Asset naming convention

General

These conventions apply to all assets, regardless of type. Names must:

Start with a letter.
Use only lowercase letters, numbers, dashes, and periods.
Be up to 255 characters long.
Use dashes to separate words.
Not include prefixes like "azureml" or "microsoft". Registries containing these assets will already provide this information.
Not include the type of asset as a suffix (examples: "component" or "environment"). The asset type is already clearly represented via CLI, SDK, and UI.
Not include a version number of the asset. Versions of included packages and frameworks are okay though.

Examples of valid asset names:

Name	Notes
tremendous-transform	Starts with a letter, uses lowercase letters and a dash
pytorch-1.9-cuda11.6-gpu	Version numbers refer to PyTorch and CUDA, not the asset itself

Examples of invalid asset names:

Name	Issue
microsoft_master_transform	Uses underscores instead of dashes
awesome-component	Ends with "component"
fastsupertransform	Should use dashes to separate words, but doesn't
1-amazing-sort	Doesn't start with a letter
pattern-detect-2.0	Asset version should be in its version, not its name

If you have a lot of related components, consider using a prefix to help group them. For example: forecast-preprocessing, forecast-threat-model, etc.

Your environment will need a meaningful name that will make it easy to find. Follow the naming convention below for framework-based environments:

<framework>-<framework-version>[-<os><os-version>][-py<python-version>][{-<gpu-driver><gpu-driver-version>|-gpu}][-inference]

Field	Description	Examples
`framework`	Machine learning framework supported by the environment	pytorch, sklearn, tensorflow
`framework-version`	Framework version, major and minor values only	1.1, 11.1, 2.8
`os`	Operating system, specified only when not Ubuntu.	centos, debian, win
`os-version`	Operating system version	9, 11, 2022
`python-version`	Python version, major and minor values only, no period. Use only when absolutely required.	38 (for Python 3.8)
`gpu-driver`	GPU driver	cuda
`gpu-driver-version`	GPU driver version, major and minor values only	11.6

Environments are assumed to be based on Ubuntu unless -os<os-version> is included
For a GPU environment, use either -<gpu-driver><gpu-driver-version> or -gpu, not both
- -gpu is only used when the GPU driver name and version aren't important
Environments without a GPU driver or -gpu suffix are CPU-only
Environments with an -inference suffix provide inferencing support
In general, use fewer fields in the name to minimize maintenance costs. Otherwise, you'll spend time deprecating environments that are locked to a specific OS or Python version that have reached end-of-life, or other situations where a required update would invalidate the environment's name.
If your environment isn't focused on a particular framework, choose a simple name and use the fields above as needed. Consider using a project-specific prefix to group multiple environments.

To keep them easy to maintain, Docker image names should match the name of their associated environment.

Examples:

Environment Name	Docker Image Name
pytorch-1.9	azureml/curated/pytorch-1.9
pytorch-1.9-cuda11.6	azureml/curated/pytorch-1.9-cuda11.6