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.
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.
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.
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