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Big Data and Analytics Workloads on Amazon EFS


Big Data and Analytics Workloads on Amazon EFS

When: June 28 | 11:00 AM - 11:45 AM PT (2:00 PM - 2:45 PM ET)
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
Who Should Attend: IT Infrastructure Architects, Administrators, and DevOps Professionals who are planning to implement or extend their data analytics workloads on the AWS CloudSpeaker(s): Darryl Osborne, Storage Specialist, Solutions Architect, AWS; Vince Carreon, Sr. Product Manager, AWS

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