Automation

This folder features multiple CI/CD pipelines for automating various tasks in the MLOps process. However, these pipelines are often very use case specific, hence often need to be adapted to your needs.

Training, Deploy, Test pipeline

Filename: train-register-deploy.yml

This Azure DevOps pipeline shows an example for the following flow:

  1. Train model
  2. Register model
  3. Deploy model
  4. Run automated tests against the deployed model

As an outcome, this pipeline creates a deployed model that has been tested and can be consumed by an application or user via API.

Deploy ML pipeline pipeline

Filename: deploy-ml-train-pipeline.yml

This Azure DevOps pipeline shows an example for the current flow:

  1. Deploy ML training pipeline
  2. Tested deployed ML pipeline with a small training set
  3. Publish pipeline to a Pipeline Endpoint

As an outcome, this pipeline deploys an AML training pipeline that can be triggered by another application or user to (re-)train a model with new data.