Kubernetes and Docker Load Balancing: State-of-the-Art Techniques and Challenges

Abstract

In the ever-evolving landscape of  container orchestration, Kubernetes stands out as a  leading platform, empowering organizations to deploy,  scale, and manage containerized applications seamlessly.  This survey paper explores the critical domain of load  balancing within Kubernetes, investigating state-of-the art techniques and the associated challenges. Container based virtualization has revolutionized cloud computing,  and Kubernetes, as a key orchestrator, plays a central role  in optimizing resource allocation, scalability, and  application performance. Load balancing, a fundamental  aspect of distributed systems, becomes paramount in  ensuring efficient utilization of resources and maintaining  high availability. The study focuses on contemporary  methods for achieving effect-ive load balancing on  containers, with a specific examination of Docker Swarm  and Kubernetes—prominent systems for container  deployment and management. The paper illustrates how  Docker Swarm and Kubernetes can leverage load bal ancing techniques to optimize traffic distribution. Load  balancing algorithms are introduced and implemented in  both Docker and Kubernetes, and their outcomes are  systematically compared. The paper concludes by  highlighting why Kuber-netes is often the preferred  choice over Docker Swarm for load balancing pur poses.This paper provides a comprehensive overview of  the current state-of-the-art techniques employed in  Kubernetes load balancing. Challenges inherent to  Docker load balancing are addressed, encompassing is sues related to the dynamic nature of containerized  workloads, varying application demands, and the need for  real-time adaptability. The survey also explores the role  of load balancing in enhancing the scalability and overall  performance of applications within Kubernetes clusters. In conclusion, this survey consolidates the current  knowledge on Docker and Kubernetes load balancing,  offering a state-of-the-art analysis while identifying  challenges that pave the way for future research and  advancements in the realm of container orchestration and  distributed systems.