Ryan Walls

@ryanwalls

Director of Software Engineering

3DSIM

101

0 to Real world use

Before we begin:

Download Docker for your OS

Wifi password: lucidguessed

So... Docker. What do you want to know?

What are solaris zones?

Agnostic build environment? Less setup.

Best practices on Dockerfiles?

Docker networking

Docker in AWS

Setup of a Safe environment

Questions

Don't be shy

What is Docker?

https://docs.docker.com

Details of Docker

Basics of Docker

Container

Image

Engine

Hub

Uses open source container framework

https://github.com/containerd/containerd

containerd is an industry-standard container runtime with an emphasis on simplicity, robustness and portability. It is available as a daemon for Linux and Windows, which can manage the complete container lifecycle of its host system

Docker container

Large

Small

Consume significant CPU and memory

Basically zero memory and CPU overhead

Not easily portable between VM environments

Run in any linux environment

Hardware centric

Application centric

Lightweight

"...You may be able to run six to eight times as many containers as VMs on the same hardware."

http://www.infoworld.com/article/3072929/linux/containers-101-linux-containers-and-docker-explained.html

An image is the source of a docker container.

Imperfect analogy:

MyClass.java -> MyClass.class -> running instance of MyClass running in JVM

Dockerfile -> docker image -> running docker container in docker enginer

Manages containers

Start/Stop

Status

Linking

Networking

Storage

Client-server application with these major components:

A server
A REST API
A command line interface (CLI) client

https://hub.docker.com/explore

Store and browse ready-made docker images

Typical workflow for docker

Dockerize your code and dependencies
- Write a Dockerfile that specifies the execution environment and pulls in your code.
- If your app depends on external applications (such as Redis, or MySQL), run them in Docker as well (usually using a premade image available on Docker Hub)
- Build, then run your containers as you develop.

Typical workflow for docker

Configure networking and storage for your solution, if needed.
Upload builds to a registry (docker's, yours, or your cloud provider’s), to collaborate with your team.
If you’re gonna need to scale your solution across multiple hosts (VMs or physical machines), plan for how you’ll set up your cluster and scale it to meet demand.

Typical workflow for docker

Finally, deploy to your preferred cloud provider (or, for redundancy, multiple cloud providers.)

Tonight

Dockerize your code and dependencies
Setup a build pipeline for the container
Upload builds to a registry (docker's, yours, or your cloud provider’s), to collaborate with your team.
(Future meetup) If you’re gonna need to scale your solution across multiple hosts (VMs or physical machines), plan for how you’ll set up your cluster and scale it to meet demand.
(Future meetup) Finally, deploy to your preferred cloud provider (or, for redundancy, multiple cloud providers.)
Hands on labs

Let's demo a little Docker first

Why Docker?

Let's see what it can do... then let's talk

I want to try it out. How do I run Docker locally?

https://docs.docker.com/docker-for-mac

https://docs.docker.com/docker-for-windows

https://docs.docker.com/engine/installation/linux

Instant CI server

docker run -i -t -d --name neo4j --cap-add=SYS_RESOURCE \
-p 7474:7474 tpires/neo4j

Try out neo4j

docker run --name myjenkins -p 8080:8080 -v /var/jenkins_home jenkins

Play around with nginx

docker run -p 7070:80 -v \
/path/to/some/sample-static-html:/usr/share/nginx/html:ro -d nginx

How about mongo?

docker run --name my-mongo -d mongo

A developer's playground

Useful commands

https://github.com/wsargent/docker-cheat-sheet

How do I dockerize my app?

Manually create

You can create a docker image by just running commands against a base image.

docker pull learn/tutorial
docker run learn/tutorial apt-get install -y ping
docker ps -l
docker commit <id from previous step> learn/ping
docker run learn/ping ping google.com

Dockerfile

Instead of running commands and saving, can create a Dockerfile that specifies all the commands to build an image.

https://docs.docker.com/engine/reference/builder

FROM maven:3.3-jdk-8-onbuild-alpine

RUN mvn test

EXPOSE 8080

CMD ["java", "-jar", "target/docker-for-java-developers-0.1.0.jar"]

Dockerfile

Build the Dockerfile into an image and tag the image

docker build -t="myname/mytomcatapp:v1" .

Create a container by running the image

docker run -t -i myname/mytomcatapp:v1

Demo Catweb

https://github.com/ryanwalls/docker101

What about a real development pipeline?

Zero to Dockerized Image

Fork/clone code
Make changes, write tests
Make sure container builds
Submit PR
Review/approve PR and merge
Container build is kicked off automatically
Once container built, deploy to QA
One button push to production

Step 1: CI/CD

"Without continuous integration, we are nothing."

-- Anonymous

See https://github.com/ryanwalls/docker-for-java-developers

Demo full life cycle at 3dsim

What's next for my company?

Zero to Docker

Use docker for prototyping on local machines
Run your CI/CD environment in Docker
Get some small applications into containers
Deploy containers instead of binaries in dev, integration, prod environments
Orchestrate deploying those containers with a fancy tool (swarm, fleet, kubernetes, rancher, etc) to a cluster of servers
Rinse...Repeat

Back to... why Docker?

(They will ask.)

Why Docker in Development?

Fast prototyping
Can easily create standalone multi-app dev environments (see Docker Compose)
Use same stack as production
Easily spin up machines to test large complex environments (see Docker Machine)

Why Docker in Production?

Improved quality/stability/consistency. Configuration of app stack is versioned and committed. Ideally even immutable.
Less work for techops. Just provision bare linux machine
Faster. Setting up applications in new server is as simple as "docker run"
Reduce costs. Apps run in their own container, so each server could have many apps running in nearly complete isolation.
Fast deployments. Docker uses diff file system for images. Any layers already run are cached.