Kubernetes and Docker Load Balancing: State-of-the-Art Techniques and Challenges
Keywords:
Load Balancing, Docker Swarm, Kubernetes, ContainersAbstract
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.
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