endpoint from a WSGI definitionΒΆ

endpoint using WSGI specification, which works with Python servers using WSGI-interface.

  • name: name of the deployment endpoint, this will be the final part of the URL

  • image: the Docker image that will be used as the deployment environment

  • wsgi: specifies the WSGI application to serve, specify the module (e.g. package.app) or the module and the WSGI callable (e.g. package.app:wsgi_callable)

  • description: (optional) more detailed human-readable description of the endpoint

  • files: (optional) files that will be loaded into the image, for example the trained model. The files will be in the same directory as your code, modified by the path property.

- endpoint:
    name: wsgi-endpoint
    description: predict digits from image inputs
    image: tensorflow/tensorflow:1.3.0-py3
    wsgi: predict_wsgi:predict_wsgi
      - name: model
        description: Model output file from TensorFlow
        path: model.pb

See also

Read more about WSGI on their website.