Quickstart template as a fork on TDSP (https://github.com/Azure/Azure-TDSP-ProjectTemplate), extending the template with a suggested structure for operationalization using Azure. Includes ARM templates as IaC for resource deployment, template build and release pipelines to enable model CI/CD, template code for working with Azure ML.
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README.md
MLOps Quickstart Template
This repo provides a quickstarter template as a fork on TDSP (https://github.com/Azure/Azure-TDSP-ProjectTemplate), extending the template with a suggested structure for operationalization using Azure. The current code base includes ARM templates as IaC for resource deployment, template build and release pipelines to enable ML model CI/CD, template code for working with Azure ML.
How to get started
- Clone this repo
- Make sure you have an Azure Subscription set up.
- Make sure you have an Azure DevOps instance set up.
- Import the build and release definitions ('Code'>'Operationalization'>'build_and_release') into Azure DevOps pipelines.
- Update the build and release definitions to use your credentials i.e. Azure subscription.
- Create an initial commit.
- If everything is set up correctly, Azure DevOps will provision your Azure Resources as triggered by the CI.
- Use the Azure CLI ML Extension (
az ml project attachcommand) or Azure ML SDK to configure your local workspace to use the created Azure ML workspace. - Run
Code/Modeling/train_submitto run your first AzureML experiment on remote compute.