Azure Data Factory Save and Publish Constraints
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution. After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen. You have an Azure subscription that contains an Azure data factory named ADF1. From Azure Data Factory Studio, you build a complex data pipeline in ADF1. You discover that the Save button is unavailable, and there are validation errors that prevent the pipeline from being published. You need to ensure that you can save the logic of the pipeline. Solution: You disable all the triggers for ADF1. Does this meet the goal?
Community Votes
100% of anonymous learners picked answer B. Votes are pick records left by other test-takers — they are not the verified answer.
Community Insight
The exam tests the distinction between pipeline execution controls and version control/saving mechanisms, with the common trap being confusion about how ADF Studio handles unsaved changes.
This question tests the prerequisites for saving and publishing Azure Data Factory (ADF) pipelines. The community consensus is that disabling triggers does not resolve validation errors or enable the save button.
Candidates often select 'Yes' believing that stopping active processes (triggers) clears validation locks, but validation errors are structural issues independent of trigger states.
Community Discussion (3 comments)
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Expert Analysis
Why the Answer Is Correct
Disabling triggers has no impact on the ability to save pipeline logic or resolve validation errors in Azure Data Factory. Triggers control when pipelines run; they do not affect the design-time state of the pipeline or its publishability. The Save button availability and validation status are determined by the integrity of the pipeline definition itself.Why the Other Options Are Wrong
Selecting 'Yes' implies that runtime configurations influence design-time saving capabilities, which is incorrect. Validation errors indicate syntax or configuration issues within the pipeline components that must be fixed directly in the designer. Changing trigger states does not alter the underlying JSON structure or fix logical errors in activities.Community Comment Notes
Comments consistently highlight that Git integration is often required for saving changes in collaborative environments. Users note that if Git is not configured, users might rely on local browser storage, but validation errors remain the primary blocker regardless of version control settings.Official Reference
Exam Strategy
Focus on understanding the separation between design-time operations (saving, validating) and run-time operations (triggering, executing). When faced with 'Save' issues, check for Git configuration requirements first, then address specific validation error messages.