Overview

Gordo is based on parsing a config file written in Yaml that is converted into an Argo workflow. This is deployed with ArgoCD onto a Kubernetes cluster. The main interface after building the models is a set of REST APIs

Gordo is a CustomResourceDefinition represents the project and could contains multiple Machine Learning models.

gordo-controller is a K8S controller and an API server that provides Gordos/Models statuses.

dpl is a deployment Job thats run generate workflow command.

model_builder1, model_builder2 Jobs builds ML models with build command.

Model is the CustomResourceDefinition represents the model entity generated by the Argo workflow.

storage is PersistentVolume where ML models have to be stored.

gordo-server is a ML Server. Full API spec can be found here.