The Docker Registry comes with a sample configuration file,
config_sample.yml
. Copy this to config.yml
to provide a basic
configuration:
cp config_sample.yml config.yml
Inside the config.yml
file we can see a selection of configuration
headings called flavors
: common
, dev
, prod
, etc.
You can specify what flavor to run with the SETTINGS_FLAVOR
environment variable.
$ export SETTINGS_FLAVOR=prod
The common
flavor overrides and is inherited by all other flavors. If
you don't specify a flavor when running the Docker Registry the dev
flavor will be used.
docker run samalba/docker-registry
NOTE: The container will try to allocate the port 5000 by default, if the port is already taken, find out which one has been taken by running "docker ps"
Install the system requirements for building a Python library:
sudo apt-get install build-essential python-dev libevent-dev python-pip
Then install the Registry app:
sudo pip install -r requirements.txt
sudo yum install python-devel libevent-devel python-pip
NOTE: On RHEL and CentOS you will need the EPEL repostitories enabled. Fedora should not require the additional repositories.
Then install the Registry app:
sudo python-pip install -r requirements.txt
gunicorn --access-logfile - --debug -k gevent -b 0.0.0.0:5000 -w 1 wsgi:application
The recommended setting to run the Registry in a prod environment is gunicorn behind a nginx server which supports chunked transfer-encoding (nginx >= 1.3.9).
You could use for instance supervisord to spawn the Registry using this command:
gunicorn -k gevent --max-requests 100 --graceful-timeout 3600 -t 3600 -b localhost:5000 -w 8 wsgi:application
The nginx configuration will look like:
location / {
proxy_pass http://localhost:5000;
proxy_set_header X-Real-IP $remote_addr;
}
And you might want to add Basic auth on Nginx to protect it (if you're not using it on your local network):
NOTE: The central Registry runs on the dotCloud platform:
cd dotcloud-registry/
dotcloud create myregistry
dotcloud push
$ cd test
$ python -m unittest discover
The file workflow.py is bit special since it's a functional test (not a unit test). It requires a server to be running in order to succeed.
$ DOCKER_CREDS="user:password" python -m unittest workflow
DOCKER_CREDS contains user credentials information to connect to the staging index server.
If you want to submit a pull request, an important point is to clear up all flake8 warning you could introduce (ignore the one about registry/init.py).
$ pip install flake8
$ find . -name '*.py' -exec flake8 {} \;