
Arun Nalpet authored a comprehensive best practices guide for running Apache Spark on Amazon EKS, published in the awslabs/data-on-eks repository. Focusing on deployment reliability and onboarding efficiency, Arun standardized Spark deployment patterns by detailing EKS networking, Karpenter integration, storage strategies, and advanced scheduling with Yunikorn and Volcano. The work leveraged expertise in Kubernetes, cloud computing, and performance optimization, with documentation written in Markdown to ensure clarity and accessibility. By addressing key operational challenges, Arun’s contribution established a robust baseline for Spark workloads on EKS, reducing deployment risk and providing actionable guidance for teams adopting these cloud-native technologies.

July 2025: Delivered a comprehensive Spark on Amazon EKS Best Practices guide for awslabs/data-on-eks, standardizing deployment patterns and guidance across EKS networking, Karpenter usage, storage considerations, and advanced schedulers like Yunikorn and Volcano. The work establishes a baseline for reliable Spark deployments on EKS and reduces onboarding risk for teams deploying Spark workloads.
July 2025: Delivered a comprehensive Spark on Amazon EKS Best Practices guide for awslabs/data-on-eks, standardizing deployment patterns and guidance across EKS networking, Karpenter usage, storage considerations, and advanced schedulers like Yunikorn and Volcano. The work establishes a baseline for reliable Spark deployments on EKS and reduces onboarding risk for teams deploying Spark workloads.
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