K8sPCM: A Domain-Specific Language for Cloud-Native Performance Modeling Workflows

Kubernetes deployment decisions, such as replica counts and container resource limits, directly influence the performance and hardware cost of cloud-native systems. However, those decisions are normally validated only after actual deployment—essentially, too late. Moreover, the focus of existing tooling, which supports the definition and analysis of Kubernetes deployments is not analysis-ready and more focused on operational visualization. One existing solution here is to do predictive analysis using architecture-level performance models like the Palladio Component Model (PCM). But currently, PCM models can only be constructed from Kubernetes manifests, requiring a level of Palladio expertise beyond most practitioners. In this paper, we present k8sPCM, a ready-to-use Eclipse plugin built on an Xtext-based Domain-Specific Language (DSL). Our DSL mirrors Kubernetes manifest structure and one-click generates a scaffolded PCM instance while also providing content assist, construct templates, and on-the-fly validation. We evaluated the usability of k8sPCM with a user study, in which twelve participants of varying familiarity with Kubernetes and Palladio modeled a TeaStore subset. ... mehrOur results show that k8sPCM achieved a mean System Usability Scale score of 82.5 (i.e., nearly “Excellent” on the Bangor scale); further, we are able to demonstrate that higher Kubernetes familiarity correlated with lower reported mental effort.