Getting started with Serverless AI Devlabs: Deploy JupyterLab®

Serverless AI Devlabs provide an interactive environment for coding and prototyping without the need to manage infrastructure. This quickstart shows how to create a Devlab from the JupyterLab® template and open it in your browser.

Prerequisites

Web console
CLI

Make sure you are in a group that has at least the editor role within your tenant or project; for example, the default editors group. You can check this in the Administration → IAM section of the web console.
In the Administration → Limits → Quotas section, check the following quotas:
- Number of virtual machines (VMs) under Compute: make sure that at least one VM is available.
- Total number of allocations under Virtual Private Cloud: make sure that at least one allocation is available.
If necessary, increase the quotas.

Make sure you are in a group that has at least the editor role within your tenant or project; for example, the default editors group. You can check this in the Administration → IAM section of the web console.
In the Administration → Limits → Quotas section, check the following quotas:
- Number of virtual machines (VMs) under Compute: make sure that at least one VM is available.
- Total number of allocations under Virtual Private Cloud: make sure that at least one allocation is available.
If necessary, increase the quotas.
Install and configure the Nebius AI Cloud CLI. Check that your project ID is saved in the Nebius AI Cloud CLI profile configuration:
cat ~/.nebius/config.yaml

Steps

Create a Devlab

Web console
CLI

In the sidebar, go to Serverless AI → Devlabs.
Click Create Devlab, choose Template, and select JupyterLab.
Review the prefilled Devlab settings. The console generates the Jupyter token automatically. Copy and save the token securely.
Click Create Devlab.

Create a random Jupyter token of exactly 16 alphanumeric characters. For example:
export JUPYTER_TOKEN=$(openssl rand -hex 8)
Create a Devlab from the JupyterLab template:
nebius ai devlab create \ --name my-jupyter \ --template jupyter \ --input jupyter_token=$JUPYTER_TOKEN
The command uses the following parameters:
- --name: Devlab name.
- --template: Template to use. In this quickstart, use jupyter for the JupyterLab template.
- --input jupyter_token=<token>: Jupyter token that you provide. The token must consist of 16 alphanumeric characters.
--platform, --preset and --disk-size are optional. If you omit them, the CLI selects the default GPU platform, the smallest suitable preset and a 250 GiB disk. Save the Devlab ID from the create command output. You will need it in the next steps.

Wait for the Devlab to start running.

Open JupyterLab

When the Devlab is running, open its managed HTTPS URL in a browser. A public IP address is not required.

Web console
CLI

In the sidebar, go to Serverless AI → Devlabs.
Open the page of the required Devlab.
Wait until the Devlab is running. Then, in the Network section, copy the public Devlab address from the Public Devlabs field.
In a browser, open the URL and enter the Jupyter token in the JupyterLab password field. Use the token that the console generated when you created the Devlab.

List Devlabs and copy the ID of the Devlab that you created (my-jupyter):
nebius ai devlab list
You can also copy the Devlab ID from the create command output, if it was printed, or from the overview page in the web console. The ID is shown under the Devlab name.
Save the Devlab ID to an environment variable:
export DEVLAB_ID=<devlab_ID>
Get the Devlab details and copy the HTTPS URL from the output:
nebius ai devlab get "$DEVLAB_ID"
In a browser, open the HTTPS URL and enter the Jupyter token in the JupyterLab password field. Use the $JUPYTER_TOKEN value that you set at create time.

View logs

Web console
CLI

In the sidebar, go to Serverless AI → Devlabs.
In the Devlab list, next to the Devlab, click View logs. Alternatively, click → View logs.

View Devlab logs:

nebius ai devlab logs "$DEVLAB_ID" --follow

Expected results

The JupyterLab Devlab reaches the Running status.
You can open JupyterLab from the managed HTTPS URL and sign in with the Jupyter token in the password field.
You can view Devlab logs.

Delete the Devlab

If you no longer need the Devlab, delete it. Once you delete the Devlab, you will not be charged for its computing resources or container disk.

Web console
CLI

In the sidebar, go to Serverless AI → Devlabs.
In the Devlab list, find the Devlab and click → Delete.
Confirm the Devlab deletion.

nebius ai devlab delete "$DEVLAB_ID"

AI services in Nebius AI Cloud

Serverless AI

Managed Service for MLflow

Applications in Nebius AI Cloud

Tutorials

Third-party integrations

Getting started with Serverless AI Devlabs: Deploy JupyterLab®

Prerequisites

Steps

Create a Devlab

Open JupyterLab

View logs

Expected results

Delete the Devlab

See also

​Prerequisites

​Steps

​Create a Devlab

​Open JupyterLab

​View logs

​Expected results

​Delete the Devlab

​See also

Prerequisites

Steps

Create a Devlab

Open JupyterLab

View logs

Expected results

Delete the Devlab

See also