This document summarizes Dockerizing a Django application. It describes the speakers' experiences moving from a non-Dockerized setup with many issues, like outdated images and long recovery times, to a Dockerized setup with improved scalability, documentation, and development workflows. Key aspects of the new setup include using Docker Compose to run multiple services, Docker Machine to provision environments, and Docker Swarm for production deployments across multiple instances.
2. Who are we?
Michael Dougherty
@maackle
Senior Front-end Engineer
CrowdStreet, Inc.
Hannes Hapke
@hanneshapke
Software Engineer
Talentpair, Inc.
3. Our pre-Docker World …
• Single instance world
(e.g. celery ran on the web
server)
• Outdated Amazon machine
image
• No documentation about the
setup, consultancy work
• Live data monkey patching
• Scaling/Recovery time > 8 hours
• Clunky QA setup > bottleneck
4. Our post-Docker World …
• Single instance world
(e.g. celery ran on the web
server)
• Outdated Amazon machine
image
• No documentation about the
setup, consultancy work
• Live data monkey patching
• Scaling/Recovery time > 8 hours
• Clunky QA setup > bottleneck
• One service per container,
redundancy of instances
• One common base image shared
across all instances
• Explicit, declarative server setup
• Immutable infrastructure (mostly)
• Scaling/Recovery time ~ 20min
• As many QA instances as we
want
6. Docker containers …
… wrap a piece of software in a complete filesystem that
contains everything needed to run: code, runtime, system
tools, system libraries – anything that can be installed on a
server. This guarantees that the software will always run
the same, regardless of its environment. *
Basically a virtual env for your operating system.
* from https://www.docker.com/what-docker
10. • Create a Dockerfile
• Build the Docker image and push it to the docker registry
Plain Docker
FROM ubuntu:16.04
RUN apt-get update && apt-get upgrade -y
RUN pip install Django
COPY requirements.txt .
WORKDIR /dev
$ docker build -t your_project/your-whale .
$ docker images
$ docker tag {image_hash} your_project/your-whale:latest
$ docker push
11. Plain Docker
• Run a shell in a docker container
-i start an interactive container
-t creates “Pseudo interface” with stdin and stdout
• Run the Django server in a container
-d run container in detached mode
-P maps all ports to the host machine
$ docker run -i -t ubuntu /bin/bash
$ docker run -d -P my-container python manage.py run server
12. What if we need
multiple services?
Docker • Compose • Machine • Swarm
13. Docker Compose
Compose is a tool for orchestrating the building,
running, and intercommunication of
multi-container Docker applications.
14. How does it work?
1) Define a Dockerfile for every service
2) Define a Docker compose description of the environment
3) Use docker-compose build/up to start all services
version: '2'
services:
web:
build: .
ports:
- "5000:5000"
volumes:
- .:/code
redis:
image: redis
15. How can I easily
provision a server with
the containers?
Docker • Compose • Machine • Swarm
16. Docker Machine
… is a great tool which creates Docker hosts anywhere.
Yes, anywhere.
Locally, AWS EC2, Digital Ocean, MS Azure, you name it.
No Ansible, Puppet, Chef, fabric, etc. required.
17. What if I need multiple
instances with multiple
services?
Docker • Compose • Machine • Swarm
20. If you start from scratch …
• Docker documentation includes a great Django
setup
• Too much work? The Django Cookie Cutter
template includes a great Docker setup
Other projects:
• django-docker on github
23. Normalize folders
• Create folders for every service
• docker-compose-{env}.yml go into the project root
• Dockerfiles go into every service folder
• startup.sh scripts go into the service folders
• Keep your local folder structure similar to the folder
structure within the container(s) - for sanity
26. Base Image
• Create one (or more) base Dockerfile(s) with all
common packages
• Service containers can use this base image - this
will increase build speed
• If you store the base image(s) in a separate git
repo, the docker registry will build them
automatically for you
27. Base Image
FROM ubuntu:16.04
RUN apt-get update && apt-get upgrade -y
RUN apt-get install -y vim # Install some useful editor
RUN apt-get install -y build-essential git software-properties-common
RUN apt-get install -y python python-dev
python-setuptools build-essential
RUN apt-get install -y nodejs npm
RUN npm install -g n # upgrading the npm version
RUN n stable
...
