Attualmente sto valutando Google App Engine e una delle risposte da Limitazioni nascoste di Google App Engine? ha dichiarato:
Performance will surprise you. GAE is optimized for many tiny queries and you get warned if a query takes any CPU time at all. You get 6.5 (at last check) free hours per day, but it's a mystical number and you should test.
You'll find that time as you measure it doesn't relate to the CPU or datastore CPU time, because (for example) under the covers there might be multiple machines updating indexes during deletes/updates. Some users have found huge CPU usage when uploading bulk data - many hours of usage for e.g. 20 min of real time.
Your Java instance might need to be powered-up if it hasn't been hit in (I think) 20 minutes. The benefit is that they can pass their smart management on to you as cheaper costs, but it does mean you'll experience a short delay, and see a high CPU warning on the first request in a while.
For many cases, Python datastore access is faster than Java JDO. You'll likely find that using the low-level API for Java faster.
Some developers seem to have experienced more datastore errors thank you would expect (around 0.4-1% maybe?). I haven't yet.
Mi chiedo quali fattori determinino il tempo di CPU di un PaaS (come, in questo caso, le 6,5 ore gratuite ottenute con GAE). Ad esempio, include il tempo totale impiegato dal database per trasferire i dati sul client?
I costi con questo modello aumentano notevolmente man mano che ottieni più utenti?