Kubernetes in Google Cloud
Advanced 5 个步骤 5 个小时 25 个积分
Kubernetes is the most popular container orchestration system, and Google Kubernetes Engine was designed specifically to support managed Kubernetes deployments in Google Cloud. In this advanced-level quest, you will get hands-on practice configuring Docker images, containers, and deploying fully-fledged Kubernetes Engine applications. This quest will teach you the practical skills needed for integrating container orchestration into your own workflow. Looking for a hands-on challenge lab to demonstrate your skills and validate your knowledge? On completing this quest, finish the additional Challenge Lab at the end of the Deploy to Kubernetes in Google Cloud Quest to receive an exclusive Google Cloud digital badge.
预备知识：It is recommended that students have earned a Badge by completing the hands-on labs in the Google Cloud Essentials Quest before attempting these labs.
In this lab you will familiarize yourself with the basic Docker container environment commands. You will create, run, and debug containers, and learn to pull and push images to and from Google Container Registry.
Google Kubernetes Engine provides a managed environment for deploying, managing, and scaling your containerized applications using Google infrastructure. This hands-on lab shows you how deploy a containerized application with Kubernetes Engine. Watch the short video Manage Containerized Apps with Kubernetes Engine.
In this lab you will learn how to: Provision a complete Kubernetes cluster using Google Container Engine; Deploy and manage Docker containers using kubectl; and Break an application into microservices using Kubernetes’ Deployments and Services.
Dev Ops best practices make use of multiple deployments to manage application deployment scenarios. This lab provides practice in scaling and managing containers to accomplish common scenarios where multiple heterogeneous deployments are used.
In this lab you will deploy and completely configure a continuous delivery pipeline using Jenkins running on Kubernetes Engine and go through the dev - deploy process.