Optimization of Kubernetes: Resource Allocation and Dynamic Scaling

Kubernetes, a leading container orchestration platform, has become essential for managing modern cloud-native applications due to its scalability, automation, and resource optimization capabilities.This research focuses on Kubernetes' architecture, resource allocation strategies, and autoscaling mechanisms, highlighting key features such as the Horizontal Pod Autoscaler (HPA) and Vertical Pod Autoscaler (VPA).Through an analysis of experimental data and related works, the research underscores the importance of advanced scheduling algorithms, efficient monitoring tools like Prometheus and Grafana, and proactive resource management in improving overall operational efficiency.The findings demonstrate that combining Kubernetes-native features with customized enhancements can significantly reduce latency, resource contention, and operational costs, making Kubernetes a powerful tool for distributed application management.