indekrutox.blogg.se - Monolith war lab code

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 you can remotely operate Google Cloud and GKE with your laptop, you will use Cloud Shell-a command-line environment running in the Cloud-for the codelab. However, the codelab could cost you more money if you use more resources or leave them running (see "clean up" section at the end).

If you're not a new user, then don't worry because the codelab shouldn't cost you more than a few dollars. New users of Google Cloud are eligible for a $300 free trial.

Next, you'll need to enable billing in the Cloud Console to use Google Cloud resources. It will be referred to as PROJECT_ID later. Remember, the project ID is a unique name across all Google Cloud projects (the name above has already been taken and will not work for you, sorry!). Sign into Google Cloud Console and create a new project. If you don't already have a Google Account, then you must create one.

A basic understanding of Docker and Kubernetes (If you lack a basic understanding, then please review Docker and Kubernetes now.).

A Google Account with administrative access to create projects or a project with a project-owner role.

How to perform a rolling update on Kubernetes.

How to scale an application on Kubernetes.

How to deploy Docker images to Kubernetes.

Roll out a new version with zero downtime.

Scale the container to multiple replicas.

The exercises are ordered to reflect a common cloud developer's experience:

Due to problems with scaling and outages, you're tasked with deploying your application to GKE! Imagine a tool that could help you do all that and even allow you to automate it! With GKE, all of that is not only possible, it's easy! In this codelab, you assume the role of a developer running an ecommerce website for a fictional company-Fancy Store. Things go wrong when they shouldn't, servers crash, increase in demand causes more resources to be utilized, and making changes without downtime is complicated and stressful. Running websites and applications is hard.