Docker has taken DevOps by storm and ignited interest in containers. Containers offer many of the benefits of virtual machines but in a much more efficient, less resource-intensive system. Containers allow you to package up an application in an isolated environment that can be executed across machines in a reproducible manner. No more "well, it worked on my machine" syndrome when you leverage Docker for your application development and deployment.

In this Lab, you will get up and running with Docker on Linux using an AWS virtual machine. You will work with images from the public Docker registry, run a handful of containers, and create your own image from which to create containers. 

Lab Objectives

Upon completion of this Lab you will be able to:

• Install Docker on Linux using an AWS virtual machine
• Add a user to the Docker group
• Find and use images from the public Docker Registry
• Build your own images using Dockerfiles

Lab Prerequisites

You should be familiar with:

• What containers are
• Working at the command line in Linux

Lab Environment

Before completing the Lab instructions the environment will look as follows:

After completing the Lab instructions the environment should look similar to:

Updates

April 5th, 2023 - Resolved an issue that caused the Lab to fail to set up on rare occasions

February 22nd, 2022 - Updated requirements file

December 14th, 2021 - Updated Dockerfile to shorten the path to the source file

April 16th, 2021 - Moved validation checks to the most relevant Lab step for more immediate validation feedback

January 5th, 2021 - Updated code snippets

July 9th, 2020 - Migrated to EC2 Instance Connect

July 3rd, 2019 - Added an additional custom validation Lab step to check the work performed in the lab

June 27th, 2019 - Added a custom validation Lab step to check the work performed in the lab

January 10th, 2019 - Added a validation Lab Step to check the work you perform in the Lab