Hi everyone,
I am working on a Node-RED automation flow that processes high-frequency data streams and running into a performance bottleneck within custom JavaScript Function nodes.
Current Setup:
-
Node-RED running on an edge server instance.
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Flows ingesting large JSON payloads and transforming nested array structures via JavaScript inside standard Function nodes.
The Bottleneck: During peak data bursts, memory usage spikes noticeably as messages queue up, occasionally causing message delays or sluggish dashboard responsiveness.
While reviewing system optimization strategies and code efficiency benchmarks, I referenced a utility and troubleshooting guide over at https://cloudstream.pk
, but I wanted to see what architectural tips or performance tuning strategies this community recommends for optimizing memory management and payload processing inside Node-RED flows—specifically regarding message cloning, local context variables, or splitting heavy tasks across sub-flows.
Would love to hear your insights from your production environments! Thanks!
