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Comment by qwerty456127 | Hacker News Reader

Reads cool until you reach the "5 seconds baseline" part.

Computations in finance can be quite time intensive, and are typically repeated many times with slightly modified (bumped) inputs to compute risks (finite difference approximations to partial derivatives). An initial 5s startup is negligible then.

I know. That's Ok to add 5 seconds to a lengthy financial calculation, from the purely practical point of view. Nevertheless it still looks awkward. My entire computer boots in comparable time nowadays (perhaps some seconds more) and somehow a Python app takes this much just to start up in such an environment.

Cloud-like run environments would typically have some network to do. Comparing booting an OS from a local SSD with booting from network-reachable resources isn't really fair due to huge difference in the performance of the "resource bus" assigned to each case in my opinion.

AWS lambda is also slow to warm up

It's an order of magnitude faster in terms of warm up times - Python Lambdas warm up in ~100 ms.

Depends on the base you use for orders of magnitude. In base 10, 100→5,000 ms is 1.7 orders of magnitude, but in base 2 (which I think is useful because we intuitively understand that twice as long or half as long make a big difference) it is 5.6.

I don't know if natural logarithms make sense in this context, but if so: using base e 100→5,000 ms is 3.9 orders of magnitude.

Regardless, it is IMHO a reasonably big deal, a bigger deal than 'an order of magnitude faster' indicates.

If you're allowed to pick the base then any difference can be 'an order of magnitude'.

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