KubeCon + CloudNative North America 2022

Network abstractions are a cornerstone of Kubernetes, interconnecting containers, pods and services, both across the cluster and beyond. Historically this rich functionality often came at the expense of performance. However, recent innovations and new implementations of the Kubernetes Container Network Interface (CNI) have transformed the Kubernetes networking landscape. Some classes of scientific computing workloads are highly network-intensive: sensitive to network performance to a degree that renders them unsuitable for execution in a Kubernetes context. In machine learning, the most demanding distributed training applications are also becoming increasingly network-intensive. The CNIs now available offer different architectures and technologies. Many claim performance advantages over their predecessors. How can we distinguish between them? In this talk we describe the leading CNIs, and use real-world benchmarks to compare and analyze performance for demanding workloads.