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That ports are exposed on the login node! It’s probably better that way, because in cases where you do get ports it’s sort of a At least at my current employer it’s not even the case I’m not sure in practice how common this is anymore. $ ssh " $DOMAINNAME " -l $FORWARD_USERNAME -K -L $PORT: $MACHINE: $PORT -N & The ssh command in this case utilizes the flag -K that forwards the login credentials to the compute node: Not Isolatedįor HPCs where the compute node is not isolated from the outside world the ssh command for port forwarding first establishes a connection the login node, but then continues to pass on the login credentials to the compute node to establish a tunnel between the localhost and the port on the compute node. The -N says “don’t execute a remote command (and just forward the port).”įinally, the last $MACHINE is the node that the jupyter notebook is running on. You’ll notice it looks just like the first, and this works because ssh commands can be chained. The next line ssh -L $PORT:localhost:$PORT -N "$MACHINE" & is a second command run from the login node,Īnd port forwards it to the compute node, since you can only access the compute node from the login nodes. Since we are forwarding ports, this would require minimally the login node to expose ports. Warded over the secure channel, and a connection is made toĮither host port hostport, or the Unix socket remote_socket,įorward whatever is running on the second port on my resource to my local machine. Made to the local port or socket, the connection is for‐ Port on the local side, optionally bound to the specifiedīind_address, or to a Unix socket. This works by allocating a socket to listen to either a TCP Given host and port, or Unix socket, on the remote side. Specifies that connections to the given TCP port or Unix socket on the local (client) host are to be forwarded to the The “-L” in the above (from the man pages) : $ ssh -L $PORT:localhost: $PORT $) is executed on the local machine, which establishes a port forwarding to the login node.