This quickstart is for Members (end users). If you’re the first person in your org, you’re also the Admin. See the Admin quickstart after completing this flow.
Create account
Go to cloud.vessl.ai and create an account. Verify your email to activate your account.

Complete your profile
After verifying your email, enter your ID (username), select your Occupation and Use case. Check the required boxes to agree to the Terms of Service and confirm your age, then click Let’s get started!

Create organization
Enter your organization name and click Create to set up your workspace.

Explore the dashboard
After creating your organization, you’ll land on the main Workspaces dashboard. This is where you can manage all your compute environments.

Register payment method
Before creating workspaces, register a payment method. Go to Organization > Billing in the sidebar. Click Manage payment method to add your card, then use Add credits to top up your credit balance.

Create a storage volume
VESSL Cloud provides two storage types:
- Object storage: S3-backed, accessible across all clusters. Ideal for sharing data.
- Cluster storage: High-performance CephFS/NVMe, bound to one cluster. Ideal for code and environments.

Object storage is slower than Cluster storage and not suitable as your main workspace. Do not mount it at
/root — use a path like /shared instead.Cluster storage volumes are managed by Organization Admins. If Cluster storage is available for your team, you can also create volumes under Cluster storage in the sidebar.Since
$HOME (/root) is the home directory in workspaces, we recommend mounting your Cluster storage volume at $HOME for easy access.Cluster storage is region-bound — when creating a workspace, only volumes from the same region as your selected GPU will appear.Create a workspace
Open the Workspace tab in the sidebar and click New Workspace. Enter a name, then select a GPU product, region, and GPU count under Resource spec for testing.Attach the Object storage volume you just created, then click Create.
You can run Jupyter notebooks directly in this workspace.

Explore workspace details

- Connect: In the workspace detail page, open the Connect tab to access using Jupyter (port 8888) or SSH (port 22). See Connect.
- Details: view GPU, volumes, image and other specs.
- Logs: view container logs in real time.
- Metrics: monitor CPU/GPU/Memory graphs.
Run code in JupyterLab
In the workspace detail page, open the Connect tab and click JupyterLab.
In JupyterLab, create a If the output prints successfully, your environment is ready.

Notebook → Python 3 (ipykernel). Run the following code:Clean up
To avoid charges: go to the Workspace tab in the sidebar, stop a running workspace from the kebab menu, and confirm Pause Workspace and Terminate to completely delete the workspace.
To permanently remove a workspace: Click Terminate from the kebab menu and confirm by typing the workspace name and clicking Delete.

