Emerging Trends, Techniques and Open Issues of Containerization: A Review

Containerization is revolutionizing the way that many industries operate, provisioning major impact to modern computing technologies because it is extra lightweight, highly portable, energy, resource and storage efficient, cost-effective, performance efficient, and extremely quick during boot up. These often facilitate efficient load balancing, low-level system maintenance, server consolidation (for efficient energy and resource utilization) and replication of instances over geographical locations for better fault tolerance to escalate application reliability. However, some recent literature have addressed various challenges (such as $complex$ networking, $persistent~storage$ facilities, $cross~data$ centers and $multicloud$ supports, $security$ issues, and $lack$ of available, capable container management APIs, etc.) regarding successful container adoption in industries, which might have resulted in a seemingly meager increase in industrial deployments of containerization over the past few years despite bestowing efficient lightweight virtualization. Moreover, a comprehensive overview of containerizations along with their popularity dynamics has still not been found in contemporary literature, which further extends knowledge gap between developers and available technologies. Hence, current study touches upon different technicalities involved in containerization with potential problems and possible solutions along with various important industrial applications to manifest its existing supports and technical hardships. Finally, we have conducted a comprehensive experimental study to compare the performance of VMs, containers and unikernels in terms of CPU utilization, memory footprints, network bandwidth, execution time and technological maturity using standard benchmarks and observed containers to deliver satisfactory performance in almost all aspects, however, are still not free from issues regarding isolation & security, performance stability, lack of available efficient tools for cross-platform support and persistent storage. Unikernels deliver good performance with VM-like isolation but still need to achieve desired technical maturity (in terms of microprocessor stability, process containment, persistent storage, etc.). VMs, on the other hand, are found to provide stable performance throughout, though bigger memory footprints and slower spin up/down remain their biggest weaknesses.