Wget google app engine sdk for python how to#

This Debian-based virtual machine is loaded with all the development tools you'll need. While Google Kubernetes 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. Alternatively, from the console home page, click on 'Select a Project' : When presented with this console landing page, please select the only project available.

Here's what you should see once logged in: Accept the new account Terms of Service and any updates to Terms of Service. Use these credentials to log into the machine or to open a new Google Cloud Console window. Note that all these accounts will be disabled soon after the codelab is over.

These temporary accounts have existing projects that are set up with billing so that there are no costs associated for you with running this codelab. Otherwise ask one of the staff for a coupon with username/password. If you see a 'request account button' at the top of the main Codelabs window, click it to obtain a temporary account. It assumes you have basic familiarity with Docker containers and Kubernetes concepts.

Wget google app engine sdk for python how to#

This codelab shows you some of the advanced features of Google Kubernetes Engine, and will show you how to run a service which makes the most of Google Cloud Platform's features. It brings our latest innovations in developer productivity, resource efficiency, automated operations, and open source flexibility to accelerate your time to market. Kubernetes Engine, also known as GKE, is a managed environment for deploying containerized applications. The easiest way to run a Kubernetes cluster is using Google Kubernetes Engine, a managed version of Kubernetes hosted on Google Cloud Platform. Developed by Google and released as open-source, Kubernetes is now maintained by a diverse community and shepherded by the Cloud Native Computing Foundation.

Kubernetes is an open-source system for automating deployment, scaling, and management of containerized applications.