In Function as a Service platform AWS Lambda, in case my function is executed inside a container:
A. When I provision the memory that my function will require during its execution, do I have to consider that some of the RAM will be consumed by the container? Or is it purely the memory that my function's code will require that I have to provision?
Furthermore, irrespectively of the answer to the above question:
B. In case I provision 8 GiB for the execution of my function, when the function's code is not executing and the container is idle (AWS says that the system usually keeps the container idle in memory for a non-deterministic amount of time, after the function's execution, for example between 5 - 15 minutes), will the system keep reserved the 8 GiB that I provisioned for the function or just the memory required for keeping the container in memory?
C. What is usually the average RAM required for an idle container? I understand that this depends, but I would appreciate just an indication from your experience (for example for a base container with Python runtime).
Many thanks in advance.