How to deploy large-scale distributed data analytics and machine learning on containers (sponsored by HPE)

Thomas Phelan (HPE BlueData)

14:35–15:15 Wednesday, 16 October 2019

Location: Hilton Meeting Room 3-6

Sponsored

Download slides (PPTX)

AI, ML, and data analytics are transforming every industry. When Gartner recently asked CIOs which technologies are game-changers for their organization, AI and ML are at the very top of the list; data analytics is number two. At the same time, containerization is taking the enterprise by storm-driven by the benefits of greater agility, efficiency, and portability across any infrastructure. By 2022, more than 75% of global organizations will be running containerized applications in production, up from less than 30% today.

As a result, many companies are now exploring whether it is possible to deploy complex distributed data analytics and ML applications (like Cloudera, Spark, Kafka, H2O, and TensorFlow) at scale on containers—with enterprise-grade security and performance in production. Thomas Phelan explains how to make it work.

This session is sponsored by HPE.

Thomas Phelan

HPE BlueData

Thomas Phelan is cofounder and chief architect of BlueData. Previously, a member of the original team at Silicon Graphics that designed and implemented XFS, the first commercially availably 64-bit file system; and an early employee at VMware, a senior staff engineer and a key member of the ESX storage architecture team where he designed and developed the ESX storage I/O load-balancing subsystem and modular pluggable storage architecture as well as led teams working on many key storage initiatives such as the cloud storage gateway and vFlash.