Deployment options
In Azure DevOps on the Pipelines page, there is a pipelineAn automated "conveyor belt" that moves data from one place to another or performs a task automatically. to deploy an environment to Microsoft FabricAn all-in-one data and analytics platform from Microsoft. Think of it as a "digital warehouse" for all your company's information.. When 'Run Pipeline' is chosen, the following parameters can be set:
| Name | Description |
|---|---|
| Branch/tag | The branch to be deployed (default=main) |
| environments | Add one or more environments. For example -tst or multiple environments at once |
| Bronze / Silver / Gold | Three separate booleans selecting which layers to deploy (at least one must be selected) |
| Deploy Notebooks | Deploy the notebooks to Fabric (Changed/All/No) |
| Deploy SQL Objects | Deploy objects to the lakehouseA place where you store both "raw" data (like files) and "organized" data (like tables). It combines the best of a File Cabinet and a Database. (Changed/All/No) |
| Deploy Tabular Models | Deploy tabular models to PowerBI.com (Changed/All/No) |
| Deploy Reports | Deploy Power BI reports to PowerBI.com (Changed/All/No) |
Deploy options (Changed/All/No)
The four deploy parameters share the same values:
- Changed: Only artifacts touched since the previous commit (detected with a git diff) are deployed. When a shared file changes (a notebook template,
reports.yaml, ormodel.yamlfor the Gold objects), the pipeline widens the selection automatically. - All: Everything in the category is deployed, regardless of changes.
- No: This step is skipped completely.
The metadata files (YAMLA simple way to write configurations. It's basically a list that computers can read easily.) are uploaded to the Meta lakehouse unconditionally on every deploymentThe process of "pushing a button" to make your configuration actual, working software in the cloud. — there is no separate parameter for them.
In the current canonical pipeline the Power BI report deployment step (pbix) is disabled (commented out), so the "Deploy Reports" parameter has no effect until that step is re-enabled.
The deployment pipeline in Azure DevOps will do the following:
Build
- Check the yaml files for common errors before deploying
- Generate the scripts for the objects to use for deployment
Deployment
- Copy yaml files to the Meta Lakehouse
- Deploy notebooks to the Meta, Bronze, Silver and Gold lakehouse
- Run a notebook that will create* the objects in the different lakehouses