Overview

Learn about Vast.ai connection methods—SSH, Jupyter, and Entrypoint—and how each controls instance access and workflow.

Choose how to access your GPU instances based on your workflow needs.

Connection Methods

SSH Access

Terminal access with port forwarding and VS Code support

Jupyter Lab

Web-based notebooks for interactive development

Note: For automated execution without interactive access, see Entrypoint below.

Additional Options

Instance Portal

Web access to any application via secure tunnels

Port Networking

Configure exposed ports and bandwidth settings

Entrypoint

For this launch mode we simply run a docker container from your specified image as is. The docker image entrypoint is the main run process, which you can override in the GUI or CLI (—entrypoint). You can also pass arguments to your entrypoint in the GUI or CLI (—args). Entrypoint launch mode is suitable for GPU worker instances which receive tasks from your webserver. As ssh/jupyter access is not provided, your docker image is responsible for setting up any such connections as needed.

SSH

For this launch option we setup an ssh connection using proxy and or direct connections where appropriate (mapping to port 22 internal). If the machine supports open ports our system will try to setup both a direct ssh connection and a backup proxy connection. This is mostly automatic under the hood, but it does require that your docker image is compatible with typical ssh daemon setup.

With the SSH launch option your docker image entrypoint is not called as we must override it. Instead we allow you to specify an onstart script which is called as part of the new entrypoint.

So if you are using making a template from an existing docker image, you typically will want to find its entrypoint command and move that to the onstart.

More information on SSH/SCP

Jupyter

For this launch option we setup a jupyter using a proxy and or direct connections where appropriate (mapping to port 8080 internal). If the machine supports open ports our system will try to setup a direct jupyter connection with a custom HTTPS certificate. This is mostly automatic under the hood, but it does require that your docker image is compatible with typical jupyter setup.

With the Jupyter launch option your docker image entrypoint is not called as we must override it. Instead we allow you to specify an onstart script which is called as part of the new entrypoint.

So if you are using making a template from an existing docker image, you typically will want to find its entrypoint command and move that to the onstart.

More information on Jupyter and installing the certificate