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Email Alerts for Failed Scheduled Table Auto-Runs
is there a way of setting up email alerts when a table that is scheduled to auto-run the source fails?
is there a way of setting up email alerts when a table that is scheduled to auto-run the source fails?
There is currently no information in our documentation about setting up email alerts specifically for failures when a table scheduled to auto-run its source fails. You can schedule tables or columns to auto-run at set intervals, but notifications for failures are not mentioned as a feature. Are you looking for alternative ways to monitor or be notified about failed runs within the platform?
yes, I have a lot of tables that are running daily and it can take me some time to notice if one is failing
Currently, there is no feature in Clay that allows you to set up email alerts or notifications specifically for failed auto-run tables or scheduled columns. You can schedule tables or columns to run automatically at set intervals, but notifications for failures are not available as part of the scheduling functionality. To monitor failures, you would need to manually check your tables for any issues or failed runs. Are you interested in learning about any workarounds or best practices for quickly identifying failed runs within the platform?
lets put in a feature request for notifications on source fails please 🙂
Currently, Clay doesn't have a built-in notification system for failed scheduled sources. While you can schedule sources to automatically refresh data at daily, weekly, or monthly intervals, there's no feature to alert you when these runs fail. To submit a feature request for notifications when scheduled tables fail: 1. Email our support team at support@clay.com 2. Share your use case explaining why notifications would be valuable (like your situation with many daily-running tables) 3. Be specific about what you'd want to be notified about (source failures) Thanks for suggesting this improvement! Scheduling is one of our newer features, and your feedback helps us make it more robust.