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. The current naming convention is:

<framework>-<framework-version>-<os><os-version>-py<python-version>-{cpu|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	ubuntu
`os-version`	Operating system version	20.04
`python-version`	Python version, major and minor values only, no period	38 (for Python 3.8)
`cpu\|gpu`	Whether the environment includes GPU support, or CPU only	cpu, gpu
`-inference`	Suffix to indicate whether the environment supports AzureML inferencing use	-inference

Examples:

The above naming convention may be simplified soon to something like this:

<framework>-<framework-version>[<gpu-driver><gpu-driver-version>-gpu]

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
`gpu-driver`	GPU driver	cuda
`gpu-driver-version`	GPU driver version, major and minor values only	11.6

Examples: