# A Comparative Analysis of High Availability for Linux Container Infrastructures
## 2 Related Work  
There are diverse studies and research on the issue of analyzing the performance of virtualization and containerization technologies from different perspectives. For example, a comparison between virtualization and containers is addressed in a study by [PERSON] et al. [10]. In addition to virtualization, it also compares two leading container platforms, Linux containers (LXC) and Docker, and highlights their advantages and disadvantages. Linux containers are more OS-centric and present an efficient method of creating and managing multiple OSs on a single device; Docker enables containerization through application containers, making it a suitable choice for systems hosting numerous applications due to its robust orchestration support. The study states that from a networking perspective, Linux containers and Docker are equivalent, with each allowing different network configurations. In an experiment, the authors found that LXC achieves lower latency than Docker, which could be important for choosing a more suitable container platform based on specific needs and requirements. The results of the experimental analysis in the study by [PERSON] et al. [11] focus on comparing the performance of containerization and virtual machines in data centers. Although cloud computing may be slightly slower compared to on-premises environments, its benefits are unquestionable. Researchers focus on the performance and security of applications in containerized and virtual environments, testing parameters such as CPU performance, file 1/O, and memory utilization. In addition, they examine the behavior of applications loaded with HTTP data from different sites to compare performance on both these types of environments. Overall, the findings confirm that the Linux-based KVM virtualization hypervisor provides a better performance than Docker containers in these tested areas. Virtualization and containerization have become key tools within datacenters, contributing to more efficient resource utilization and bringing many other benefits. With the growing trend of microservices and DevOps, containerization is starting to gain popularity, and it is important to understand and compare the performance of these technologies. [PERSON] et al. in [12] focused on evaluating the impact of different container platforms (Docker, LXC, and LXD) when running different TCP services. They analyzed the system performance of each container and compared it with a native system without container solutions. The purpose of the research was to provide comprehensive performance metrics to compare container platforms. The results indicate that the performance between containers can vary. The authors found that LXD performs better in terms of system performance. They also observed that server performance results vary depending on what specific service was being evaluated. [PERSON] et al. in [13] addressed a comprehensive comparison of different convergence architectures. They investigated the characteristics of container solutions such as Docker, QEMU/KVM, Firecracker, gVisor, and Kata to identify limitations and the most suitable use cases. As part of the measurements, they analyzed the performance of CPU, RAM, system calls, network, disk storage, and startup time. They also evaluated their performance when running the Nginx web server and the MySQL database management system. On the basis of the benchmark tests, they analyzed the results, discussed the advantages and disadvantages of each architecture, and identified potential limitations. The results of the analysis showed various trade-offs and performance barriers to virtualization, providing insights for making decisions about the use of each technology in specific cases. They alsooutlined a direction for future research, which should focus on optimizing the memory footprint of lightweight hypervisor containers and on leveraging other technologies such as Xen with customized unikernels and the Kubernetes KubeVirt superstructure.