Azure ML Environment build fails

Marvin Joseph Guico Agor 67 Reputation points
2023-05-30T06:48:29.5466667+00:00

I am trying to construct a custom environment to be used in a scheduled pipeline. I used the following script to create the custom environment:

from azure.ai.ml.entities import Environment

env_docker_conda = Environment(
    image = "AzureML-sklearn-0.24-ubuntu18.04-py37-cpu", # Building on top of this pre-constructed environment
    conda_file = './src/conda-env.yml',
    name = "custom-env-trending-terms-01",
    description = "Custom Environment for Trending Terms"
)

ml_client.environments.create_or_update(env_docker_conda) # registering custom environment



Where the conda-env.yml file is defined as follows


name: required-env-cpu
channels:
    - conda-forge
dependencies:
    - python=3.80
    - nlp-rake
    - nltk
    - langdetect
    - pandas
    - numpy



I ran the code chunk (on kernel Python 3.10 V2). Checking the Environment's build status, I found that it failed.

User's image

Checking the build log, I found that it failed due to "Connection to container registry docker.io failed."

User's image

Would like to ask for any and all help: how could I resolve this issue?

Azure Machine Learning
Azure Machine Learning
An Azure machine learning service for building and deploying models.
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