Overview
This lesson is part of the n8n AI Automation - Zero to Hero course, Section: 4. Error Handling & Debugging.
Watch the video above for the full tutorial, or read the written guide below.
What does n8n's Debug in Editor feature do?
Debug in Editor copies a failed production execution directly onto your n8n canvas in fully editable mode, so you can inspect and fix the exact data that caused the failure without re-triggering your webhook or reloading fresh data. You open the execution log, locate the failed run, and click "Debug in Editor" to load the erroneous payload into every node as live, editable input.
How do you retry a failed execution in n8n?
The Retry Execution button, located next to Debug in Editor in the execution log, replays a failed run so no data is lost from one-off failures caused by temporary outages. Clicking it surfaces two options: "Retry with currently saved workflow from node with error" runs the failed payload through your latest workflow changes, while "Retry with original workflow from node with error" reruns the exact workflow that was live at the time of failure.
If a downstream service like AWS SES was temporarily unavailable, retrying with the original workflow reproduces the error. Retrying with the currently saved workflow, after you have applied a fix, picks up exactly where the run stopped and processes the original payload through your corrected nodes, ensuring no data is lost.
How does Workflow Version History work in n8n?
Workflow Version History saves a snapshot every time you save a workflow, letting you restore any previous version from the history panel. You access it via the "Workflow History" button next to the Save button on the canvas. Each saved version is listed with a timestamp, and the action menu on each entry lets you restore, clone to a new workflow, open in a new tab, or download the version.
Restoring a version replaces the current workflow immediately. In the lesson demo, restoring an earlier version reverts both the misconfigured property reference (from email back to user_email) and the sender domain, confirming the rollback is complete. The Starter plan limits version history to one day; the $60 per month plan extends retention to five days.
How do you prevent recurring errors from silently failing n8n workflows?
The IF node routes workflow execution based on a condition check, catching bad input before it reaches fragile nodes like an email sender. In the lesson demo, an IF node checks whether the incoming email field is non-empty before the AWS SES node runs. The true branch continues the workflow; the false branch connects to a Stop and Error node, which halts execution and raises an explicit error instead of letting the workflow silently succeed with invalid data.
Logging bad records to a Google Sheet on the false branch is one option, but the instructor flags that attaching a Stop and Error node is more elegant because it triggers n8n's error workflow system. That system handles recurring data-quality failures centrally, a topic covered in the next lesson of the course.
Key Takeaways
- Debug in Editor loads a real failed execution onto an editable canvas so you fix the exact payload that broke the workflow, with no need to re-trigger the webhook or reload data.
- Retry Execution offers two modes: "current workflow" applies your latest fixes to the original payload, while "original workflow" reruns the flow exactly as it was, confirming whether a temporary outage or a configuration error caused the failure.
- Workflow Version History saves a snapshot on every save; the Starter plan retains one day of history, the $60 per month plan retains five days, and restoring a version immediately replaces the current workflow.
- The IF node guards fragile nodes by validating input data upstream, routing invalid records to a Stop and Error node rather than crashing mid-execution with a silent or ambiguous failure.
- Stop and Error node raises an explicit error on the false branch of your validation IF node, enabling n8n's error workflow system to handle recurring data-quality problems centrally rather than burying them in execution logs.
Related Lessons
- Lesson 21: Master Error Handling in n8n | Build Reliable n8n Workflows That Don't Break
- Lesson 32: Master AI Automation Workflows Debugging & Error Handling with Execution Logs
- Lesson 34: Error Workflows in n8n AI Automation | Stop & Error Node | Error Trigger Node
Next Steps
Continue your n8n journey with the full n8n AI Automation - Zero to Hero course.