Generating Your SSH Public Key. In order to provide a public key, each user in your system must generate one if they don’t already have one. See the GitHub. Jan 30, 2019 Please note that the steps and instructions. This will generate a new SSH key. Click the “Add SSH key” to complete the process of adding the SSH key to your Github account. Step add-ssh-key. Wercker allows you to generate SSH keys and expose them as via environment variables to your build or deployment pipeline. This step can be used to write these values to an IdentityFile and add them to the SSH configuration. This repo contains a showcase of how to use SSH certificates (for hosts & users) generated by step-ca using the step CLI's ssh sub-command. If you haven't already you should read our blog post on why SSH certificates are better than SSH public keys for authentication and how you can achieve de facto SSH Single Sign-on while doing away with pesky public key management across.

Being new to training ML models using Google Cloud VM instances, I faced issues where my ssh connection to the cloud instance (using either the clound web-based ssh client or using cloud shell) would disconnect from time to time (for example when I power off my laptop or the network gets disconnected) which would terminate the model training process. Therefore I searched for a ssh client that can handle disconnection and can resume connection without disrupting the process running on the server and came across with Mosh mobile shell, a remote terminal app that supports roaming.

It took me a while to figure out how to set up a third party ssh terminal using the google cloud OAuth. Here's a step-by-step guide:

Update: a simpler alternative for persisting remote sessions

Since this writing, another Mosh user kindly advised me that using terminal multiplexer could achive my use case mentioned above but with much less effort, I tried and it works like a charm, thanks Jan! Here's how:

'For the use case you mentioned, it's probably more convenient to use tmux. It's a terminal multiplexer, so you can disconnect from the machine but keep your terminals open. To start it, run 'tmux'. You know you’re in tmux if you see a green status bar at the bottom. Start your ML training program like you normally would, then press ctrl+b, then d. You should see something like [detached (from session 0)]. Now you can disconnect from the machine, and your program will keep running. If you want to check back on its progress, log back in and type 'tmux attach'. Now you can detach again, close the terminal or run another command. It's very convenient.'

Prerequisite

You should have created a Google Cloud VM instance (Compute Engine) and be able to ssh into the instance using the cloud, using cloud console.

I'm using MacOS Hign Sierra, but OS version shouldn't matter much.

Enable OS login

This step allows compute GCP to generate SSH keys automatically based on Google OAuth, so we don't need to generate ssh keys manually. Alternatively we could manually setup public and private ssh keys to manage the connection (see doc), but it might break the web-based ssh connection or cloud shell access.

In my case, I've granted access for my user account marcwjj@gmail.com, which is part of the organization.

Install gcloud SDK and ssh into remote instance using gcloud command to generate public and private ssh keys

Then run the following command from mac terminal to access to cloud instance

When you connect for the first time, there will be a browser popup that asks which google account to use for authentication. Make sure to choose the same user account that was granted access in the previous OS login step. This allows the gcloud command line to generate public and private ssh keys that will be used to access the remote server.

Once connected, type exit to logoff the ssh session. You can now find the public and private ssh keys stored under ${HOME}/.ssh/

To test that the ssh keys are properly setup, run the following command from the mac terminal. Make sure to use your user account and cloud instance external IP address, in the format of youremail_gmail_com@external_ip

Install Mosh on client (your Mac) and on server (Google cloud VM instance)

Client

Download the mac package and install. After installation, test by running mosh-client in mac terminal.

Server

Remote access to server using gcloud command line

Actual free working key generator for farmville 2. And install depending on your VM instance OS following the instructions, for Debian, run

Once installed, run mosh-server to test server installation.

Allow UDP connections on Google cloud VM instances

Mosh server-client will establish UDP connections using ports 60000 - 61000, so we need to allow these connections by configuring the firewall rules on cloud.

Step By Step Instructions Generate Ssh Key Github Free

• In the google cloud web console, go to VPC network -> Firewall rules settings page
• Create a rule named allow-mosh-udp with the following settings

How To Generate Ssh Key Pair

Connect to remote server from Mac terminal using Mosh

Finally, you should be able to connect to cloud server using Mosh roaming connections from your mac terminal, using a command such as the following:

Step By Step Instructions Generate Ssh Key Github Tutorial

Voila, now you can run your model trainings for hours on your cloud instances without worrying about any ssh disconnections, and when it's reconnected, you can get back to previous state before the disconnection, as if you are working in front of the remote server.

I hope this guide is useful for other people like me who are new to google cloud / ssh. If you have any questions or have a better way of making cloud ssh access robust and roamable, leave a comment here or shoot me an email at marcwjj@gmail.com.

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Happy machine learning and Moshing!😄âx9D¤ï¸x8F