Deploy your Fashion MNIST model with Seldon
Seldon is an open source platform for deploying machine learning models on Kubernetes. Since FfDL stores your trained model in your Object Storage, it's very simple to deploy and serve it using Seldon with the following steps.
Install Seldon(https://github.com/SeldonIO/seldon-core/blob/master/docs/install.md) on your Kubernetes Cluster. Then, install S2I(https://github.com/openshift/source-to-image#installation) for building any Seldon model image.
Go to the
seldon-deploymentdirectory, build your Seldon model image using S2I(https://github.com/openshift/source-to-image#installation) and push it to DockerHub.
cd seldon-deployment s2i build . seldonio/seldon-core-s2i-python2 <your model image name> docker push <your model image name>
- Modify deployment resource from the template
fashion-seldon.json. You need to set:
TRAINING_ID: Your FfDL Training ID
BUCKET_NAME: The name of the bucket containing your model
image: Your Seldon model image at DockerHub
You also need to create a kubernetes secret containing your bucket endpoint url, key and secret. You can use the
bucket-secret.yaml as a template. Edit
bucket-secret.yaml and enter the base64 values for endpoint url, key, secret. (e.g.
echo -n "my key" | base64)
Then, deploy the
bucket-secret.yaml to your cluster.
kubectl apply -f bucket-secret.yaml
- Deploy your Seldon model image on your Kubernetes Cluster.
kubectl apply -f fashion-seldon.json
Congratulations, your model is now ready to take input and return predictions of confidence in the picture being of a certain class.