Create a custom SageMaker image with recent Python release

Question

I am using Sagemaker Notebook Instances on AWS.

Looks like we can only use Python 3.6 kernels. I would like to be able to use Python 3.10 (latest version, or at least Python 3.9) in a notebook.

So far, what I have tried is based on life cycle: https://docs.aws.amazon.com/sagemaker/latest/dg/studio-byoi-create-sdk.html

But somehow, it didn't work (I was not able to use the recent kernel in the notebook)

I have found an interesting link: https://github.com/aws-samples/sagemaker-studio-custom-image-samples but my knowledge is a bit limited and I do not know what exactly I should look at precisely to see the example I should follow.

Any advice/lead you could suggest please ?

Thanks

To confirm, are you making use of SageMaker Notebook Instances or SageMaker Studio? Regarding Studio, Lifecycle scripts are suited for customization includes installing custom packages. If you would like to make use of a custom kernel you would need to build your own container. You could look at using an example in the GitHub repo as as starting point. — Marc Karp
– Marc Karp, Commented Apr 5, 2022 at 21:10
@MarcK , I am using SageMaker Notebook instances. I will precise it, thank you. — LaGabriella
– LaGabriella, Commented Apr 6, 2022 at 23:51

Raghu Ramesha · Accepted Answer · 2022-04-05 23:31:52Z

1

SageMaker Data Science Kernel supports Python 3.6 version at the moment. If you need a persistent custom kernel in SageMaker studio, you can create an ECR repository and build a docker image with custom environment configurations. This image can then be attached to the SageMaker studio notebooks. Reference link!

answered Apr 5, 2022 at 23:31

Raghu Ramesha

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2 Comments

LaGabriella Over a year ago

I edited my initial post, I am using SageMaker notebook instances. I guess your solution only works for Studio ? Thanks

Raghu Ramesha Over a year ago

That's correct the above reference is for SageMaker Studio. For creating a custom image for SageMaker notebooks you can use - github.com/aws-samples/…

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