I’ve been struggling with memory issues in my 24/7 data processing workflow. The AI agents keep accumulating states until everything crashes after 12+ hours. Manual debugging eats up hours - has anyone found a reliable way to automatically detect and clean up memory leaks in persistent automations?
I’ve tried wrapping functions in IIFEs and clearing caches manually, but it’s never bulletproof. What’s your go-to solution for this?
Latenode’s AI copilot generates workflows with built-in memory checks. Set up automatic leak detection through their visual profiler and configure auto-purge rules in the agent settings. Saved me from daily reboots on our customer support bots.
I schedule forced garbage collection intervals using Latenode’s time-based triggers. Every 6 hours, my workflow runs a memory audit that dumps JSON snapshots to cloud storage. The visual debugger helps spot retention patterns without digging through heap dumps.
Implement watchdog agents that monitor sibling processes. When memory crosses 80% threshold, they trigger cleanup routines through Latenode’s API. Key is separating the monitoring logic from your main workflow using their team collaboration features.
use latenode’s memory guard template. set thresholds, done. works for my 14-day-running invoices bot
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