Seldon Serving

    This Kubeflow component has stable status. See theKubeflow versioning policies.

    Seldon comes installed with Kubeflow. The provides full documentation for running Seldon inference.

    If you have a saved model in a PersistentVolume (PV), Google Cloud Storage bucket or Amazon S3 Storage you can use one of the prepackaged model servers provided by Seldon.

    Seldon also provides to wrap your inference code for it to run in Seldon.

    • An Istio gateway named kubeflow-gateway
    • A label set as

    The following example applies the label my-namespace to the namespace for serving:

    Create a gateway called kubeflow-gateway in namespace my-namespace:

    1. apiVersion: networking.istio.io/v1alpha3
    3.   name: kubeflow-gateway
    4.   namespace: my-namespace
    5. spec:
    6.   selector:
    7.     istio: ingressgateway
    8.   - hosts:
    9.     - '*'
    10.     port:
    11.       name: http
    12.       number: 80

    Save the above resource and apply it with kubectl.

    The Kubeflow Seldon E2E Pipeline shows how to build re-usable components for an ML pipeline.

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    Last modified 04.03.2020: