Kubernetes Configuration Defect

Kubernetes is a tool that facilitates rapid deployment of software. Unfortunately, configuring Kubernetes is prone to errors.Configuration defects are not uncommon and can result in serious consequences. This paper reports an empirical study aboutconfiguration defects in Kubernetes with the goal of helping practitioners detect and prevent these defects. We study 719 defects thatwe extract from 2,260 Kubernetes configuration scripts using open source repositories. Using qualitative analysis, we identify 15categories of defects. We find 8 publicly available static analysis tools to be capable of detecting 8 of the 15 defect categories. We findthat the highest precision and recall of those tools are for defects related to data fields. We develop a linter to detect two categories ofdefects that cause serious consequences, which none of the studied tools are able to detect. Our linter revealed 26previously-unknown defects that have been confirmed by practitioners, 19 of which have already been fixed. We conclude our paper byproviding recommendations on how defect detection and repair techniques can be used for Kubernetes configuration scripts. Thedatasets and source code used for the paper are publicly available online.