagemaker training job plugin, would PRs only be needed for these files? • https://github.com/flyteorg/flyteidl/blob/master/protos/flyteidl/plugins/sagemaker/training_job.proto • https://github.com/flyteorg/flytekit/blob/master/plugins/flytekit-aws-sagemaker/flytekitplugins/awssagemaker/models/training_job.py

cc @Edgar Trujillo / @Andrew Achkar we at Union would love to help communicate. But most of us are our for the next few days. How about 7th / 8th?

@Ketan (kumare3) Returning to this thread, I think I stumbled into an issue with using Flyte’s Sagemaker training integration that I’m curious if you’ve resolved. As it stands, it doesn’t seem possible to associate a training job with a sagemaker experiment, so it wouldn’t be possible to use SM Studio UI to compare trials or otherwise view training metrics. What kind of pattern makes the most sense to you in terms of having experiment tracking and comparisons on top of training orchestrated by Flyte?

Hey Andrew would you be open for a quick chat

@Ketan (kumare3) yes I am available today to chat

I dmed you