July 22 | 11:00 AM - 12:00 PM PT
Level 200 | Solutions Best Practices
Data is a core part of every business. As data volumes increase so do costs of processing it. Whether you are running your Apache Spark, Hive, or Presto workloads on-premise or on AWS, Amazon EMR is a sure way to save you money. In this session, we’ll discuss several best practices and new features that enable you to cut your operating costs and save money when processing vast amounts of data using Amazon EMR.
You’ll also hear from Unravel Data on how you can use Unravel APM, a full-stack solution for big data workloads running on Amazon EMR, to get visibility and reporting on your Amazon EMR cluster resource utilization and cost savings.

Learning Objectives
- Learn about the best practices and new features such as Managed Scaling and improved Apache Spark performance to help you optimize and reduce your Amazon EMR costs.
- Watch a demo on how Unravel APM, a full-stack monitoring, tuning, and troubleshooting solution for big data workloads running on Amazon EMR, can help you optimize your Amazon EMR cluster costs.
Speakers
- Roy Hasson, Sr. Manager – Data Lakes, AWS
- Mark Wolfram, VP Business Development & Partnerships, Unravel Data
Intro body copy here about 2018 re:Invent launches.
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