Nice

looks like the same as in server_info

yeah, even then it'll run but return 0 notebooks

curious whether it impacts anything besides sagemaker. I'm thinking it's generically a kernel gateway issue, but I'm not sure if other platforms are using that yet

Try to add here:
None

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

and the only calls to "uri": "/api/sessions" are the ones I made during testing - sagemaker doesn't seem to ever call that itself

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

nope, that's wrong

so notebook path is empty

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 ?

sh-4.2$ cat /var/log/studio/kernel_gateway.log | head -n10
{"__timestamp__": "2023-02-23T21:48:28.036559Z", "__schema__": "sagemaker.kg.request.schema", "__schema_version__": 1, "__metadata_version__": 1, "account_id": "", "duration": 0.0012829303741455078, "method": "GET", "uri": "/api", "status": 200}
{"__timestamp__": "2023-02-23T21:48:39.111068Z", "__schema__": "sagemaker.kg.request.schema", "__schema_version__": 1, "__metadata_version__": 1, "account_id": "", "duration": 0.0012879371643066406, "method": "GET", "uri": "/api/kernels", "status": 200}
{"__timestamp__": "2023-02-23T21:48:39.116324Z", "__schema__": "sagemaker.kg.request.schema", "__schema_version__": 1, "__metadata_version__": 1, "account_id": "", "duration": 0.0007715225219726562, "method": "GET", "uri": "/api/terminals", "status": 200}
{"__timestamp__": "2023-02-23T21:48:39.272822Z", "__schema__": "sagemaker.kg.request.schema", "__schema_version__": 1, "__metadata_version__": 1, "account_id": "", "duration": 0.0007491111755371094, "method": "GET", "uri": "/api/terminals", "status": 200}
{"__timestamp__": "2023-02-23T21:48:43.000795Z", "__schema__": "sagemaker.kg.request.schema", "__schema_version__": 1, "__metadata_version__": 1, "account_id": "", "duration": 2.539133071899414, "method": "POST", "uri": "/api/kernels", "status": 201}
{"__timestamp__": "2023-02-23T21:48:43.073568Z", "__schema__": "sagemaker.kg.request.schema", "__schema_version__": 1, "__metadata_version__": 1, "account_id": "", "duration": 0.0013430118560791016, "method": "GET", "uri": "/api/kernels/6ba227af-ff2c-4b20-89ac-86dcac95e2b2", "status": 200}
{"__timestamp__": "2023-02-23T21:48:43.469751Z", "__schema__": "sagemaker.kg.request.schema", "__schema_version__": 1, "__metadata_version__": 1, "account_id": "", "duration": 0.0013761520385742188, "method": "GET", "uri": "/api/kernels/6ba227af-ff2c-4b20-89ac-86dcac95e2b2", "status": 200}
{"__timestamp__": "2023-02-23T21:48:43.702549Z", "__schema__": "sagemaker.kg.request.schema", "__schema_version__": 1, "__metadata_version__": 1, "account_id": "", "duration": 0.0013780593872070312, "method": "GET", "uri": "/api/kernels/6ba227af-ff2c-4b20-89ac-86dcac95e2b2", "status": 200}
{"__timestamp__": "2023-02-23T21:48:43.986808Z", "__schema__": "sagemaker.kg.request.schema", "__schema_version__": 1, "__metadata_version__": 1, "account_id": "", "duration": 0.0007445812225341797, "method": "GET", "uri": "/api/kernels/6ba227af-ff2c-4b20-89ac-86dcac95e2b2", "status": 200}
{"__timestamp__": "2023-02-23T21:48:43.992860Z", "__schema__": "sagemaker.kg.request.schema", "__schema_version__": 1, "__metadata_version__": 1, "account_id": "", "duration": 0.001028299331665039, "method": "GET", "uri": "/api/kernels", "status": 200}

