Docker
Learn Enough Docker to be Useful
Part 1: The Conceptual Landscape
Docker is a platform to develop, deploy, and run applications inside containers.
Docker containers are superior to virtual machines because they take fewer resources, are very portable, and are faster to spin up.
Docker Containers
Holds things: There are things both inside and outside of a container
Is portable: Cam be used your local machine, coworker's machine or on the cloud
Has clear interfaces for access: Configure to interact through the command line
Can be obtained from a remote location: Registry keeps an image which can create containers on demand
Docker container is a Docker image brought to life
Superior to virtual machines because containers take fewer resources, are very portable, and are faster to spin up
Docker Image
An image contains the Dockerfile, libraries, and code your application needs to run, all bundled together
docker run image_name
creates and starts a container from an image
Dockerfile
A recipe file with instructions for how Docker should build your image
Base image layer: Used to build the initial image layer
Example: ubuntu, node
Additional layers can then be stacked on top of the base image layers
Example: Libraries such as alfresco-content-repository, es6-angular-webpack
Thin writable layer
Container Registry
Share your image with others
Docker Hub is the largest registry
Part 2: A Delicious Dozen Docker Terms You Need to Know
https://towardsdatascience.com/learn-enough-docker-to-be-useful-1c40ea269fa8
Part 3: A Dozen Dandy Docker file Instructions
https://towardsdatascience.com/learn-enough-docker-to-be-useful-b0b44222eef5
Part 4: Slimming Down Your Docker Images
https://towardsdatascience.com/slimming-down-your-docker-images-275f0ca9337e
Part 5:15 Docker Commands You Should Know
https://towardsdatascience.com/15-docker-commands-you-should-know-970ea5203421
Part 6: Pump up the Volumes: Data in Docker
https://towardsdatascience.com/pump-up-the-volumes-data-in-docker-a21950a8cd8
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