Hi @powerbiexpert22,
Thanks for reaching out to the Microsoft fabric community forum and for clarifying that you’re asking about concurrent users rather than total licensed seats. In Microsoft Fabric (just like in Power BI Premium), capacity sizing isn’t driven by no of users but by the amount of compute and memory you’ve purchased and how many simultaneous workloads that can sustain as already mentioned by @lbendlin.
Here’s a breakdown for the F2 capacity and what F2 actually gives you:
Compute power:
* 4 Spark v-Cores for on-demand Spark workloads.
* 2 Capacity Units (CUs) per second, which Fabric’s engine uses to throttle and smooth background jobs across the day.
* Memory and storage are likewise fixed.
Spark notebook concurrency
On an F2 SKU, because you have just 4 v-Cores, only one Spark session can run at a time. If User A is
actively running code in Notebook 1, and User B tries to start a second session in Notebook 2, that
session will queue (and eventually time out with a “too many requests” error)
Dataflows and pipelines
Dataflows and Lakehouse transformations share those same CUs. If you run multiple dataflows or
pipelined jobs at once, they’ll compete for the same pool of 2 CUs/sec and queue if you exceed
capacity.
I would also take a moment to thank @lbendlin and @Deku, for actively participating in the community forum and for the solutions you’ve been sharing in the community forum. Your contributions make a real difference.
If I misunderstand your needs or you still have problems on it, please feel free to let us know.
Best Regards,
Hammad.
Community Support Team
If this post helps then please mark it as a solution, so that other members find it more quickly.
Thank you.
