Seeking advice on optimizing a loop workflow to resolve an out-of-memory issue

[Blueli]

Hello
I have a list of URLs in a Google Sheet, around 200 in total. I use a loop node to process them in batches of 3 items each. However, the process stops at 33 items and shows as successfully completed (not failed). I’m not sure why this might be happening – could it be due to running out of memory? I am hosting this on a 1GB server.

Is there any way to optimize this workflow? My current process is to fetch the URL list, processing them in batches of 3 items, taking a screenshot, and converting the image file to base64 for Google Vision AI to read. And then update the Sheet Cell with the output data.
I suspect the base64 data consumes too much RAM. And any possible solution on this?

Thank you so much

[n8n]

It looks like your topic is missing some important information. Could you provide the following if applicable.

• n8n version:
• Database (default: SQLite):
• n8n EXECUTIONS_PROCESS setting (default: own, main):
• Running n8n via (Docker, npm, n8n cloud, desktop app):
• Operating system:

[Jon]

Hey @Blueli,

Can you share the worklfow json so we can see what is happening? Normally the best option when using a loop is to use a sub workflow for the processing that way once the subworkflow has finished the memory is released for the next loop.

[Blueli]

Hello. Turns out the loop node stopped was caused by no output data from the HTTP node. I have resolved it by enabling always output data option.
Thanks