Example on how to use Github Actions to set up a CI/CD pipeline for automating the development of a machine learning model on Azure ML. When you open a PR and make commits, a CI job is run to check code style and run unittests. You can start training model and deploy model directly from the PR comments. When the PR is merge to master, CD job is triggered to kick of re-training and deploying model in the Staging environment. When the deployment to Staging environment is finished, approval request will be promoted to reviewers. If approved, deploying to Production environment will start.
- You need to have an Azure service principle set up, and credentials stored as secret
in the repo to run the Azure CLI commands with GHA.
Follow steps described here to
to create a repo secret named
AZURE_LOGIN AZURE_RESOURCE_GROUP: your azure resource group nameAZURE_WORKSPACE: your azure workspace nameREPO_ACCESS_TOKEN: personal access token to github
Open a PR and comment following to submit training script:
/train param-file=dev_params.json
It will trigger a workflow to submit training script to AML. While it's running
the github actions bot is going post the following comments back on PR:
Comment following to deploy trained model:
/deploy model-name=iris_model model-version=26 service-name=irisservice
If you don't specify model-version, it will deploy the latest version of the model.
The deploy workflow will get trigger
See full example here