  Time predictable edge cloud is seen as the answer for many arising needs in
Industry 4.0 environments, since it is able to provide flexible, modular, and
reconfigurable services with low latency and reduced costs. Orchestration
systems are becoming the core component of clouds since they take decisions on
the placement and lifecycle of software components. Current solutions start
introducing real-time containers support for time predictability; however,
these approaches lack of determinism as well as support for workloads requiring
multiple levels of assurance/criticality.
  In this paper, we present k4.0s, an orchestration model for real-time and
mixed-criticality environments, which includes timeliness, criticality and
network requirements. The model leverages new abstractions for both node and
jobs, e.g., node assurance, and requires novel monitoring strategies. We sketch
an implementation of the proposal based on Kubernetes, and present an
experimentation motivating the need for node assurance levels and adequate
monitoring.
