Robert Kubis
From Google UK
Robert is a Developer Advocate for the Google Cloud Platform based in London specializing in Container, Storage and Scalable technologies. Before joining Google, Robert collected over 10 years of experience in Software Development and Architecture. He has driven multiple full-stack application developments at SAP with a passion for distributed systems, containers and databases. In his spare time he enjoys following tech trends, good restaurants, traveling and improving his photographing skills :)
More info at https://www.linkedin.com/in/kubisrobert
Cloud, Containers & Infrastructure
Spanner - a fully managed horizontally scalable relational database with ACID transactions that speaks SQL
Live coding and demos! In this presentation you'll learn what Spanner is all about! I'll talk about TrueTime, horizontal scale, the CAP theorem and best practices. You'll see how to setup your first Spanner instance and database. We walk through design decisions when coming up with your schema and queries that are enabled to scale to terabytes. Come prepared to see some code, queries and query explains. :D
Big Data & Machine Learning
Google Dataflow: The New Open Model for Batch and Stream Processing
In 2004 Google published the MapReduce paper, a programming model that kick-started big data as we know it. Ten years later, Google introduced Dataflow - a new paradigm, integrating batch and stream processing in one common abstraction. This time the offer was more than a paper, but also an open source Java SDK and a cloud managed service to run it. In 2016 big data players like Cask, Cloudera, Data Artisans, PayPal, Slack, Talend joined Google to propose Dataflow for incubation at the Apache Software Foundation - Dataflow is here, not only unifying batch and streaming, but also the big data world.
In this talk we are going to review Dataflow's differentiating elements and why they matter. We’ll demonstrate Dataflow’s capabilities through a real-time demo with practical insights on how to manage and visualize streams of data.