mlflow-serve-api-openshift-infrastructure

Introduction

This repository contains MLflow's model serving capability Dockerfile as well as infrastructure-as-code needed to run on OpenShift.

Quick start

Trying it out locally

The fastest way to try it out is by start a container locally. You can build container first by running:

docker build .

You can then start the container by running:

docker run -it -p 5000:5000 \
    -e MODEL_ARTIFACT_URI=<ARTIFACT LOCATION> \
    -e AWS_ACCESS_KEY_ID=<AWS_ACCESS_KEY_ID> \
    -e AWS_SECRET_ACCESS_KEY=<AWS_SECRET_ACCESS_KEY> \
    <container image ID>

Running it on OpenShift for production use case

After running docker build . and image it pushed to an place which stores Docker Image such as Docker Hub, you can use following command to do deployment:

oc process -f deployment.yaml \
    -p IMAGE_URL=<image URL> \
    -p DEFAULT_ARTIFACT_ROOT="s3://<your path to model>/model" \
    -p AWS_ACCESS_KEY_ID=<key> \
    -p AWS_SECRET_ACCESS_KEY=<password> \
    | oc apply -f-