Emily CLI Documentation
Release-v3.0.4Emily combines the powers of Python and Docker to build stable and consistent machine learning and datascience python environments. Emily is useful for large cross-team project development as well as for simply running a single jupyter notebook or python script.
Downloademily@v3.0.4See earlier versions
$ emily deployment add kubernetes [options]Add a deployment specification targeting a Kubernetes cluster.
$ deployment add kubernetesChoose a project| AB82JD - movie-recommender>> Please enter a deployment name: >> Please select a configuration| + Add new configuration>> Please select an environment| + Add new environment>> Please enter your Docker Hub username: >> Kubernetes deployment "production" added to project my-project (M9VHKD)
Created:
- <project root>/deployments/production/deployment.json
Adding Kubernetes Deployment Specifications
A deployment specification of type kubernetes specifies the deployment of a project to a Kubernetes cluster.
Emily supports deployments to any Kubernetes cluster, with explicit support for Azure Kubernetes Service clusters.
Deploying using Docker Hub
When deploying to a Kubernetes cluster, the project image is hosted on an image repository. By default, this is a Docker Hub repository.
When creating the Kubernetes configuration with emily configuration add kubernetes, the user specifies the repository from which to pull images for the service.
The --docker-user flag specifies the user to use when logging into Docker Hub to pull the image.
If using a private Docker Hub repo, the --email must also be provided (this should be the email for the specified Docker user).
Deploying using Azure Kubernetes Service
When deploying to an Azure Kubernetes cluster, pass the --azure flag.
When this flag is provided, the --acr-name must also be provided. This is the name of the Azure Container Registry to pull images from.
Usually, if your images are pulled from myregistry.azurecr.io/images/my-image, the --acr-name would be myregistry.azurecr.io.