yep

if I use the same kernel there'll be two

Hi @<1532532498972545024:profile|LittleReindeer37> @<1523701205467926528:profile|AgitatedDove14>
I got the session with a bit of "hacking".
See this script:

import boto3, requests, json
from urllib.parse import urlparse

def get_notebook_data():
    log_path = "/opt/ml/metadata/resource-metadata.json"
    with open(log_path, "r") as logs:
        _logs = json.load(logs)
    return _logs

notebook_data = get_notebook_data()
client = boto3.client("sagemaker")
response = client.create_presigned_domain_url(
    DomainId=notebook_data["DomainId"],
    UserProfileName=notebook_data["UserProfileName"]
)
authorized_url = response["AuthorizedUrl"]
authorized_url_parsed = urlparse(authorized_url)
unauthorized_url = authorized_url_parsed.scheme + "://" + authorized_url_parsed.netloc
with requests.Session() as s:
    s.get(authorized_url)
    print(s.get(unauthorized_url + "/jupyter/default/api/sessions").content)

Basically, we can get the session directly from AWS, but we need to be authenticated.
One way I found was to create a presigned url through boto3, by getting the domain id and profile name from a resoure-metadata file that is found on the machine None .
Then use that to get the session...
Maybe there are some other ways to do this (safer), but this is a good start. We know it's possible

environ{'PYTHONNOUSERSITE': '0',
        'HOSTNAME': 'gfp-science-ml-t3-medium-d579233e8c4b53bc5ad626f2b385',
        'AWS_CONTAINER_CREDENTIALS_RELATIVE_URI': '/_sagemaker-instance-credentials/xxx',
        'JUPYTER_PATH': '/usr/share/jupyter/',
        'SAGEMAKER_LOG_FILE': '/var/log/studio/kernel_gateway.log',
        'PATH': '/usr/local/sbin:/usr/local/bin:/usr/sbin:/usr/bin:/sbin:/bin:/tmp/miniconda3/condabin:/tmp/anaconda3/condabin:/tmp/miniconda2/condabin:/tmp/anaconda2/condabin',
        'REGION_NAME': 'us-east-1',
        'AWS_INTERNAL_IMAGE_OWNER': 'Custom',
        'AWS_DEFAULT_REGION': 'us-east-1',
        'PWD': '/home/sagemaker-user',
        'AWS_REGION': 'us-east-1',
        'SHLVL': '1',
        'HOME': '/home/sagemaker-user',
        'AWS_SAGEMAKER_PYTHONNOUSERSITE': '0',
        'AWS_ACCOUNT_ID': 'xxx',
        '_': '/opt/.sagemakerinternal/conda/bin/jupyter-kernelgateway',
        'LC_CTYPE': 'C.UTF-8',
        'KERNEL_LAUNCH_TIMEOUT': '40',
        'KERNEL_WORKING_PATH': '',
        'KERNEL_GATEWAY': '1',
        'JPY_PARENT_PID': '9',
        'PYDEVD_USE_FRAME_EVAL': 'NO',
        'TERM': 'xterm-color',
        'CLICOLOR': '1',
        'FORCE_COLOR': '1',
        'CLICOLOR_FORCE': '1',
        'PAGER': 'cat',
        'GIT_PAGER': 'cat',
        'MPLBACKEND': '

_inline'}

right now I can't figure out how to get the session in order to get the notebook path

As another test I ran Jupyter Lab locally using the same custom Docker container that we're using for Sagemaker Studio, and it works great there, just like the native local Jupyter Lab. So it's seemingly not the image, but maybe something to do with how Studio runs it as a kernel.

as best I can tell it'll only have one .ipynb in $HOME with this setup, which may work...

sounds good!

and this

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

so notebooks ends up empty

At the top there should be the URL of the notebook (I think)

it does return kernels, just not sessions

the problem is here: None

Hmm and you are getting empty list for thi one:

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

I can get it to run up to here: None

weird that it won't return that single session

that fails

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}