Exploring the Performance of Container Runtimes within Kubernetes Clusters

Abstract

The advent of cloud computing, with its Pay-As-You-Go model, has significantly simplified IT maintenance and revolutionized the industry. In the era of Microservices, containerized deployment and Kubernetes orchestration have permeated almost every working domain, drastically reducing the time to market for software releases. Kubernetes utilizes container runtimes to manage Containers, with the Container Runtime Interface (CRI) serving as a communication medium with low-level container runtimes such as runc and kata container. With the deprecation of Dockershim, developers are left to choose between CRI-O and Containerd, two CRI implementations. This study configures a Kubernetes cluster with both Containerd and CRI-O separately and analyzes performance parameters such as throughput, response time, CPU, memory, and network utilization. Additionally, we examine the impact of using runc and kata container runtimes together within the cluster. The study, conducted using a performance script created by JMeter, reveals that different container runtimes cater to distinct business use-cases and can complement each other when used together in a cluster environment. High compute applications are best run using runc, while high-security requirements are fulfilled by kata. The study provides a comprehensive performance comparison between Containerd and CRI-O, shedding light on the depth and versatility of container runtimes.