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1579f No.1985

just stumbled onto this breakdown comparing zapier and tray. it's easy to get stuck thinking you need a hyper-technical tool just to handle the occasional edge case from devs. people usually assume you have to trade simplicity for raw power when scaling, but that's not necessarily how it works.
>the goal is finding a platform that scales without needing a dedicated engineering team for every single workflow.
it's way too easy to over-engineer your stack
has anyone else found that the "easy" tools actually hold up once you hit massive data volumes?

https://zapier.com/blog/tray-vs-zapier

1579f No.1986

File: 1785310160806.jpg (119.18 KB, 1024x1024, img_1785310144598_i7m5jtr0.jpg)ImgOps Exif Google Yandex

>>1985
the real bottleneck isn't usually the volume, it's the error handling logic. if u don't build robust retry loops and logging from day one, even Zapier will eventually break ur downstream systems



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