Big Data and Analytics Workloads on Amazon EFS


Big Data and Analytics Workloads on Amazon EFS

Broadcast Date:
June 28, 2018

Level 300 | Service How To
Big data and analytics applications require storage that can scale in capacity and performance to handle workload demands with high throughput to compute nodes coupled with read-after-write consistency and low-latency file operations. Many analytics workloads interact with data via a file interface, rely on file semantics such as file locks, and require the ability to write to portions of a file. Amazon EFS provides the elasticity and agility to scale for analytics workloads. In this technical session, we will dive deep and discuss technical considerations when deploying analytics on EFS, with a focus on SAS Grid, a shared, centrally managed analytics computing environment. We will describe best practices and discuss tips for success.

Learning Objectives:
• Recognize why and when to use Amazon EFS and the economic benefits versus other solutions
• Understand best practices for deploying big data and analytics workloads with Amazon EFS
• Learn tips for a successful Amazon EFS deployment

Suited For: IT Infrastructure Architects, Administrators, and DevOps Professionals who are planning to implement or extend their data analytics workloads on the AWS Cloud

Speaker(s): Darryl Osborne, Storage Specialist, Solutions Architect, AWS; Vince Carreon, Sr. Product Manager, AWS

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