> ## Documentation Index > Fetch the complete documentation index at: https://docs.nebius.com/llms.txt > Use this file to discover all available pages before exploring further. # Deploying the JupyterLab® application in Nebius AI Cloud To work with JupyterLab notebooks in Nebius AI Cloud, you can deploy the JupyterLab application in the [web console](https://console.nebius.com). ## Prerequisites Make sure you are in a [group](/iam/authorization/groups/index) that has at least the `editor` role within your tenant; for example, the default `editors` group. You can check this in the [Administration → IAM](https://console.nebius.com/iam) section of the web console. ## How to deploy 1. In the [web console](https://console.nebius.com), go to  **Applications**. 2. Find JupyterLab by searching for it or browsing by category, then open the application page. 3. Deploy the application as a [container over a Compute virtual machine](/compute/virtual-machines/containers). You create the VM from the application page, and the JupyterLab container image is pre-selected: 1. Click **Deploy on VM**. The creation page for a container over VM opens. 2. Select the project and specify the VM name. 3. Configure computing resources: * Select **With GPU** or **Without GPU**, then choose a platform and preset. Available options depend on the region. * In **Local storage**, specify the disk size. 4. In **Access**, add a username and an SSH key. Copy and save any generated password or token shown on the page. 5. (Optional) In advanced settings, configure the network, subnet, public or private IP address, or a service account. 6. Click **Create container over VM**. 7. Wait until the VM is running. It takes about five minutes. ## What's next When the application is running, you can [connect to it](./connect). *** *"Jupyter" and the Jupyter logos are trademarks or registered trademarks of LF Charities, used by Nebius B.V. with permission.*