Exam DP-203 topic 1 question 107 discussion

This has to be B. If you have experience working with Azure before you will know that it is impossible to export anything as an ARM template with validation errors. https://learn.microsoft.com/en-us/azure/azure-resource-manager/troubleshooting/error-invalid-template?tabs=bicep Scroll down to "Solution 3".

You can't export an ARM Template with validation errors. I don't know why some people voted yes on this one.

From Azure documentation: When exporting from a resource group or resource, the exported template is generated from the published schema We can't publish with errors so this cannot be done with ARM template export. https://learn.microsoft.com/en-us/azure/azure-resource-manager/templates/export-template-portal

B is correct. ARM template will only have latest Pipeline work only when published. Since the pipeline has validation errors it can't be published.

Yes, you can export Azure Data Factory (ADF1) pipelines, datasets, linked services, and other artifacts as Azure Resource Manager (ARM) templates. This process allows you to capture the configuration of your data factory in a JSON-based template format. You can then use this template to automate deployment, manage version control, or replicate your data factory across different environments. Exporting an ADF1 data factory as an ARM template can be done from the Azure portal. Simply navigate to your data factory, select the "Author" tab, and then click on "Export ARM template" from the menu. This will generate an ARM template containing the definition of your data factory and its components, which you can download and use as needed.

Exporting the Azure Data Factory (ADF) as an Azure Resource Manager (ARM) template would capture the logic of the pipeline along with other ADF resources. This allows you to save the configuration and logic of the pipeline in a structured format, even if the Save button is unavailable due to validation errors. While it doesn't directly fix the validation errors, it ensures that you have a backup of the pipeline definition in an ARM template, which can be modified and redeployed later.

Answer is B. The ARM template is disabled or rather it is not available in ADF ,hence there is no template to export .This means that there no template to hold the logic of the program. However, when it is connected to the git,the template is enabled in there (lol..They are good marketers)

This will allow you to save the logic of the pipeline and make changes to it as needed

No, exporting ADF1 as an Azure Resource Manager (ARM) template does not meet the goal of ensuring that you can save the logic of the pipeline. ARM templates are used to deploy resources, not to save the logic of a data pipeline. To save the logic of the pipeline, you need to resolve the validation errors that are preventing the pipeline from being published. Once the errors are resolved, the Save button will become available, and you can save the pipeline.

answer is A as it is possible to use an ARM template to save the logic, but it's not necessarily best practice when you could use a git repo instead

A. Yes Exporting ADF1 as an Azure Resource Manager (ARM) template will capture the logic of the pipeline in JSON format. Even if the Save button is unavailable in the Azure Data Factory Studio due to validation errors, exporting the ARM template allows you to save the pipeline logic in a file. You can then review and edit the JSON code to correct the validation errors and redeploy the updated ARM template to resolve the issues.

From chat gpt: Yes, exporting the Azure Data Factory (ADF1) as an Azure Resource Manager (ARM) template can meet the goal of ensuring that you can save the logic of the pipeline, even when the Save button is unavailable due to validation errors. When you export the Azure Data Factory as an ARM template, it captures the entire structure and configuration of the Data Factory, including pipelines, datasets, linked services, triggers, and other artifacts in JSON format. This exported ARM template serves as a backup or snapshot of your Data Factory configuration. Therefore, by exporting ADF1 as an ARM template, you create a backup of the entire Data Factory structure, including the complex data pipeline that you built. This allows you to save the logic of the pipeline, despite the Save button being unavailable due to validation errors. Later, you can rectify the issues causing validation errors and re-import the updated ARM template to restore the logic of the pipeline.