The Kubernetes Network Driver Model: A Composable Architecture for High-Performance Networking

TL;DR

This paper presents Kubernetes Network Drivers (KNDs), a modular architecture that enhances high-performance networking for AI/ML and Telco workloads by integrating network resource management into Kubernetes core.

Contribution

It introduces a novel, declarative, and composable network driver model that overcomes limitations of traditional Kubernetes networking and supports high-performance, cloud-native applications.

Findings

DraNet enables declarative attachment of RDMA devices.

Significant performance improvements for AI/ML workloads.

Foundation for future Telco network solutions.

Abstract

Traditional Kubernetes networking struggles to meet the escalating demands of AI/ML and evolving Telco infrastructure. This paper introduces Kubernetes Network Drivers (KNDs), a transformative, modular, and declarative architecture designed to overcome current imperative provisioning and API limitations. KNDs integrate network resource management into Kubernetes' core by utilizing Dynamic Resource Allocation (DRA), Node Resource Interface (NRI) improvements, and upcoming OCI Runtime Specification changes. Our DraNet implementation demonstrates declarative attachment of network interfaces, including Remote Direct Memory Access (RDMA) devices, significantly boosting high-performance AI/ML workloads. This capability enables sophisticated cloud-native applications and lays crucial groundwork for future Telco solutions, fostering a "galaxy" of specialized KNDs for enhanced application delivery and reduced operational complexity.