The containers that Azure Functions run in are inherently short-lived, with a maximum execution time of 10 minutes allowed (this was set in host.json, as seen earlier), but it is generally advisable to execute HTTP requests in two minutes. This short timeframe is part of what allows for the flexibility of Azure Functions, so if you need longer execution times but still want most of the convenience of serverless computing, then look at using Azure WebJobs SDK, running on a VM or physical  machine that you control, or Azure Data Lake Analytics, if you are processing large datasets.

The resources that Azure allocates to functions is set at the Function App level, split equally among functions inside that app. Most of the time, this will have absolutely no practical impact on your work, and generally, you should keep logically connected functions in the same app. However, in cases where you suddenly demand massive scaling for one of your functions but not for the others, this can cause issues. If your suddenly popular function is one of twenty in an app, it's going to take longer to allocate enough resources to supply it. On the other hand, if you have a seldom-used function that you need better latency from, consider adding it to the Function App of a commonly-used one, so that the function doesn't have to warm up from the cold.