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Crea una instancia de notebooks administrados con la consola de Google Cloud
Obtén información para crear una instancia de notebook administrada de Vertex AI Workbench y abrir JupyterLab con la Google Cloud consola.
En esta página, también se describe cómo detener, iniciar, restablecer o borrar una instancia de notebooks administrados.
Para seguir la guía paso a paso sobre esta tarea directamente en la consola Google Cloud , haz clic en Guiarme:
Sign in to your Google Cloud account. If you're new to
Google Cloud,
create an account to evaluate how our products perform in
real-world scenarios. New customers also get $300 in free credits to
run, test, and deploy workloads.
In the Google Cloud console, on the project selector page,
select or create a Google Cloud project.
En la ventana Crear instancia, en el campo Nombre, ingresa my-instance.
Haz clic en Crear.
Cuando completes las tareas que se describen en este documento, podrás borrar
los recursos que creaste para evitar que se te siga facturando. Para obtener más información, consulta
Realiza una limpieza.
Abre JupyterLab
Después de crear la instancia, Vertex AI Workbench la inicia de forma
automática. Cuando la instancia está lista para usarse, Vertex AI Workbench
activa un vínculo Abrir JupyterLab.
Junto al nombre de la instancia de notebooks administrados,
haz clic en Abrir JupyterLab.
En el cuadro de diálogo Authenticate your managed notebook, haz clic en el botón
para obtener un código de autenticación.
Elige una cuenta y haz clic en Allow. Copia el código de autenticación.
En el cuadro de diálogo Authenticate your managed notebook,
pega el código de autenticación y, luego, haz clic en Authenticate.
Tu instancia de notebooks administrados abre JupyterLab.
Abre un archivo de notebook nuevo
Select Archivo > Nuevo > Notebook.
En el cuadro de diálogo Seleccionar Kernel, selecciona Python y haz clic en Seleccionar.
Se abrirá el archivo de notebook nuevo.
Cambia el kernel
Puedes cambiar el kernel de tu archivo de notebook de JupyterLab desde el menú o en el archivo.
Menú
En JupyterLab, en el menú Kernel, haz clic en Change kernel.
En el cuadro de diálogo Seleccionar kernel, selecciona otro kernel para usar.
Haz clic en Seleccionar.
En el archivo :
En el archivo del notebook de JupyterLab, haz clic en el nombre del kernel.
En el cuadro de diálogo Seleccionar kernel, selecciona otro kernel para usar.
Haz clic en Seleccionar.
Detén tu instancia
En la consola de Google Cloud , ve a la página Notebooks administrados.
Cuando se restablece una instancia, se borra por la fuerza el contenido de la memoria de la instancia y se restablece la instancia a su estado inicial. Para obtener más información sobre cómo funciona el restablecimiento de una instancia, consulta Restablece una instancia.
En la consola de Google Cloud , ve a la página Notebooks administrados.
Selecciona la fila que contiene la instancia que deseas borrar.
Haz clic en deleteBorrar.
(Según el tamaño de la ventana, puede que el botón Borrar esté en el menú de opciones de more_vert).
Para confirmar la acción, haz clic en Borrar.
¿Qué sigue?
Prueba uno de los instructivos que se incluye en tu nueva instancia de notebooks administrados.
En el Navegador de archivosfolder de JupyterLab, abre la carpeta de instructivos y abre uno de los archivos del notebook.
[[["Fácil de comprender","easyToUnderstand","thumb-up"],["Resolvió mi problema","solvedMyProblem","thumb-up"],["Otro","otherUp","thumb-up"]],[["Difícil de entender","hardToUnderstand","thumb-down"],["Información o código de muestra incorrectos","incorrectInformationOrSampleCode","thumb-down"],["Faltan la información o los ejemplos que necesito","missingTheInformationSamplesINeed","thumb-down"],["Problema de traducción","translationIssue","thumb-down"],["Otro","otherDown","thumb-down"]],["Última actualización: 2025-09-04 (UTC)"],[],[],null,["# Quickstart: Create a managed notebooks instance by using the Google Cloud console\n\nCreate a managed notebooks instance\nby using the Google Cloud console\n=====================================================================\n\n\n| Vertex AI Workbench managed notebooks is\n| [deprecated](/vertex-ai/docs/deprecations). On\n| April 14, 2025, support for\n| managed notebooks will end and the ability to create managed notebooks instances\n| will be removed. Existing instances will continue to function\n| but patches, updates, and upgrades won't be available. To continue using\n| Vertex AI Workbench, we recommend that you\n| [migrate\n| your managed notebooks instances to Vertex AI Workbench instances](/vertex-ai/docs/workbench/managed/migrate-to-instances).\n\n\u003cbr /\u003e\n\nLearn how to create a Vertex AI Workbench managed notebooks instance\nand open JupyterLab by using the Google Cloud console.\nThis page also describes how to stop, start, reset, or delete\na managed notebooks instance.\n\n*** ** * ** ***\n\nTo follow step-by-step guidance for this task directly in the\nGoogle Cloud console, click **Guide me**:\n\n[Guide me](https://console.cloud.google.com/freetrial?redirectPath=/?walkthrough_id=vertex-ai--workbench--managed--create-managed-notebooks-instance-console-quickstart)\n\n*** ** * ** ***\n\n\u003cbr /\u003e\n\nBefore you begin\n----------------\n\n- Sign in to your Google Cloud account. If you're new to Google Cloud, [create an account](https://console.cloud.google.com/freetrial) to evaluate how our products perform in real-world scenarios. New customers also get $300 in free credits to run, test, and deploy workloads.\n- In the Google Cloud console, on the project selector page,\n select or create a Google Cloud project.\n\n | **Note**: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.