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Crie uma instância de notebooks gerenciado
usando o console do Google Cloud
Saiba como criar uma instância de notebooks gerenciados do Vertex AI Workbench e abrir o JupyterLab usando o Console do Google Cloud.
Nesta página, também descrevemos como interromper, iniciar, redefinir ou excluir uma instância de notebooks gerenciados.
Para seguir as instruções detalhadas desta tarefa diretamente no
console do Google Cloud, clique em Orientação:
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.
Na janela Criar instância, no campo Nome,
insira my-instance.
Clique em Criar.
Ao concluir as tarefas descritas neste documento, é possível evitar
o faturamento contínuo excluindo os recursos criados. Saiba mais em
Limpeza.
Abrir JupyterLab
Depois que você cria instância, o Vertex AI Workbench a inicia
automaticamente. Quando a instância estiver pronta para uso, o Vertex AI Workbench ativa um link Abrir JupyterLab.
Ao lado do nome da instância de notebooks gerenciados, clique em Abrir JupyterLab.
Na caixa de diálogo Autenticar o notebook gerenciado, clique no botão
para receber um código de autenticação.
Escolha uma conta e clique em Permitir. Copie o código de autenticação.
Na caixa de diálogo Autenticar seu notebook gerenciado, cole o código de autenticação e clique em Autenticar.
Sua instância de notebooks gerenciados abre o JupyterLab.
Abrir um novo arquivo de notebook
Selecione File -> New -> Notebook.
Na caixa de diálogo Selecionar kernel, selecione Python
e clique em Selecionar.
O novo arquivo do notebook será aberto.
Alterar o kernel
É possível alterar o kernel do arquivo do notebook do JupyterLab no menu
ou no arquivo.
Menu
No JupyterLab, no menu Kernel, clique em Change kernel.
Na caixa de diálogo Selecionar kernel, selecione outro kernel para usar.
Clique em Selecionar.
No arquivo
No arquivo do notebook do JupyterLab, clique no nome do kernel.
Na caixa de diálogo Selecionar kernel, selecione outro kernel para usar.
Clique em Selecionar.
Interromper a instância
No Console do Google Cloud, acesse a página Notebooks gerenciados.
A redefinição forçada de uma instância exclui permanentemente o conteúdo da memória da sua
máquina virtual (VM) e a redefine para o estado inicial.
Para saber mais, consulte Redefinir
uma VM.
No Console do Google Cloud, acesse a página Notebooks gerenciados.
Selecione a linha que contém a instância que você quer excluir.
Clique deleteExcluir.
Dependendo do tamanho da janela,
o botão Excluir vai estar no
menu "opções" (more_vert).
Para confirmar, clique em Excluir.
A seguir
Teste um dos tutoriais incluídos
na nova instância de notebooks gerenciados.
No navegador de arquivos JupyterLab,
foldernavegador de arquivos, abra a pasta tutoriais e abra um dos arquivos de notebook.
[[["Fácil de entender","easyToUnderstand","thumb-up"],["Meu problema foi resolvido","solvedMyProblem","thumb-up"],["Outro","otherUp","thumb-up"]],[["Difícil de entender","hardToUnderstand","thumb-down"],["Informações incorretas ou exemplo de código","incorrectInformationOrSampleCode","thumb-down"],["Não contém as informações/amostras de que eu preciso","missingTheInformationSamplesINeed","thumb-down"],["Problema na tradução","translationIssue","thumb-down"],["Outro","otherDown","thumb-down"]],["Última atualização 2025-08-18 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)."]]
Redefinir.