Vehicle-to-Everything-Car Edge Cloud Management with Development, Security, and Operations Automation Framework

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Modern autonomous driving and intelligent transportation systems face critical challenges in managing real-time data processing, network latency, and security threats across distributed vehicular environments. Conventional cloud-centric architectures typically struggle to meet the low-latency and high-reliability requirements of vehicle-to-everything (V2X) applications, particularly in dynamic and resource-constrained edge environments. To address these challenges, this study introduces the V2X-Car Edge Cloud system, which is a cloud-native architecture driven by DevSecOps principles to ensure secure deployment, dynamic resource orchestration, and real-time monitoring across distributed edge nodes. The proposed system integrates multicluster orchestration with Kubernetes, hybrid communication protocols (C-V2X, 5G, and WAVE), and data-fusion pipelines to enhance transparency in artificial intelligence (AI)-driven decision making. A software-in-the-loop simulation environment was implemented to validate AI models, and the SmartX MultiSec framework was integrated into the proposed system to dynamically monitor network traffic flow and security. Experimental evaluations in a virtual driving environment demonstrate the ability of the proposed system to perform automated security updates, continuous performance monitoring, and dynamic resource allocation without manual intervention.