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What Google Learned about Creating Effective Teams
Matt Sakaguchi talks about some of the practical research Google has done around building effective teams, along with key insights from the Pilot program at Google.
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A Series of Unfortunate Container Events @Netflix
Amit Joshi and Andrew Spyker talk about Project Titus, Netflix's container runtime on top of Amazon EC2.
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Streaming for Personalization Datasets at Netflix
Shriya Arora discusses challenges faced with stream processing unbounded datasets, comparing microbatch with event-based approaches using Spark and Flink.
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Refactoring Organizations - A Netflix Study
Josh Evans uses Netflix as a case study to illustrate how specific strategies, framed as technical analogs, have been employed to maximize engineering agility, velocity, and impact.
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BLESS: Better Security and Ops for SSH Access
Bryan Payne talks about BLESS in general: what it is, how it works, and how we can start using it. He explores the Netflix BLESS production architecture and how other companies have used BLESS.
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In Depth TensorFlow
Illia Polosukhin keynotes on TensorFlow, introducing it and presenting the components and concepts it is built upon.
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Panel: What's Next for Our Programming Languages?
Martin Thompson asks the hard questions on choices made and moderates the discussion between the people behind some of the largest and most innovative languages in use by developers today.
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Thinking Strategically about IoT
Holly Cummins talks about the big picture of IoT and whether embedded devices are relevant to business. Cummins demos using an embedded device with MQTT and a Java toolkit for MQTT.
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Hybrid Code-Gen: Designing Cloud Service Client Libraries
Jon Skeet discusses using hybrid code generating to create cloud client libraries in a way that does not affect the future evolution of a service API.
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High Performance Managed Languages
Martin Thompson explores how their managed runtimes can equal, and even better in some cases, the performance of native languages.
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Straggler Free Data Processing in Cloud Dataflow
Eugene Kirpichov describes the theory and practice behind Cloud Dataflow's approach to straggler elimination, and the associated non-obvious challenges, benefits, and implications of the technique.
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