Downloads: 2 | Views: 215 | Weekly Hits: ⮙1 | Monthly Hits: ⮙2
Research Paper | Information Technology | India | Volume 9 Issue 9, September 2020 | Rating: 4.8 / 10
Latency Optimization for Cross-Region Data Replication in EKS
Babulal Shaik
Abstract: Latency optimization for cross-region data replication in Amazon Elastic Kubernetes Service (EKS) is critical for ensuring efficient and reliable application performance in distributed systems. Organizations often rely on EKS for its scalability and seamless integration with Kubernetes, but cross-region replication presents challenges due to network latencies, bandwidth limitations, and consistency requirements. This paper explores strategies to minimize latency while maintaining data integrity and availability across geographically dispersed regions. Critical approaches include leveraging intelligent replication techniques, such as asynchronous and incremental data synchronization, which reduce the amount of data transferred and mitigate the impact of network latency. Additionally, implementing region-aware traffic routing and prioritizing data transfers for high-priority applications ensures optimal resource allocation. The study also examines the benefits of employing caching mechanisms, data compression, and network optimization tools to enhance performance. Monitoring and observability tools are vital in identifying bottlenecks, enabling dynamic adjustments to replication strategies in real time. Case studies demonstrate how optimizing latency for cross-region replication can significantly improve end-user experience, reduce operational costs, and support compliance with data sovereignty requirements. By integrating these best practices, organizations can enhance the resilience and performance of their EKS-powered applications, ensuring they meet the demands of modern, globally distributed user bases.
Keywords: EKS, Elastic Kubernetes Service, latency optimization, cross-region data replication, AWS, data-intensive workloads
Edition: Volume 9 Issue 9, September 2020,
Pages: 1656 - 1664