29. Set up Docker compose
for the different
environments
30. Docker Compose
• For every environment, local, QA, staging,
production, define a docker-compose-{env}.yml file
• The files describe the environment stack
• Each service within the docker-compose file can
have it’s own Dockerfile
33. Docker Compose
• Build your service stack with
• Start the container stack with
• Access a single container with
$ docker-compose -f docker-compose-{env}.yml build
$ docker-compose -f docker-compose-{env}.yml up
$ docker-compose -f docker-compose-{env}.yml run django bash
$ docker-compose -f docker-compose-{env}.yml
run container name command
38. Docker Machine
• With
will provision you an AWS instance
• “Activate” the instance with
• Afterwards, any docker-compose command will be
executed on the active machine
• Easy to start/stop/terminate machines
$ docker-machine create --driver amazonec2
--amazonec2-region [e.g. us-west-2]
--amazonec2-vpc-id [YOUR_VPC_ID vpc-xxxxxx]
--amazonec2-instance-type [e.g. t2.small]
[INSTANCE_NAME]
$ docker-machine env [INSTANCE_NAME]
41. Or... how to cowboy code
with Docker
• Sometimes you just need to manually change
something
• Docker provides ways to get a shell inside a
running instance and copy files back and forth
• Your changes will of course be lost next time you
spin up a new container
42. The Disciplined Way:
The Cowboy Way:
$ docker-compose run django bash
$ docker exec -it {container_id} bash
43. How does QA work with
Docker?
• No QA bottleneck anymore
• No database gridlock anymore
• Each feature branch gets its own instance
• Once feature is tested, instance gets terminated
44. How can I access the
manage.py shell/migrate?
• Access the bash of the django container with
• Continue as usual with
Some for migrations, make_migrations, etc.
• Or run it from outside of the container stack with
$ docker-compose -f docker-compose-{env}.yml run django bash
# ./manage.py shell
docker-compose -f … run django python manage.py migrate
45. Help, ipdb doesn’t work
anymore …
• Start the Django container with the service ports
enabled
• If no command is specified, then Docker will default
to the command in the docker-compose.yml file
$ docker-compose -f dev.yml run --service-ports django
46. How to run tests?
• Start the Django container with your test command
$ docker-compose -f … run django manage.py test
47. CI Testing is convenient
• Setup for Circle CI
machine:
pre:
- curl -sSL https://s3.amazonaws.com/circle-downloads/install-circleci-docker.sh
| bash -s -- 1.10.0
services:
- docker
dependencies:
override:
- sudo pip install docker-compose
- docker login -e $DOCKER_EMAIL -u $DOCKER_USER -p $DOCKER_PASS
- docker-compose -f docker-compose-circle.yml build
- npm install -g jshint
test:
pre:
- sudo killall postgres # not sure why, but port 5432 is already taken up sometimes!
- docker-compose -f docker-compose-circle.yml up -d postgres
override:
- jshint ~/your_project/django/static/js/your_project*
- docker-compose -f docker-compose-circle.yml run django
/your_project/manage.py test --verbosity=2
48. WTF, the files I copied into
my container are missing??
• If a volume is mounted at the same directory
where you copied other files, you will essentially
overwrite those files
49. Sharing Docker Machine
credentials
• Docker machine is great, but there is no concept
of sharing credentials
• All credentials are simple text files, no magic
• npm tool `machine-share` solved the problem
• Let’s you export and import machine credentials
50. General Troubleshooting
• Confirm that the correct docker-machine environment is active
• Rebuild your container stack
• Rebuild with the --pull and/or --no-cache options
• Restart the docker daemon
• Restart your docker machine with docker-machine restart
[INSTANCE NAME]
• Restart your docker machine VirtualBox VM
• Remove and recreate your docker machine (essentially recreates
your dev environment from scratch)
52. Dev Environment
• You can use the same image as in your production
builds
• All services run at once, all output piped to a single
log stream (which we saw earlier)
• You can still have live reloading via Docker Volumes
(but be careful!)
53. How does the deployment
work now?
• Create AWS instance with docker-machine
• Activate the docker machine
• Use docker-compose to build the stack
• Use docker-compose up -d
• Switch the load balancer
54. Summary of technologies
• Learned about Docker
• How to use docker to define images and containers
• Learned about Docker-compose to define
relationships between containers
• Learned about Docker-machine to seamlessly work
with containers on local/remote machines
55. Summary of benefits
• Explicit, declarative server setup
• Zero down time deployments
• All dev services in one "window" and start with one
command
• Easy provisioning of multiple QA instances
• Quick onboarding for new devs