8. Debugging
Workflow debugging effectively prevents errors and ensures successful automation execution.
Mastering Workflow Debugging: Essential Skills for n8n
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🛠 The final video in the n8n beginner course focuses on workflow debugging , a critical skill for fixing errors that occur when a workflow is activated in production .
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🔍 Debugging is the process of identifying and resolving issues that cause a specific node within a workflow to fail, which could be due to misconfiguration , unavailable services , or missing input data .
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📜 Execution history allows users to see failed workflow executions and debug them sequentially to avoid repeating errors .
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🖥 The in-editor debug feature is highlighted as a powerful tool that allows users to pin data from failed runs to the current workflow canvas for easier debugging .
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🔄 The retry after error correction feature allows you to re-trigger a failed run, which can be especially useful when multiple runs fail due to the same issue .
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📚 The output editing feature and workflow version history enable manual adjustments and are also useful debugging tools that allow users to revert to previous workflow versions if necessary.
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⚙ Two real-world examples of workflow debugging illustrate the process of error handling and ensuring successful execution, emphasizing the importance of error handling throughout workflow development .
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🎓 This video concludes with a sneak peek into an advanced course that covers more complex topics related to building and debugging workflows .
LiveWiki, the key content on YouTube in 10 seconds! - https://livewiki.com/ko/content/n8n-beginner-course-debugging
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In this video we'll cover workflow debugging.
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Debugging is an important process for correcting errors and preventing them from happening again.
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Workflow errors can be caused by: incorrect settings, service failures (e.g. 500 errors in Google Sheets or Slack), input data issues, etc.
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You can check and debug failed workflows in the execution log.
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Describes situations in which automation can fail without error.
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Emphasize the importance of error handling.
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Debug in Editor feature description: Debug by pinning data from a failed run to the current workflow canvas.
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Similar to the pin function used in the webhook node, only one data can be pinned at a time.
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After the error is corrected, the failed execution can be re-run using the Retry function.
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Re-execution will start from the node where the error occurred, and if there are errors in previous nodes, they will need to be copied to the editor and re-executed.
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Edit Output feature: Manually edit the output of a specific node for quick testing or debugging.
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Not suitable for large-scale problems.
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Workflow Version History feature description: You can revert to a previous workflow version or check the structure.
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Combined with the Retry feature, you can retry multiple executions after rolling back to a previous version.
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06:09 – 07:33:
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Debugging Example 1: Identifying errors in a failed workflow and pinning error data to the canvas to resolve the issue.
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Modified to retrieve data by email if there is no ID.
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07:33 – 09:59:
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Debugging Example 2: How to send a notification as a Slack message when the data received from a webhook does not have an ID.
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If an error occurs and there is no ID or email, use the Stop and Error node to generate an error message.
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09:59 – 11:41:
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Another example: How to handle cases where no data is returned, but no error occurred.
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Use the Always Output Data option to return an empty entry even when there are no contacts.
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11:41 – 15:05:
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How to generate an error message instead of sending a Slack message when there is no email.
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Optimize your workflow to handle errors when they occur.
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15:05 – 15:48:
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If your workflow is invalid, use the Throw Error node to raise an error so that others can troubleshoot the issue.
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The final video covers how to debug your workflow and fix errors.
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15:48 – End:
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Advanced courses will cover more complex workflow building, data flow, error handling, and debugging methods.