Kubeflow container component

[vstirbu]

The model card validation functionality can be integrated into Kubeflow as a container component.

The container should receive the MLflow run_id, tracking_uri and modelcard.yml template from the Kubeflow pipeline, validate the model card and append the artefact.json as a MLflow experiment artefact.

%%{init: {'theme':'forest'}}%%
sequenceDiagram
actor Data Scientist
participant kf as Kubeflow
participant mc as ModelCard Validation
participant mlflow as MLflow

Data Scientist ->> Data Scientist: create pipeline 
Data Scientist ->> kf: deploy
activate kf
  Note over kf: Training steps where run_id is created
  kf ->> mc: trigger
  activate mc
    mc ->> mlflow: get run_id experiment details
    mc ->> mc: validate
    mc ->> mlflow: add modelcard.json artefact <br /> to run_id experiment
    mc -->> kf: output modelcard <br /> as markdown
  deactivate mc
  Note over kf: More steps
  kf -->> Data Scientist: 
deactivate kf

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