Hybrid Auto-Scaling and Governance for Cloud-Native Applications: Optimizing Resources and Security

With the rapid expansion of Cloud-Native Applications (CNAs), the demand for efficient scaling models and intelligent governance mechanisms has increased significantly. Traditional scaling approaches, including horizontal scaling (adding or removing nodes) and vertical scaling (adjusting resources within a node), offer benefits but also have limitations such as increased latency, inefficient resource utilization, and lack of security compliance. This study introduces a hybrid model that integrates horizontal and vertical scaling while incorporating governance mechanisms to optimize resource management in cloud environments. The proposed framework consists of three key components: (۱) Hybrid Scaling Management, (۲) Real-Time Monitoring & Observability, and (۳) Security & Compliance Enforcement. The model is implemented and tested on AWS Kubernetes (EKS), achieving a ۲.۵-second response time, a ۹۲% increase in resource efficiency, and a ۲۵% reduction in operational costs. Additionally, integrating governance mechanisms has resulted in a ۴۰% decrease in security violations and policy breaches. Despite these advancements, challenges such as improving workload prediction accuracy, reducing monitoring overhead, and extending the model to multi-cloud environments remain. This study highlights how combining hybrid scalability with intelligent governance and real-time observability provides a robust and scalable solution for efficient cloud resource management.

کلیدواژه ها:

Cloud-Native Applications ، Hybrid Scaling ، Cloud Governance ، Kubernetes ، AWS EKS