> ## Documentation Index
> Fetch the complete documentation index at: https://docs.cloud.vessl.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Understand workspaces

> What a workspace is and why it matters for ML development on VESSL Cloud.

<Tip>
  **Workspaces work from the CLI too.** Create, list, SSH into, pause, and terminate workspaces from your terminal with `vesslctl workspace`. See the [CLI cheat sheet](/cli/cheatsheet) for a one-page command reference, or [vesslctl workspace](/cli/commands/workspace) for the full flag reference.
</Tip>

**[Workspace](/guides/get-started/glossary#workspace)** lets you instantly run a containerized environment with [GPU](/guides/get-started/glossary#gpu) and CPU resources for ML development.

In a workspace, you can run code using JupyterLab or connect using SSH.

* Start quickly without complex infrastructure setup
* Choose resources and launch instantly
* Pause to preserve the environment at lower cost, or Terminate to stop billing

<div>
  <Frame>
    <img src="https://mintcdn.com/dora/vPFagCAoutrvcxVV/images/understandworkspaces.png?fit=max&auto=format&n=vPFagCAoutrvcxVV&q=85&s=1cd85c3d5c70c3ea8e496f2791636bf8" alt="Workspace tab listing running and paused environments with their resources and cost" width="1920" height="1266" data-path="images/understandworkspaces.png" />
  </Frame>

  <small>Example: Workspace overview</small>
</div>