Container Orchestration in Multi-Cloud Environments: A Performance Evaluation

Abstract

The emergence of multi-cloud strategies has significantly transformed how enterprises deploy and manage applications, particularly through the use of container orchestration platforms like Kubernetes. This study investigates the performance efficiency of container orchestration in multi-cloud environments by evaluating key parameters such as deployment time, resource utilization, latency, scalability, and fault tolerance. A comparative analysis is conducted using Google Kubernetes Engine (GKE), Amazon Elastic Kubernetes Service (EKS), and Azure Kubernetes Service (AKS), supported by statistical regression and predictive modeling. Results reveal varying degrees of orchestration performance across platforms, with hybrid orchestration strategies offering promising trade-offs between latency and cost-efficiency. The findings provide insights into optimal workload distribution and orchestration techniques for robust cloud-native deployments. Keywords Container Orchestration, Multi-Cloud, Kubernetes, Performance Evaluation, Resource Utilization, Regression Analysis, Predictive Modeling