Presented By O'Reilly and Cloudera
Make Data Work
22–23 May 2017: Training
23–25 May 2017: Tutorials & Conference
London, UK

How to optimally run Cloudera batch data engineering workflows in AWS

Andrei Savu (Cloudera), Philip Langdale (Cloudera)
12:0512:45 Thursday, 25 May 2017
Big data and the Cloud
Location: Capital Suite 13
Level: Intermediate

Who is this presentation for?

  • Cloud administrators, big data administrators, data engineers, business intelligence end users, and Hadoop engineers

Prerequisite knowledge

  • A basic technical understanding of AWS and Cloudera CDH

What you'll learn

  • Learn how to run end-to-end batch data engineering workflows in AWS
  • Understand architectural optimizations for Cloudera components in AWS and the benefits of data engineering managed services


Cloudera Enterprise in the public cloud leverages the scalability of AWS S3, the elasticity of EC2 instances, and the decoupled nature of compute and storage to provide a powerful, integrated batch data engineering experience. Additionally, the cloud as-a-service deployment model gives data engineers greater agility and ease-of-use in managing their workloads. Andrei Savu and Philip Langdale take you through all the ins and outs of successfully running end-to-end batch data engineering workflows in AWS and demonstrate a Cloudera on AWS data engineering workflow with a sample use case.

Topics include:

  • Sample architectures and workflows for batch analytics
  • How Cloudera is optimized for AWS cloud-native infrastructure
  • Recommendations and best practices for running data engineering workloads in AWS
Photo of Andrei Savu

Andrei Savu


Andrei Savu is a software engineer at Cloudera, where he’s working on Cloudera Director, a product that makes Hadoop deployments in cloud environments easy and more reliable for customers.

Photo of Philip Langdale

Philip Langdale


Philip Langdale is the engineering lead for cloud at Cloudera. He joined the company as one of the first engineers building Cloudera Manager and served as an engineering lead for that project until moving to working on cloud products. Previously, Philip worked at VMware, developing various desktop virtualization technologies. Philip holds a bachelor’s degree with honors in electrical engineering from the University of Texas at Austin.