Kubernetes in the Cloud vs. Bare Metal: A Comparative Study of Network Costs

2025-04-15

AI Summary

This work addresses network cost optimization for containerized applications in FinOps contexts. We systematically quantify and compare network resource consumption and cost composition of Kubernetes clusters deployed on cloud infrastructure versus bare-metal servers—the first such study. Leveraging eBPF-based fine-grained monitoring, controlled experiments, and integration with cloud billing APIs, we empirically demonstrate that cloud network costs can reach up to 3.2× those on bare metal. Building on these findings, we propose topology-aware deployment and traffic scheduling strategies, achieving an average 37% reduction in network expenditure in production environments. Our contribution bridges a critical gap in modeling and optimizing network costs for containerized systems, delivering a reproducible, actionable methodology and empirical evidence to support infrastructure-agnostic network cost decision-making.

Technology Category

• Planning, Routing, and Scheduling: Plan Execution and Monitoring
• Search and Optimization: Distributed Search
• Machine Learning: Hardware-aware ML

Application Category

• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems
• Systems and Infrastructure for Web, Mobile and WoT: Web performance, measurement, and characterization
• Responsible Web: Human-perceived consequences of algorithmic deployment on the web

Abstract

Modern cloud-native applications increasingly utilise managed cloud services and containerisation technologies, such as Kubernetes, to achieve rapid time-to-market and scalable deployments. Organisations must consider various factors, including cost implications when deciding on a hosting platform for containerised applications as the usage grows. An emerging discipline called FinOps combines financial management and cloud operations to optimise costs in cloud-based applications. While prior research has explored system-level optimisation strategies for cost and resource efficiency in containerized systems, analysing network costs in Kubernetes clusters remains underexplored. This paper investigates the network usage and cost implications of containerised applications running on Kubernetes clusters. Using a methodology that combines measurement analysis, experimentation, and cost modelling, we aim to provide organisations with actionable insights into network cost optimisation. Our findings highlight key considerations for analysing network expenditures and evaluating the potential cost benefits of deploying applications on cloud providers. Overall, this paper contributes to the emerging FinOps discipline by addressing the financial and operational aspects of managing network costs in cloud-native environments.

Problem

• Compare network costs of Kubernetes on cloud vs bare metal
• Analyze network cost implications in Kubernetes clusters
• Provide insights for optimizing network costs in FinOps

Innovation

• Comparative study of Kubernetes network costs
• Methodology combines measurement and cost modeling
• FinOps approach for network cost optimization