if I change it to 0.0.0.0 it works

which I looked at previously to see if I could import sagemaker.kg or kernelgateway or something, but no luck

SageMaker Studio:

So it's seemingly not the image, but maybe something to do with how Studio runs it as a kernel.

Yeah I think that for some reason it fails detecting this is actually jupyter noteboko (not really sure why), Thank you for double checking on the container !!

nope, that's wrong

lots of things like {"__timestamp__": "2023-02-23T23:49:23.285946Z", "__schema__": "sagemaker.kg.request.schema", "__schema_version__": 1, "__metadata_version__": 1, "account_id": "", "duration": 0.0007679462432861328, "method": "GET", "uri": "/api/kernels/6ba227af-ff2c-4b20-89ac-86dcac95e2b2", "status": 200}

Hi @<1532532498972545024:profile|LittleReindeer37>
Yes you are correct it should capture the entire jupyter notebook in sagemaker studio.
Just verifying this is the use case, correct ?

looks like the same as in server_info

but the only exception handler is for requests.exceptions.SSLError

Just ran the same notebook in a local Jupyter Lab session and it worked as I expected it might, saving a copy to Artifacts

sounds good, thanks!

I've poked around both the internal URL that Jupyter kernel is running on and some of the files in /sagemaker/.jupyter but no luck so far - I can find plenty of kernel info, but not session

weird that it won't return that single session

I additionally tried using a Sagemaker Notebook instance, to see if it was the kernel dockerization that Studio uses that was messing things up. But it seems to actually log less information from a Notebook instance vs Studio .

and this

server_info['url'] = f"http://{server_info['hostname']}:{server_info['port']}/{server_info['base_url']}/"