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CLI (v2) environment YAML schema

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APPLIES TO: Azure CLI ml extension v2 (current)

The source JSON schema can be found at https://azuremlschemas.azureedge.net/latest/environment.schema.json.

Note

The YAML syntax detailed in this document is based on the JSON schema for the latest version of the ML CLI v2 extension. This syntax is guaranteed only to work with the latest version of the ML CLI v2 extension. You can find the schemas for older extension versions at https://azuremlschemasprod.azureedge.net/.

YAML syntax

Key Type Description Allowed values Default value
$schema string The YAML schema. If you use the Azure Machine Learning VS Code extension to author the YAML file, including $schema at the top of your file enables you to invoke schema and resource completions.
name string Required. Name of the environment.
version string Version of the environment. If omitted, Azure Machine Learning will autogenerate a version.
description string Description of the environment.
tags object Dictionary of tags for the environment.
image string The Docker image to use for the environment. One of image or build is required.
conda_file string or object The standard conda YAML configuration file of the dependencies for a conda environment. See https://conda.io/projects/conda/en/latest/user-guide/tasks/manage-environments.html#creating-an-environment-file-manually.

If specified, image must be specified as well. Azure Machine Learning will build the conda environment on top of the Docker image provided.
build object The Docker build context configuration to use for the environment. One of image or build is required.
build.path string Local path to the directory to use as the build context.
build.dockerfile_path string Relative path to the Dockerfile within the build context. Dockerfile
os_type string The type of operating system. linux, windows linux
inference_config object Inference container configurations. Only applicable if the environment is used to build a serving container for online deployments. See Attributes of the inference_config key.

Attributes of the inference_config key

Key Type Description
liveness_route object The liveness route for the serving container.
liveness_route.path string The path to route liveness requests to.
liveness_route.port integer The port to route liveness requests to.
readiness_route object The readiness route for the serving container.
readiness_route.path string The path to route readiness requests to.
readiness_route.port integer The port to route readiness requests to.
scoring_route object The scoring route for the serving container.
scoring_route.path string The path to route scoring requests to.
scoring_route.port integer The port to route scoring requests to.

Remarks

The az ml environment command can be used for managing Azure Machine Learning environments.

Examples

Examples are available in the examples GitHub repository. Several are shown below.

YAML: local Docker build context

$schema: https://azuremlschemas.azureedge.net/latest/environment.schema.json
name: docker-context-example
build:
  path: docker-contexts/python-and-pip

YAML: Docker image

$schema: https://azuremlschemas.azureedge.net/latest/environment.schema.json
name: docker-image-example
image: pytorch/pytorch:latest
description: Environment created from a Docker image.

YAML: Docker image plus conda file

$schema: https://azuremlschemas.azureedge.net/latest/environment.schema.json
name: docker-image-plus-conda-example
image: mcr.microsoft.com/azureml/openmpi4.1.0-ubuntu20.04
conda_file: conda-yamls/pydata.yml
description: Environment created from a Docker image plus Conda environment.

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