GitHub repository: kikibillz/gads-2020-pratice-project
Created: 2020-09-09T11:22:16Z
Description: In the Cloud Console, on the project selector page, select or create a Cloud project.  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. Go to the project selector page  Make sure that billing is enabled for your Google Cloud project. Learn how to confirm billing is enabled for your project.  Enable the Google Compute Engine and Cloud Source Repositories APIs. Enable the APIs  Install and initialize the Cloud SDK. If you can't install Cloud SDK because you are using an unsupported device or platform, such as Chromebook, see Starting Cloud Datalab on a Chromebook. Steps to set up and open Cloud Datalab From a terminal window on your local machine:  Update your gcloud command-line tool components:  gcloud components update  If you installed the gcloud command-line tool through apt or yum, use those package managers to update the components: sudo apt update && sudo apt upgrade google-cloud-sdk  sudo yum upgrade google-cloud-sdk  Install the datalab component for the gcloud command-line tool:  gcloud components install datalab  If you installed the gcloud command-line tool through apt or yum, use those package managers to update the components: sudo apt update && sudo apt install google-cloud-sdk-datalab  sudo yum install google-cloud-sdk-datalab  Create a Cloud Datalab instance. The name of the instance must start with a lowercase letter, followed by up to 62 lowercase letters, numbers, or hyphens, and cannot end with a hyphen.  datalab create datalab-instance-name  If the command returns an error, re-run the command with the following debug flag to help diagnose the problem: datalab create --verbosity=debug datalab-instance-name. To create a Cloud Datalab instance with GPUs. To create a Cloud Datalab VM with one K80 GPU (see GPU Pricing), use the following beta command: datalab beta create-gpu datalab-instance-name  To specify more than one K80 GPU, use the --accelerator-count number flag. For more information, run: datalab beta create-gpu --help  Open the Cloud Datalab home page in your browser.  http://localhost:8081   The connection to your Datalab instance remains open while the datalab command is active. If the terminal command window is closed or interrupted, the connection will terminate, and you will need to run the following command to reestablish the connection:  datalab connect instance-name  Clean up To avoid incurring charges to your Google Cloud account for the resources used in this quickstart, follow these steps.  You incur charges from the time of creation to the time of deletion of the Cloud Datalab VM instance (see Cloud Datalab Pricing). You are also charged for the Persistent Disk where notebooks are stored. The Persistent Disk remains after the deletion of the VM until you delete it. The following command deletes both the VM instance and its Persistent Disk. datalab delete --delete-disk instance-name  Other cleanup tasks. Additional resources are created by the datalab create command, and will be reused by other Cloud Datalab instances that you create. You can run the following commands to delete the additional resources listed below if you do not expect to create additional Cloud Datalab instances.