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How To Run Jupyter from a Remote Server (such as on an Azure DSVM)

Referenced from: https://ljvmiranda921.github.io/notebook/2018/01/31/running-a-jupyter-notebook/

Step 1: Run Jupyter Notebook from remote machine

Log-in to your remote machine the usual way you do. In most cases, this is simply done via an ssh command. Once the console shows, type the following:

remoteuser@remotehost: jupyter notebook --no-browser --port=XXXX

# Note: Change XXXX to the port of your choice. Usually, the default is 8888. 
# You can try 8889 or 8890 as well.
  • jupyter notebook: simply fires up your notebook
  • --no-browser: this starts the notebook without opening a browser
  • --port=XXXX: this sets the port for starting your notebook where the default is 8888. When it's occupied, it finds the next available port.

Step 2: Forward port XXXX to YYYY and listen to it

In your remote, the notebook is now running at the port XXXX that you specified. What you'll do next is forward this to port YYYY of your machine so that you can listen and run it from your browser. To achieve this, we write the following command:

localuser@localhost: ssh -N -f -L localhost:YYYY:localhost:XXXX remoteuser@remotehost
  • ssh: your handy ssh command. See man page for more info
  • -N: suppresses the execution of a remote command. Pretty much used in port forwarding.
  • -f: this requests the ssh command to go to background before execution.
  • -L: this argument requires an input in the form of local_socket:remote_socket. Here, we're specifying our port as YYYY which will be binded to the port XXXX from your remote connection.

Step 3: Fire-up Jupyter Notebook

To open up the Jupyter notebook from your remote machine, simply start your browser and type the following in your address bar:

localhost:YYYY

Again, the reason why we're opening it at YYYY and not at XXXX is because the latter is already being forwarded to the former. XXXX and YYYY can be the "same" number (not the same port, technically) because they are from different machines.

If you're successful, you should see the typical Jupyter Notebook home screen in the directory where you ran the command in Step 1. At the same time, if you look in your remote terminal, you should see some log actions happening as you perform some tasks.

In your first connection, you may be prompted to enter an Access Token as typical to most Jupyter notebooks. Normally, I'd just copy-paste it from my terminal, but to make things easier for you, you can set-up your own notebook password.

Closing all connections

To close connections, I usually stop my notebook from remote via CTRL + C then Y, and kill the process on YYYY via:

localuser@localhost: sudo netstat -lpn |grep :YYYY

# This will show the process ID (PID), e.g. ABCDEF of the one running in YYYY,
# you can kill it by simply typing

localuser@localhost: kill ABCDEF