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Cloud computing has radically changed the way organisations operate theirsoftware by allowing them to achieve high availability of services ataffordable cost. Containerized microservices is an enabling technology for thischange, and advanced container orchestration platforms such as Kubernetes areused for service management. Despite the flourishing ecosystem of monitoringtools for such orchestration platforms, service management is still mainly amanual effort.  The modeling of cloud computing systems is an essential step towardsautomatic management, but the modeling of cloud systems of such complexityremains challenging and, as yet, unaddressed. In fact modeling resourceconsumption will be a key to comparing the outcome of possible deploymentscenarios. This paper considers how to derive resource models for cloud systemsempirically. We do so based on models of deployed services in a formal modelinglanguage with explicit CPU and memory resources; once the adherence to the realsystem is good enough, formal properties can be verified in the model.  Targeting a likely microservices application, we present a model ofKubernetes developed in Real-Time ABS. We report on leveraging data collectedempirically from small deployments to simulate the execution of higherintensity scenarios on larger deployments. We discuss the challenges andlimitations that arise from this approach, and identify constraints under whichwe obtain satisfactory accuracy.

Predicting Resource Consumption of Kubernetes Container Systems using Resource Models