  In FaaS, users invoke remote functions, which encapsulate service(s). These
functions typically need to remotely access a persistent state via external
services: this makes the paradigm less attractive in edge systems, especially
for IoT applications, due to the increased delay and outbound traffic. We
propose to generalize the FaaS paradigm by allowing functions to alternate
between remote-state and local-state phases, depending on internal and external
conditions, and dedicating a container with persistent memory to functions when
in a local-state phase. We present initial results showing that this simple yet
powerful pattern allows to better utilize the available resources, which are
scarce on edge nodes, while significantly reducing tail latencies, which is key
to enable many new applications based on real-time ML, e.g., in smart vehicles
and smart factory scenarios