\n\n [Go to project selector](https://console.cloud.google.com/projectselector2/home/dashboard)\n-\n [Verify that billing is enabled for your Google Cloud project](/billing/docs/how-to/verify-billing-enabled#confirm_billing_is_enabled_on_a_project).\n\n-\n\n\n Enable the Notebooks API.\n\n\n [Enable the API](https://console.cloud.google.com/flows/enableapi?apiid=notebooks.googleapis.com&redirect=https://console.cloud.google.com)\n\n- In the Google Cloud console, on the project selector page,\n select or create a Google Cloud project.\n\n | **Note**: If you don't plan to keep the resources that you create in this procedure, create a project instead of selecting an existing project. After you finish these steps, you can delete the project, removing all resources associated with the project.\n\n [Go to project selector](https://console.cloud.google.com/projectselector2/home/dashboard)\n-\n [Verify that billing is enabled for your Google Cloud project](/billing/docs/how-to/verify-billing-enabled#confirm_billing_is_enabled_on_a_project).\n\n-\n\n\n Enable the Notebooks API.\n\n\n [Enable the API](https://console.cloud.google.com/flows/enableapi?apiid=notebooks.googleapis.com&redirect=https://console.cloud.google.com)\n\n\u003cbr /\u003e\n\nCreate an instance\n------------------\n\n1. In the Google Cloud console,\n go to the **Managed notebooks** page.\n\n [Go to Managed notebooks](https://console.cloud.google.com/vertex-ai/workbench/managed)\n2. Click add_box **Create new**.\n\n3. In the **Create instance** window, in the **Name** field,\n enter `my-instance`.\n\n4. Click **Create**.\n\nWhen you finish the tasks that are described in this document, you can avoid\ncontinued billing by deleting the resources that you created. For more information, see\n[Clean up](#clean-up).\n\nOpen JupyterLab\n---------------\n\nAfter you create your instance, Vertex AI Workbench automatically starts\nthe instance. When the instance is ready to use, Vertex AI Workbench\nactivates an **Open JupyterLab** link.\n\n1. Next to your managed notebooks instance's name,\n click **Open JupyterLab**.\n\n2. In the **Authenticate your managed notebook** dialog, click the button\n to get an authentication code.\n\n3. Choose an account and click **Allow**. Copy the authentication code.\n\n4. In the **Authenticate your managed notebook** dialog,\n paste the authentication code, and then click **Authenticate**.\n\n Your managed notebooks instance opens JupyterLab.\n\nOpen a new notebook file\n------------------------\n\n1. Select **File \\\u003e New \\\u003e Notebook**.\n\n2. In the **Select kernel** dialog, select **Python** ,\n and then click **Select**.\n\n Your new notebook file opens.\n\nChange the kernel\n-----------------\n\nYou can change the kernel of your JupyterLab notebook file from the menu\nor in the file. \n\n### Menu\n\n1. In JupyterLab, on the **Kernel** menu, click **Change kernel**.\n\n2. In the **Select kernel** dialog, select another kernel to use.\n\n3. Click **Select**.\n\n### In the file\n\n1. In your JupyterLab notebook file, click the kernel name.\n\n2. In the **Select kernel** dialog, select another kernel to use.\n\n3. Click **Select**.\n\nStop your instance\n------------------\n\n1. In the Google Cloud console, go to the **Managed notebooks** page.\n\n [Go to Managed notebooks](https://console.cloud.google.com/vertex-ai/workbench/managed)\n2. Select the instance that you want to stop.\n\n3. Click square **Stop**.\n\nStart your instance\n-------------------\n\n1. In the Google Cloud console, go to the **Managed notebooks** page.\n\n [Go to Managed notebooks](https://console.cloud.google.com/vertex-ai/workbench/managed)\n2. Select the instance that you want to start.\n\n3. Click arrow_right **Start**.\n\nReset your instance\n-------------------\n\nResetting an instance forcibly wipes the memory contents of your instance and\nresets the instance to its initial state. To learn more about how resetting an\ninstance works, see\n[Resetting an instance](/compute/docs/instances/suspend-stop-reset-instances-overview#resetting-instance).\n\n1. In the Google Cloud console, go to the **Managed notebooks** page.\n\n [Go to Managed notebooks](https://console.cloud.google.com/vertex-ai/workbench/managed)\n2. Select the instance that you want to reset.\n\n3. Click\n\n **Reset** , and then click **Reset** to confirm.\n\nClean up\n--------\n\n\nTo avoid incurring charges to your Google Cloud account for\nthe resources used on this page, follow these steps.\n\nIf you created a new project to learn about\nVertex AI Workbench managed notebooks\nand you no longer need the project, then\n[delete the project](https://console.cloud.google.com/cloud-resource-manager).\n\nIf you used an existing Google Cloud project, then delete the resources\nyou created to avoid incurring charges to your account:\n\n1. In the Google Cloud console, go to the **Managed notebooks** page.\n\n [Go to Managed notebooks](https://console.cloud.google.com/vertex-ai/workbench/managed)\n2. Select the row containing the instance that you want to delete.\n\n3. Click delete **Delete** .\n (Depending on the size of your window,\n the **Delete** button might be in\n the more_vert options menu.)\n\n4. To confirm, click **Delete**.\n\nWhat's next\n-----------\n\n- Try one of the tutorials that is included\n in your new managed notebooks instance.\n In the JupyterLab folder **File Browser** , open the **tutorials** folder,\n and open one of the notebook files.\n\n- Read the [Introduction to managed notebooks](/vertex-ai/docs/workbench/managed/introduction).\n\n- To learn more about advanced settings\n for managed notebooks instances, see [Create\n a managed notebooks instance](/vertex-ai/docs/workbench/managed/create-instance)."]]
Restablecer y, luego, en Restablecer para confirmar.