Containers, in the context of this article, leverage features of the Linux operating system kernel that increase runtime isolation toward other processes on the same machine and operating system with less overhead than full virtual machines. 2 Consequently, there is considerable academic and industrial interest in achieving cost-efficient use of cloud and containerization technologies. The worldwide cloud Infrastructure as a Service (IaaS) market is worth $32.4 billion 1 and containerization penetration is predicted to reach 75% by 2022. Instead, the particularities of the underlying Kubernetes and cloud platform must be taken into account, in particular because their performance can impact that of etcd. The implication of this experience article is that systems researchers studying the performance of applications deployed on Kubernetes cannot simply consider their specific application to be under test.
Finally, it is demonstrated that using high-performance backing storage for etcd can reduce the occurrence of such nondeterministic behaviors by a statistically significant ( P < .05) margin. It also shows that statistical analysis may reveal the data resulting from such experiments to be misleading even when careful preparations are made, and that nondeterministic behavior stemming from etcd can affect both the platform as a whole and the deployed application.
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The article contains (a) detailed descriptions of how networking with and without Istio works in Kubernetes, based on the Flannel Container Networking Interface (CNI) provider in VXLAN mode with IP Virtual Server (IPVS)-backed Kubernetes Services, (b) a comprehensive discussion about how to conduct load and performance testing using a closed-loop workload generator, and (c) an open source experiment framework useful for executing experiments in a shared cloud environment and exploring the resulting data.
This experience article describes lessons learned as we conducted experiments in a Kubernetes-based environment, the most notable of which was that the performance of both the Kubernetes control plane and the deployed application depends strongly and in unexpected ways on the performance of the etcd database.
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