Openscoring application for the Docker distributed applications platform

[Openscoring] (https://github.com/jpmml/openscoring) provides REST API for publishing and evaluating predictive models:

• Model deployment and undeployment
• Model evaluation in single prediction, batch prediction and CSV prediction modes
• Model metrics

Prerequisites:

• Docker 1.5 or newer

GitHub repository [jpmml/openscoring-docker] (https://github.com/jpmml/openscoring-docker) contains a Dockerfile for Openscoring command-line server application.

Building the latest Openscoring application image from the HEAD revision:

sudo docker build -t jpmml/openscoring:latest github.com/jpmml/openscoring-docker

Additionally, this GitHub repository is tracked by Docker Hub repository [jpmml/openscoring] (https://registry.hub.docker.com/u/jpmml/openscoring/) using the "Automated Builds" mechanism.

Pulling a stable Openscoring application image:

sudo docker pull jpmml/openscoring:1.2.2

Running the image in the host networking mode:

sudo docker run --net="host" jpmml/openscoring:latest

The container shares host's network stack. It is possible to use privileged HTTP methods PUT and DELETE for deploying and undeploying models, respectively.

Running the image in the bridge (default) networking mode:

sudo docker run --net="bridge" -p 8080:8080 -v /path/to/pmml:/openscoring/pmml jpmml/openscoring:latest --model-dir /openscoring/pmml

The container uses Docker's default network setup, which is separate from host's network stack. It is impossible to use privileged HTTP methods. The only option for deploying and undeploying models is via the model auto-deployment directory /openscoring/pmml. This directory is mapped to host's filesystem directory /path/to/pmml using the data volume mechanism.

Openscoring is dual-licensed under the [GNU Affero General Public License (AGPL) version 3.0] (http://www.gnu.org/licenses/agpl-3.0.html) and a commercial license.

Please contact [[email protected]] (mailto:[email protected])