tensorflow-serving

Kubefaas: Tensorflow Serving Environment

This is the Tensorflow Serving environment for Kubefaas.

It's a Docker image containing a Go runtime, along with a tensorflow serving service.

How it works

Tensorflow Serving is an serving service that supports both RESTful API and gRPC endpoints. In current implementation, Go server launches tensorflow_model_server to load in model during specialization. As long as the Go server receives requests from router it creates a reverse proxy that connects to RESTful API endpoint exposed by tensorflow_model_server and get response from the upstream server for user.

Build this image

docker build -t USER/tensorflow-serving . && docker push USER/tensorflow-serving

Using the image in kubefaas

You can add this customized image to kubefaas with "kubefaas env create":

kubefaas env create --name tensorflow --image USER/tensorflow-serving --version 2

After this, kubefaas functions that have the env parameter set to the same environment name as this command will use this environment.