This is the Docker & Kubernetes config that accompanies my blog post Deploying ML workloads with Azure and Kubernetes.
You should first create the docker container image and test locally..
cd docker docker build -t gretkowski/kubeevo:v1 -f Dockerfile .
make sure everything is good w/ the container image, then push it to your private image registry.
You then use the rest of the YAML files - modified to suit your environment - to deploy the master and worker containers to your Kubernetes cluster