  Serverless computing has emerged as a very popular cloud technology, together
with its companion Function-as-a-Service (FaaS) programming model enabling
invocations of stateless functions from clients. An evolution of serverless is
now taking place, shifting it towards the edge of the network and broadening
its scope to stateful functions, as well. In this paper we argue that stateless
vs. stateful is not a dichotomy of the application per se, but rather a
time-varying property of most (if not all) applications, as confirmed by the
analysis of real traces collected in a production environment. Based on this
observation, we propose a mathematical formulation of a resource allocation
problem that jointly encompasses both operation modes, dubbed lambda vs. mu,
which can be solved efficiently at run-time by an edge orchestrator. We
evaluate the proposed solution via simulation experiments in realistic network
and workload conditions, which leads the way to the practical realization of a
system where applications can freely adapt their current operation mode and
optimize their performance at a minimum cost of operation from the network's
perspective.
