Debugging and Troubleshooting Data Pipelines

Debugging and troubleshooting are important aspects of the data pipeline development life cycle. While designing and implementing data pipelines, developers often encounter errors that need to be identified and resolved quickly to ensure smooth data integration. In this lesson, we’ll explore various debugging and troubleshooting techniques available in Azure Data Factory.

Debugging and troubleshooting concepts

• Pipeline validation: Before running a pipeline, it is important to ensure that the pipeline is valid and that all connections and dependencies are properly configured. Azure Data Factory provides a validation feature that enables developers to validate a pipeline for any syntax or semantic errors.

• Pipeline monitoring: Azure Data Factory provides detailed monitoring options to track the status of a pipeline. Pipeline runs can be monitored in real time, and logs can be collected to identify the root cause of any errors.

• Debugging in Visual Studio Code: Visual Studio Code is a popular integrated development environment (IDE) for Azure Data Factory. It provides a powerful debugging feature that enables developers to set breakpoints, inspect variables, and step through code to identify and resolve issues. ...