Why Is My Active n8n Workflow Suddenly Not Executing Without Errors?

Based on the description and the fact that you’re running n8n Cloud, one common culprit for an active workflow stopping suddenly—without an explicit error message—is that the workflow execution may have exceeded your instance’s memory limits. Here are a few points to consider:

Possible Cause: Memory Constraints

• Memory usage: n8n Cloud plans have specific memory limits (for example, Starter has 320 MiB RAM while Pro-2 has 1280 MiB RAM). If your workflow processes large amounts of data or uses memory-heavy nodes (such as the Code or Function nodes), it might consume more memory than available.
• Automatic restarts: On n8n Cloud, when an out-of-memory situation occurs the instance is automatically restarted. This can lead to executions stopping without an obvious error message being shown in the UI.
• Workflow design: Complex or heavy workflows (especially ones operating with multiple nodes or processing large binary data) can peak memory usage unexpectedly.

Recommendations

1. Review and Optimize the Workflow:

   • Ensure that you’re not saving unnecessary execution data. On Cloud, you can disable saving for successful executions through workflow settings.
   • Break down particularly heavy parts of the workflow or optimize nodes that require large data processing.

2. Monitor Memory Consumption:

   • Use the Admin Panel to check resource usage if available. This might give you hints if the memory consumption is spiking during the workflow execution.
   • Consider simplifying or restructuring the workflow to reduce the data being passed between nodes.

3. Upgrade Your Plan (if necessary):

   • If your workflows have grown in complexity and data volume, you might need more memory. Upgrading to a plan with higher memory limits can help prevent such out-of-memory terminations.

Next Steps

• Check the n8n Cloud Dashboard: Look for any automated alerts or logs that might indicate that the instance was restarted due to overloading memory.
• Isolate the Issue: If possible, run a simpler version of the workflow to determine which part is causing the increase in memory consumption.
• Review Best Practices: Ensure you’re following n8n's recommended guidelines for building memory-efficient workflows.

If you continue to encounter issues, providing additional details about which part of the workflow might be heavy or any recent changes could help further diagnose the problem.

Below are some troubleshooting steps and considerations based on our documentation that might help identify why an active workflow suddenly stopped without showing an error:

1. Check the Workflow Execution Log

Even if no error message is shown in the node output, n8n logs every execution. In the Editor UI, click on All executions in the left panel to see a list of recent runs. Look for any indication that the workflow status changed (for example, from Succeeded to Cancelled or Failed without an explicit error) or stopped at a particular node.

2. Review Workflow Settings

Make sure that the workflow settings haven’t been changed inadvertently. In the Workflow Settings (accessed via the three dots in the upper right of the Editor UI), check if options like “Save successful production executions” are configured as expected. Changes here might affect how and if executions are logged.

3. Check Resource or Memory Limits

Although cloud setups generally handle resource limits, if your workflow handles large amounts of data (for example, with memory-heavy nodes), it might hit resource constraints that cause an execution to stop. On n8n Cloud, different plans have specific memory limits, and if a workflow goes beyond these limits, it might be forcefully stopped. Double-check that your workflow doesn’t inadvertently use excessive memory.

4. Re-run or Test the Workflow Manually

If the workflow stopped unexpectedly without an error, try triggering it manually. This can help determine whether the issue is repeatable or only occurred under specific conditions during scheduled runs.

5. Check System or n8n Logs

On n8n Cloud, system logs may provide additional insight into why the workflow stopped suddenly. Look for any messages related to memory consumption or connectivity that might give a clue.

If after these steps the issue continues without clear error messages, consider reaching out to n8n support with details about your recent workflow executions and any observed resource usage. This information can help identify whether the issue is due to factors like unexpected workflow behavior or resource constraints.

These suggestions are based on the available n8n documentation on workflow executions, settings, and resource management.