MicrosoftLearning / MicrosoftLearning/mslearn-mlops

"Deploy and monitor a model in Azure Machine Learning" deploy-prod fails at "Deploy model to managed online endpoint"

Open
#72 1 comment 0 reactions 0 assignees View on GitHub

@v-vfarias is already working on this.

Since Sep 4, 2026.

  • #73 by @v-vfarias — open
Dominant language
Jupyter Notebook
Stars
40
Forks
90
PR merge metrics
No merged PRs in 30d

Description

Following Deploy and monitor a model in Azure Machine Learning, "/deploy-prod" fails.

After commenting "/deploy-prod", it is supposed to create an endpoint and deploy to it.

The GitHub action fails at the "Deploy model to managed online endpoint" step with the following error:

Run python src/deploy_to_online_endpoint.py \
Traceback (most recent call last):
Connecting to Azure Machine Learning workspace...
  File "/opt/hostedtoolcache/Python/3.10.21/x64/lib/python3.10/site-packages/azure/core/polling/base_polling.py", line 950, in run
Ensuring online endpoint 'diabetes-endpoint-73dcd7c9' exists...
    self._poll()
  File "/opt/hostedtoolcache/Python/3.10.21/x64/lib/python3.10/site-packages/azure/core/polling/base_polling.py", line 982, in _poll
    raise OperationFailed("Operation failed or canceled")
azure.core.polling.base_polling.OperationFailed: Operation failed or canceled

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "/home/runner/work/mslearn-mlops/mslearn-mlops/src/deploy_to_online_endpoint.py", line 119, in <module>
    main()
  File "/home/runner/work/mslearn-mlops/mslearn-mlops/src/deploy_to_online_endpoint.py", line 100, in main
    endpoint = ensure_endpoint(ml_client, args.endpoint_name)
  File "/home/runner/work/mslearn-mlops/mslearn-mlops/src/deploy_to_online_endpoint.py", line 57, in ensure_endpoint
    return ml_client.online_endpoints.begin_create_or_update(endpoint).result()
  File "/opt/hostedtoolcache/Python/3.10.21/x64/lib/python3.10/site-packages/azure/core/polling/_poller.py", line 323, in result
    self.wait(timeout)
  File "/opt/hostedtoolcache/Python/3.10.21/x64/lib/python3.10/site-packages/azure/core/tracing/decorator.py", line 119, in wrapper_use_tracer
    return func(*args, **kwargs)
  File "/opt/hostedtoolcache/Python/3.10.21/x64/lib/python3.10/site-packages/azure/core/polling/_poller.py", line 342, in wait
    raise self._exception  # type: ignore
  File "/opt/hostedtoolcache/Python/3.10.21/x64/lib/python3.10/site-packages/azure/core/polling/_poller.py", line 247, in _start
    self._polling_method.run()
  File "/opt/hostedtoolcache/Python/3.10.21/x64/lib/python3.10/site-packages/azure/core/polling/base_polling.py", line 965, in run
    raise HttpResponseError(response=self._pipeline_response.http_response, error=err) from err
azure.core.exceptions.HttpResponseError: (SubscriptionNotRegistered) Resource provider [N/A] isn't registered with Subscription [N/A]. Please see troubleshooting guide, available here: https://aka.ms/register-resource-provider
Code: SubscriptionNotRegistered
Message: Resource provider [N/A] isn't registered with Subscription [N/A]. Please see troubleshooting guide, available here: https://aka.ms/register-resource-provider
Error: Process completed with exit code 1.

Contributor guide

No contributing guide indexed for this repository

First steps

  1. Read the whole issue, then the project's contributing guide.
  2. Comment on the issue to say you are picking it up — it saves two people doing the same work.
  3. Fork the repository and make your change on a branch.
  4. Open a pull request that references the issue number.

Research direction

Start with the deploy-prod GitHub Action and src/deploy_to_online_endpoint.py, especially ensure_endpoint at line 57 and the call at line 100. Reproduce the managed online endpoint deployment and inspect the Azure operation behind the SubscriptionNotRegistered error. Done means the action completes the deployment step successfully.

Written by the indexing model from the issue text.

Assessment

Tech stack
azure, github-actions, python
Domain
ci-cd, cloud, machine-learning
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Clearly specified
Newbie friendliness
25/100

Get new issues in your inbox

A short digest of beginner-friendly GitHub issues.