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Prebuilt Docker images for inference

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Prebuilt Docker container images for inference are used when deploying a model with Azure Machine Learning. The images are prebuilt with popular machine learning frameworks and Python packages. You can also extend the packages to add other packages by using one of the following methods:

Why should I use prebuilt images?

  • Reduces model deployment latency.
  • Improves model deployment success rate.
  • Avoid unnecessary image build during model deployment.
  • Only have required dependencies and access right in the image/container. 

List of prebuilt Docker images for inference

Important

The list provided below includes only currently supported inference docker images by Azure Machine Learning.

  • All the docker images run as non-root user.
  • We recommend using latest tag for docker images. Prebuilt docker images for inference are published to Microsoft container registry (MCR), to query list of tags available, follow instructions on the GitHub repository.
  • If you want to use a specific tag for any inference docker image, we support from latest to the tag that is 6 months old from the latest.

Inference minimal base images

Framework version CPU/GPU Pre-installed packages MCR Path
NA CPU NA mcr.microsoft.com/azureml/minimal-ubuntu18.04-py37-cpu-inference:latest
NA GPU NA mcr.microsoft.com/azureml/minimal-ubuntu18.04-py37-cuda11.0.3-gpu-inference:latest
NA CPU NA mcr.microsoft.com/azureml/minimal-ubuntu20.04-py38-cpu-inference:latest
NA GPU NA mcr.microsoft.com/azureml/minimal-ubuntu20.04-py38-cuda11.6.2-gpu-inference:latest

How to use inference prebuilt docker images?

Check examples in the Azure machine learning GitHub repository

Next steps