Abstract

Deploying applications using Kubernetes has become a standard practice in modern cloud-native environments. However, these deployments are frequently hindered by misconfigurations, security vulnerabilities, and operational instability, all of which can significantly affect overall system reliability and security. This paper investigates the application of kube-score, an open-source static code analysis tool specifically designed for evaluating the quality and robustness of Kubernetes object definitions. We systematically examine the key features of kube-score, highlighting its ability to detect configuration errors and provide actionable, context-aware recommendations that enhance both the security posture and operational resilience of Kubernetes workloads. In addition, we review alternative approaches to Kubernetes configuration analysis, positioning kube-score in terms of usability, integration flexibility, and effectiveness. The paper further discusses deployment models for kube-score, including its use as a containerized service within CI/CD pipelines and as a standalone plugin for local development. Through a detailed case study, we demonstrate how integrating kube-score into existing DevOps workflows enables teams to identify and remediate potential issues early in the development lifecycle, thereby reducing risk and promoting best practices. Our findings underscore the practical benefits of automated static analysis in supporting secure, stable, and efficient Kubernetes operations.