If you're lucky, the system you're trying to simulate has good in-vivo recordings. That way you can compare the in-silco models directly to the real ones using either firing rates, LFPs, or other neuronal dynamic. Unfortunately, most of the time that isn't the case.

Trying to simulate a 3000 cells and 500K connections of the fly brain is not a computational problem, it's a knowledge one. If you can find functional properties to build a spiking/rates model, and data to compare it too; then it would be feasible (although a lot of work) to build and run simulations on the model. But without that extra info, and only using the physical connectome, there would be very little reason to try to do so.

We can model some aspects essentially completely - that's basically what this map covers, the "obvious" physical connections. Simplified forms of this can probably be simulated very very quickly. Sometimes that's sufficient.

It's not the complete picture though, normally that brain would be in an ever-changing soup of chemicals, which definitely impact behavior... somehow. Simulating that, and even knowing what might be relevant to simulate, will never be complete. Only incrementally better than previous attempts.