Docker Deployer

Deploying your pipelines locally with Docker.

The Docker deployer is a deployer flavor that comes built-in with ZenML and deploys your pipelines locally using Docker.

When to use it

You should use the Docker deployer if:

• you need a quick and easy way to deploy your pipelines locally.

• you want to debug issues that happen when deploying your pipeline in Docker containers without waiting and paying for remote infrastructure.

• you need an easy way to test out how pipeline deployments work

How to deploy it

To use the Docker deployer, you only need to have Docker installed and running.

How to use it

To use the Docker deployer, you can register it and use it in your active stack:

zenml deployer register docker --flavor=docker

# Register and activate a stack with the new deployer
zenml stack register docker-deployer -D docker -o default -a default --set

ZenML will build a local Docker image called zenml:<PIPELINE_NAME> and use it to deploy your pipeline as a Docker container. Check out this page if you want to learn more about how ZenML builds these images and how you can customize them.

You can now deploy any ZenML pipeline using the Docker deployer:

zenml pipeline deploy my_module.my_pipeline

Additional configuration

For additional configuration of the Docker deployer, you can pass the following DockerDeployerSettings attributes defined in the zenml.deployers.docker.docker_deployer module when configuring the deployer or defining or deploying your pipeline:

• Basic settings common to all Deployers:

  • auth_key: A user-defined authentication key to use to authenticate with deployment API calls.

  • generate_auth_key: Whether to generate and use a random authentication key instead of the user-defined one.

  • lcm_timeout: The maximum time in seconds to wait for the deployment lifecycle management to complete.

• Docker-specific settings:

  • port: The port to expose the deployment on.

  • allocate_port_if_busy: If True, allocate a free port if the configured port is busy.

  • port_range: The range of ports to search for a free port.

  • run_args: Arguments to pass to the docker run call. A full list of what can be passed in via the run_args can be found in the Docker Python SDK documentation.

Check out this docs page for more information on how to specify settings.

For example, if you wanted to specify the port to use for the deployment, you would configure settings as follows:

from zenml import step, pipeline
from zenml.deployers.docker.docker_deployer import DockerDeployerSettings


@step
def greet(name: str) -> str:
    return f"Hello {name}!"


settings = {
    "deployer": DockerDeployerSettings(
        port=8000
    )
}

@pipeline(settings=settings)
def greet_pipeline(name: str = "John"):
    greet(name=name)