Why Does My Ml Model Deployment In Azure Container Instance Still Fail With "current Service State: Transitioning"?

I am using Azure Machine Learning Service to deploy a ML model as web service. I registered a model and now would like to deploy it as an ACI web service as in the guide. To do so

Solution 1:

If ACI deployment fails, one solution is trying to allocate less resources, e.g.

aciconfig = AciWebservice.deploy_configuration(cpu_cores=1, 
                  memory_gb=8, 
                  tags={"data": "text",  "method" : "NB"}, 
                  description='Predict something')

While the error messages thrown are not particularly informative, this is actually clearly stated in the documentation:

When a region is under heavy load, you may experience a failure when deploying instances. To mitigate such a deployment failure, try deploying instances with lower resource settings [...]

The documentation also states which are the maximum values of the CPU/RAM resources available in the different regions (at the time of writing, requiring a deployment with memory_gb=32 would likely fail in all regions because of insufficient resources).

Upon requiring less resources, deployment should succeed with

Creating service Running...................................................... SucceededACI service creation operation finished, operation "Succeeded" Healthy