Everything worked locally, but after deploying, my workflows started failing randomly. What changed
Describe the problem/error/question
What is the error message (if any)?
Please share your workflow
(Select the nodes on your canvas and use the keyboard shortcuts CMD+C/CTRL+C and CMD+V/CTRL+V to copy and paste the workflow.)
Share the output returned by the last node
Information on your n8n setup
- n8n version:
- Database (default: SQLite):
- n8n EXECUTIONS_PROCESS setting (default: own, main):
- Running n8n via (Docker, npm, n8n cloud, desktop app):
- Operating system:
1 Like
Hey @Heis_Femq Welcome to the n8n community !
Do youy mind sharing your workflow and the errors you are facing because there are many reasons this can happen as transition from test to production URLs (If you are using a webhook) , Having No Fallback Logic in AI Agents (Enable fallback model) , Not enabling error handling logic in node settings (have a separate branch to handle things when a node errors.),
You can also use a error trigger and configure to notify you about the errors if something happens in production,
Also if you’re self hosted then please recheck your base/Env variables.
WEBHOOK_URL, N8N_HOST, N8N_PROTOCOL, N8N_EDITOR_BASE_URL, VUE_APP_URL_BASE_API etc.
This is how users and webhooks actually reach n8n and sometimes if these variables dont match, you can see webhooks not firing, callbacks failing, or UI oddities.
I could assist you in more detail @Heis_Femq if i can have more context about the errors you are facing as well as the workflow, Appreciate it
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Hi @Heis_Femq Welcome! Can you please provide more information about your workflow and the error.
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Hello, there is likely nothing wrong with the logic in your workflow but rather a difference in the environment it is running in. This is usually caused by:
- Missing or different environment variables/credentials occurring in production.
- The local and production versions of n8n are different
- A switch to queue mode
- Webhooks pointing to test URLs and not production
- File system or resource limits
Start by analyzing your both your local and your production setup next to each other and check the error logs that are in production.