October 25-27, 2017 - Prague, Czech Republic
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Friday, October 27 • 12:00 - 12:50
How We Built a Highly Scalable Machine Learning Platform Using Apache Mesos - Daniel Sârbe, SDL

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Is there a way to combine new architectural patterns such as micro-services with Big Data technologies and run everything in Mesos?

In this talk I will present a novel, highly scalable Machine Learning platform for our Machine Translation use-cases.

I will explain how, in order to reach this goal, we have combined a wide variety of Big Data technologies(like Kafka, HBase, Hadoop), and I will discuss the challenges that we have faced along the way. I will also present how we adopted a containerized micro-services architecture(based on Mesos, Docker, Zookeeper) in order deploy our highly scalable Machine Learning platform.

avatar for Daniel Sârbe

Daniel Sârbe

Development Manager, SDL
Daniel is leading the Big Data and Cloud Machine Translation group at SDL and in the last two years he was involved in building a highly scalable Machine Learning platform using some technologies from the BigData ecosystem like Kafka, HBase, Hadoop HDFS, ELK, Mesos in combination... Read More →

Friday October 27, 2017 12:00 - 12:50 CEST
Congress Hall 1