A comparative analysis of log management solutions: ELK stack versus PLG stack

Abstract: Managing and analyzing large volumes of logs can be challenging, and a log management solution can effectively address this issue. However, selecting the right log management solution can be a daunting task, considering various factors such as desired features and the solution's efficiency in terms of storage and resource usage. This thesis addressed the problem of choosing between two log management solutions: ELK and PLG. We compared their tailing agents, log storage and visualization capabilities to provide an analysis of their pros and cons. To compare the two log management solutions we conducted two types of evaluations: performance and functional evaluation. Together these two evaluations provide a comprehensive picture of each tool's capabilities. The study found that PLG is more resource-efficient in terms of CPU and memory compared to ELK, and requires less disk space to store logs. ELK, however, performs better in terms of query request time. ELK has a more user-friendly interface and requires minimal configuration, while PLG requires more configuration but provides more control for experienced users. With this study, we hope to provide organizations and individuals with a summary of the pros and cons of ELK and PLG that can help when choosing a log management solution.