  Kubernetes is a container management system that has many automated
functionalities. Those functionalities are managed by configuring objects and
resources in the control plane. Since most objects change their state depending
on other objects' states, a change propagates to other objects in a chain. As
cluster availability is influenced by the time required for these cascading
changes, it is essential to make the propagations measurable and shed light on
the behavior of the Kubernetes control plane. However, it is not easy because
each object constantly monitors other objects' status and acts autonomously in
response to their changes to play its role. In this paper, we propose a
measurement system that outputs objects' change logs published from the API
server in the control plane and assists in analyzing the time of cascading
changes between objects by utilizing the relationships among resources. With a
practical change scenario, our system is confirmed that it can measure change
propagation times within a cascading change. Also, measurements on the system
itself showed it has a small CPU and memory footprint.
