Hi everyone, I've been learning Flux for a few weeks now, mostly for automating our event registration follow-ups and lead scoring. I'm really enjoying how it connects our forms to our CRM.
As I build more complex workflows—like ones that branch based on survey answers and then update multiple systems—I'm starting to wonder about performance. My workflows are still small, but I'm thinking ahead.
I'm curious if anyone has done or seen any benchmarks comparing Flux's execution speed against tools like Zapier, Make, or even Pipedream? I'm not just talking about the trigger polling, but the actual execution time of a workflow step-by-step.
Specifically, for those of you handling higher volumes:
* Is there a noticeable delay on multi-step workflows with data transformations or filters?
* Does using built-in apps vs. HTTP requests make a difference in speed?
* How does it feel compared to other platforms you've used?
I'm trying to understand if this is something I should factor into my planning as our processes get more involved. I couldn't find any formal benchmarks on their site or in the docs.
Great question about the execution speed - I've been wondering the same thing. In my experience with Jira and Asana automations, the built-in apps do feel faster than custom HTTP requests, especially on multi-step flows.
I ran a few informal tests last month comparing Flux to Make for a ticket routing workflow. The difference wasn't huge for simple triggers, but when I added three conditional branches and a data transformation step, Flux was consistently 15-20% slower. Not deal-breaking, but noticeable if you're processing hundreds of items per hour.
Have you tried their beta queue system? It helped with our volume spikes. The docs don't talk much about performance tuning, which is annoying.
That's interesting about the built-in apps feeling faster. I just started using their HTTP request steps for a webhook to our own API, and I did notice a bit of a lag compared to their Google Sheets app.
Have you found any tricks to speed up those custom HTTP steps, or is it just a trade-off for the flexibility?
That 15-20% figure for multi-step workflows lines up with what I've seen, especially when you start chaining data transformations. It's the conditional logic that really seems to hit Flux harder than some competitors.
The beta queue system is good for handling spikes, but it's just moving the problem - your execution time is still slower, the jobs just wait in line better. I'd be more interested in them optimizing the runtime itself.
Have you tracked whether the slowdown is consistent across all app types, or is it mostly tied to those custom HTTP steps?