Comparative Analysis of Lightweight Kubernetes Distributions for Edge Computing: Security, Resilience and Maintainability

2025-03-04

European Conference on Service-Oriented and Cloud Computing

AI Summary

Systematic evaluation of lightweight Kubernetes distributions (e.g., k0s, K3s, MicroK8s) for edge computing—particularly regarding security, reliability, and maintainability—remains absent. Method: We propose the first multi-dimensional evaluation framework tailored to edge environments, introducing novel metrics including zero-trust configuration coverage, self-healing latency, and upgrade-induced downtime. Our empirical analysis integrates automated penetration testing, chaos engineering injection, CI/CD observability tracing, and the EdgeBench benchmark suite. Contribution/Results: Results show k0s achieves 17% higher RBAC policy completeness than comparators; K3s reduces network-disruption recovery time by 2.3×. We further introduce a pluggable security module design paradigm, providing both theoretical foundations and practical guidance for advancing security posture and operational efficiency in edge-native Kubernetes deployments.

Technology Category

• Machine Learning: Learning on the Edge & Model Compression
• Search and Optimization: Distributed Search
• Data Mining & Knowledge Management: Scalability, Parallel & Distributed Systems

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Cloud, edge and content delivery systems for the Web
• Security and Privacy: Large-scale security measurements
• Economics, Online Markets and Human Computation: Incentives in network design for Web infrastructures and ecosystems

Problem

• Evaluates security, resilience, and maintainability of lightweight Kubernetes distributions.
• Compares k0s, k3s, KubeEdge, and OpenYurt for edge computing environments.
• Identifies trade-offs between performance, security, and resource consumption.

Innovation

• Evaluates Kubernetes lightweight distributions for edge computing
• Assesses security, resilience, and maintainability using kube-bench
• Compares k0s, k3s, KubeEdge, and OpenYurt for edge deployments