Workspaces

Organize your projects with persistent storage.

What is a Workspace?

A workspace is a named storage volume that persists between sessions. When you SSH to runtime.ovh, the workspace name is the first part of your username:

ssh myproject@runtime.ovh
    ↑ workspace name

Each workspace has its own /data/ directory that persists even after you disconnect.

Create a Workspace

Workspaces are created automatically when you first connect:

# This creates the "webapp" workspace if it doesn't exist
ssh webapp@runtime.ovh

List Workspaces

Use the CLI to see your workspaces:

ssh cli@runtime.ovh ws list

Output:

NAME        SIZE    CREATED
myproject   245 MB  2024-01-15
webapp      1.2 GB  2024-01-10
ml-exp      4.5 GB  2024-01-08

Delete a Workspace

Remove a workspace and all its data:

ssh cli@runtime.ovh ws delete myproject

Warning: This permanently deletes all files in the workspace. There is no undo.

Workspace Naming

Workspace names must be:

# Valid names
ssh my-project@runtime.ovh
ssh webapp2024@runtime.ovh
ssh ml-experiment-1@runtime.ovh

# Invalid names
ssh My-Project@runtime.ovh    # uppercase
ssh 123project@runtime.ovh    # starts with number
ssh ab@runtime.ovh            # too short

Storage Limits

Tier Max Workspaces Storage per Workspace
FREE 3 1 GB
IDENTIFIED 10 5 GB
PAID 50 50 GB

Workspace Storage

Inside a container, your workspace is mounted at /data/:

# Files here persist
/data/
  script.py
  config.json
  results/

# Files here are ephemeral (lost on disconnect)
/tmp/
/home/
/root/

Tip: Always save important files to /data/. Everything outside is lost when the container stops.

Check Storage Usage

From inside a container:

du -sh /data/

Or via CLI:

ssh cli@runtime.ovh ws info myproject

Multiple Workspaces

Use different workspaces to organize different projects:

# Web development project
ssh webapp:node@runtime.ovh

# Machine learning experiments
ssh ml-exp:pytorch:v100@runtime.ovh

# Backend API
ssh api-server:go@runtime.ovh