How to remotely connect to GCP ML Engine/AWS Sagemaker managed notebooks?

Question

GCP has finally released managed Jupyter notebooks. I would like to be able to interact with the notebook locally by connecting to it. Ie. i use PyCharm to connect to the externaly configured jupyter notebbok server by passing its URL & token param.

Question also applies to AWS Sagemaker notebooks.

Answer 1

GCP has finally released managed Jupyter notebooks. I would like to be able to interact with the notebook locally by connecting to it. Ie. i use PyCharm to connect to the externaly configured jupyter notebbok server by passing its URL & token param.

Question also applies to AWS Sagemaker notebooks.

Answer 2

GCP has finally released managed Jupyter notebooks. I would like to be able to interact with the notebook locally by connecting to it. Ie. i use PyCharm to connect to the externaly configured jupyter notebbok server by passing its URL & token param.

Question also applies to AWS Sagemaker notebooks.

Answer 3

GCP has finally released managed Jupyter notebooks. I would like to be able to interact with the notebook locally by connecting to it. Ie. i use PyCharm to connect to the externaly configured jupyter notebbok server by passing its URL & token param.

Question also applies to AWS Sagemaker notebooks.

Answer 4

GCP has finally released managed Jupyter notebooks. I would like to be able to interact with the notebook locally by connecting to it. Ie. i use PyCharm to connect to the externaly configured jupyter notebbok server by passing its URL & token param.

Question also applies to AWS Sagemaker notebooks.

Answer 5

There is a way to SSH into a Sagemaker notebook instance without having to use a third party reverse proxy like ngrok, nor setup an EC2 bastion, nor using AWS Systems Manager, here is how you can do it.

Prerequisites

• Use your own VPC and not the VPC managed by AWS/Sagemaker for the notebook instance
• Configure an ingress rule in the security group of your notebook instance to allow SSH traffic (port 22 over TCP)

How to do it

• Create a lifecycle script configuration that is executed when the instance starts
• Add the following snippet inside the lifecycle script:

INSTANCE_IP=$(/sbin/ifconfig eth2 | grep 'inet addr:' | cut -d: -f2 | awk '{ print $1}')
echo "SSH into the instance using : ssh ec2-user@$INSTANCE_IP" > ~ec2-user/SageMaker/ssh-instructions.txt

• Add your public SSH key inside /home/ec2-user/.ssh/authorized_keys , either manually with the terminal of jupyterlab UI, or inside the lifecycle script above

When your users open the Jupyter interface, they will find the ssh-instructions.txt file which gives the host and command to use: ssh ec2-user@<INSTANCE_IP>

If you want to SSH from a local environment, you'll probably need to connect to your VPN that routes your traffic inside your VPC.

Answer 6

I've found not being able to SSH to notebook instances too limiting so I've build a guide to set it up by using the bastion box. https://ruslanmv.com/blog/How-to-connect-to-Sagemaker-Notebook-via-SSH I hope this can be helpful. :)