# A Comparative Analysis of High Availability for Linux Container Infrastructures
## 6 Discussion  
This study provides valuable information on the performance characteristics of different high-availability solutions for Linux containers. Comparison of different services based on service recovery time, total number of failed calls, data rate, and average call time enables informed decision making when selecting the appropriate high-availability solution for specific use cases. Understanding the strengths and weaknesses of each service can lead to optimal selection, ensuring a reliable and efficient container-based infrastructure. In addition, the study highlights the importance of taking into account not only performance indicators but also the specific requirements and characteristics of each application or service deployed. Different applications may have different resource, scalability, and fault tolerance requirements. Therefore, it is critical for organizations to carefully assess their individual needs before selecting a container platform. As mentioned in Section 2, various studies have attempted to compare container platforms from different perspectives. The scope of the present study was specifically focused on high availability within Linux container infrastructures, which narrowed the parameters evaluated; other comparative studies have investigated various aspects of virtualization, containerization, system performance, and container orchestration. The selection of platforms depends on what a company prioritizes when implementing a container environment. A study by [PERSON] et al. [PERSON] et al. (2018) compares virtualization and containerization, specifically the Linux containers LXC and Docker. From a network perspective, Linux and Docker containers are considered equivalent, but allow for different network configurations. The study found that LXC achieves lower latency than Docker, which may be important for specific use cases. [PERSON] et al. in [PERSON] et al. (2018) compare the performance of containerization and virtual machines in data centers. They evaluate parameters such as CPU performance, file I/O, memory usage, and application behavior in different environments. The findings show that the Linux-based KVM virtualization hypervisor performs better than Docker containers in the tested domains. The study by [PERSON] et al. [PERSON] et al. (2018) evaluates the impact of different container platforms (Docker, LXC, and LXD) when running TCP services. It analyzes the system performance and compares the containers with the native system. The results indicate that performance between containers can vary, and LXD performs better in terms of system performance. The study by [PERSON] et al. [PERSON] et al. (2018) provides a comprehensive comparison of different convergence architectures (Docker, QEMU/KVM, Firecracker, gVisor, and Kata). It analyzes performance metrics such as CPU, RAM, system calls, network, disk storage, and boot time. The results highlight virtualization trade-offs and performance barriers and provide insights for case-specific decision making. In [PERSON] et al. (2018), the authors [PERSON] and [PERSON] focused on comparing container orchestration platforms (Redhat OpenShift, Mesos, Docker Swarm, and Kubernetes). Evaluation considers parameters such as security, deployment, cluster installation, scalability, stability, and learning curve. The findings suggest that Kubernetes has the best scheduling features, Docker Swarm is easy to use, Mesos is suitable for scalable deployments, and OpenShift excels in security. Kubernetes is identified as the most popular tool among the platforms discussed. Each of the above studies provided valuable insight and recommendations based on their specific areas of focus and benchmarks. Likewise, the present study aimed to analyze the performance of different high-availability solutions within a given experimental setup and provide insights into their strengths and weaknesses based on specific performance metrics. The following are the recommendations that have emerged from the measured results.