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Serverless datastream processing by Martin Görner

407 views · Published 8 November 2017 · 30:42 · Indexed 19 October 2026

Channel: Devoxx · 2017 · Science & Technology

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The focus is shifting from big data to fast data. Massively scalable datastream processing infrastructures are the next field of R&D in large internet companies and thankfully, they often open source their latest developments. But setting up and running the infrastructure required to deploy these environments is hard, really hard. However, it is now possible to run datastream processing workloads in the cloud in an entirely serverless fashion and let the cloud provider worry about operations. We will demonstrate in this session how an end-to-end system including message handling, complex datastream processing, persistency, data querying and cleaning as well as machine learning (both training and serving predictions) can be build out of serverless components on Google Cloud Platform. We will use it to power a business running a fleet of connected taxis in NYC. Language: Java

Martin is passionate about science, technology, coding, algorithms and everything in between. He graduated from Mines Paris Tech, enjoyed his first engineering years in the computer architecture group of ST Microlectronics and then spent the next 11 years shaping the nascent eBook market, starting with the Mobipocket startup, which later became the software part of the Amazon Kindle and its mobile variants. He joined Google Developer Relations in 2011 and now focuses on parallel processing and machine learning .

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