Container-based Cluster Orchestration Systems: A Taxonomy and Future Directions

TL;DR

This paper presents a comprehensive taxonomy of container-based cluster orchestration systems, analyzing their mechanisms, challenges, and future research directions in managing large-scale container deployments.

Contribution

It introduces a detailed taxonomy for classifying orchestration systems and applies it to current solutions, highlighting open challenges and future research opportunities.

Findings

Identifies key mechanisms for scalability and fault-tolerance.

Classifies existing systems based on the proposed taxonomy.

Highlights gaps and future directions in container orchestration research.

Abstract

Containers, enabling lightweight environment and performance isolation, fast and flexible deployment, and fine-grained resource sharing, have gained popularity in better application management and deployment in addition to hardware virtualization. They are being widely used by organizations to deploy their increasingly diverse workloads derived from modern-day applications such as web services, big data, and IoT in either proprietary clusters or private and public cloud data centers. This has led to the emergence of container orchestration platforms, which are designed to manage the deployment of containerized applications in large-scale clusters. These systems are capable of running hundreds of thousands of jobs across thousands of machines. To do so efficiently, they must address several important challenges including scalability, fault-tolerance and availability, efficient resource utilization, and request throughput maximization among others. This paper studies these management systems and proposes a taxonomy that identifies different mechanisms that can be used to meet the aforementioned challenges. The proposed classification is then applied to various state-of-the-art systems leading to the identification of open research challenges and gaps in the literature intended as future directions for researchers.