I am interested in knowing how can I integrate a repository with Azure Machine Learning Workspace.
I have some experience with Azure Data Factory and usually I have setup workflows where
I have a dev
azure data factory instance that is linked to azure repository.
Changes made to the repository using the code editor.
These changes are published via the adf_publish
branch to the live dev
instance
I use CI / CD pipeline and the AzureRMTemplate task to deploy the templates in the publish branch to release the changes to production
environment
The following workflow is the official practice to be followed to achieve the task required.
Follow the below steps to complete the procedure
Before implementation:
- We need azure subscription enabled account
- DevOps activation must be activated.
Open DevOps portal with enabled SSO
Navigate to Pipeline -> Builds -> Choose the model which was created -> Click on EDIT
We need to use Anaconda distribution for this example to get all the dependencies.
To install environment dependencies, check the link
Use the python environment, under Install Requirements in user setup.
Select create or get workspace select your account subscription as mentioned in below screen
The entire CI/CD procedure and solution was documented in link
Document Credit: Praneet Singh Solanki