Note: if you've omitted to specify a default zone in the setup steps, the command will respond suggesting a zone for you. Note down the EXTERNAL_IP - that's important later on. Let's first create an instance with default settings : $ gcloud compute instances create myinstance Everything done here can be achieved using the console (available at ). But in Cloud Shell, you will need to set this for every new session or reconnection.Īs discussed previously we will use the gcloud command- line in this codelab. Note: When you run gcloud on your own machine, the config settings would've been persisted across sessions. For more information, see Regions & Zones. You can choose a variety of different zones. Gcloud config set compute/zone us-central1-f Finally, set the default zone and project configuration.Looking for your PROJECT_ID? Check out what ID you used in the setup steps or look it up in the Cloud Console dashboard:Ĭloud Shell also sets some environment variables by default, which may be useful as you run future commands. If, for some reason, the project is not set, simply issue the following command: gcloud config set project For more information, see gcloud command-line tool overview. Note: The gcloud command-line tool comes preinstalled in Cloud Shell and you'll surely enjoy its support for tab completion. Once connected to Cloud Shell, you should see that you are already authenticated and that the project is already set to your PROJECT_ID. To activate Cloud Shell from the Cloud Console, simply click Activate Cloud Shell (it should only take a few moments to provision and connect to the environment).This means that all you will need for this codelab is a browser (yes, it works on a Chromebook). It offers a persistent 5GB home directory and runs in Google Cloud, greatly enhancing network performance and authentication. This Debian-based virtual machine is loaded with all the development tools you'll need. While Google Cloud and Compute Engine can be operated remotely from your laptop, in this codelab we will be using Google Cloud Shell, a command line environment running in the Cloud. New users of Google Cloud are eligible for the $300 USD Free Trial program. To shut down resources so you don't incur billing beyond this tutorial, follow any "clean-up" instructions found at the end of the codelab. Running through this codelab shouldn't cost much, if anything at all. Next, you'll need to enable billing in the Cloud Console in order to use Cloud resources/APIs.If you're using a Google Workspace account, then choose a location that makes sense for your organization. Note: If you're using a Gmail account, you can leave the default location set to No organization. If a project is deleted, that ID can never be used again. Learn more about all three of these values in the documentation.Ĭaution: A project ID must be globally unique and cannot be used by anyone else after you've selected it. There is a third value, a Project Number which some APIs use. Then it's "frozen" after the project is created. In most codelabs, you'll need to reference the Project ID (and it is typically identified as PROJECT_ID), so if you don't like it, generate another random one, or, you can try your own and see if it's available. The Cloud Console auto-generates a unique string usually you don't care what it is. The Project ID must be unique across all Google Cloud projects and is immutable (cannot be changed after it has been set).It is a character string not used by Google APIs, and you can update it at any time. The Project name is the display name for this project's participants.If you don't already have a Gmail or Google Workspace account, you must create one. Sign-in to the Google Cloud Console and create a new project or reuse an existing one.The machines are available in many configurations including predefined sizes and can also be created with Custom Machine Types optimized for your specific needs.įinally, Compute Engine virtual machines are also the technology used by several other Google Cloud products (Kubernetes Engine, Cloud Dataproc, Cloud Dataflow, etc.). These VMs boot quickly, come with persistent disk storage, and deliver consistent performance. The tooling and workflow offered enables scaling from single instances to global, load-balanced cloud computing. Google Compute Engine offers virtual machines running in Google's data centers connected to its worldwide fiber network. This lab will walk you through using the command-line. You can create a Compute Engine instance from either the graphical console or from the command line. You'll create Compute Engine instances, deploy nginx, and finally put a network load balancer in the front. In this codelab, we will explore Compute Engine working through an example Guestbook application. Hello everyone, thanks for coming today! Ready to learn Google Compute Engine?
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