Deis Workflow Controller (API)
Python Other
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Deis Controller

Build Status Docker Repository on Quay Dependency Status

Deis (pronounced DAY-iss) Workflow is an open source Platform as a Service (PaaS) that adds a developer-friendly layer to any Kubernetes cluster, making it easy to deploy and manage applications on your own servers.

For more information about the Deis Workflow, please visit the main project page at

We welcome your input! If you have feedback, please submit an issue. If you'd like to participate in development, please read the "Development" section below and submit a pull request.


The Controller is the central API server for Deis Workflow. It is installed on a Kubernetes cluster, making it easy to deploy and manage applications on your own cluster. Below is a non-exhaustive list of things it can do:

  • Create a new application
  • Delete an application
  • Scale an application
  • Configure an application
  • Create a new user


The Deis project welcomes contributions from all developers. The high level process for development matches many other open source projects. See below for an outline.

  • Fork this repository
  • Make your changes
  • Submit a pull request (PR) to this repository with your changes, and unit tests whenever possible.
    • If your PR fixes any issues, make sure you write Fixes #1234 in your PR description (where #1234 is the number of the issue you're closing)
  • The Deis core contributors will review your code. After each of them sign off on your code, they'll label your PR with LGTM1 and LGTM2 (respectively). Once that happens, the contributors will merge it



In order to do development on this component, you'll need a working Kubernetes cluster. If you don't have one, follow the installation instructions and note that Controller currently targets version 1.2 and higher.

Workflow Installation

After you have a working Kubernetes cluster, you're ready to install Workflow.


The application and tests use PostgreSQL. To start a local instance via Docker, run make postgres and set the following in your shell:

  export PGHOST=`docker-machine ip $(docker-machine active) 2>/dev/null || echo`
  export PGPORT=5432
  export PGUSER=postgres


Python 3.5 is a minimum requirement and can be installed via pyenv:

brew install pyenv
pyenv install 3.5.0
# if you have build issues, ensure Xcode CLI tools are installed:
python local 3.5.0 # use Python 3.5.0 in your current directory

Or via your package manager. For example, on Debian Jessie:

apt-get install python3 python3-dev python3-venv

With the correct Python in place the quickest way to get up and running is to run make setup-venv which will install the Python specific dependencies via PIP inside an isolated virtualenv. Running python --version to verify the correct version is recommend.

Follow the linked documentation to learn about virtualenv and how to activate and deactivate the environment.

Testing Your Code

When you've built your new feature or fixed a bug, make sure you've added appropriate unit tests and run make test to ensure your code works properly.

Also, since this component is central to the platform, it's recommended that you manually test and verify that your feature or fix works as expected. To do so, ensure the following environment variables are set:

  • DEIS_REGISTRY - A Docker registry that you have push access to and your Kubernetes cluster can pull from
    • If this is Docker Hub, leave this variable empty
    • Otherwise, ensure it has a trailing /. For example, if you're using, use
  • IMAGE_PREFIX - The organization in the Docker repository. This defaults to deis, but if you don't have access to that organization, set this to one you have push access to.
  • SHORT_NAME (optional) - The name of the image. This defaults to controller
  • VERSION (optional) - The tag of the Docker image. This defaults to the current Git SHA (the output of git rev-parse --short HEAD)

Then, run make deploy to build and push a new Docker image with your changes and replace the existing one with your new one in the Kubernetes cluster. See below for an example with appropriate environment variables.

export IMAGE_PREFIX=arschles
make deploy

After the make deploy finishes, a new pod will be launched but may not be running. You'll need to wait until the pod is listed as Running and the value in its Ready column is 1/1. Use the following command watch the pod's status:

kubectl get pod --namespace=deis -w | grep deis-controller


Copyright 2013, 2014, 2015, 2016 Engine Yard, Inc.

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.