48:50
Scaling Uber's Real-time Market Platform
Matt Ranney explains the Uber architecture overall, with a focus on the dispatch systems, the geospatial index, handling failure, and dealing with the distributed traveling salesman problem.
01:09:10
IoT Realized - The Connected Car
This session explores the power of Spring XD in the context of the Internet of Things (IoT).
35:16
Better Together - Using Spark and Redshift to Combine Your Data with Public Datasets
Eugene Mandel discusses challenges of conforming data sources and compares processing stacks: Hadoop+Redshift vs Spark, showing how the technology drives the way the problem is modeled.
51:34
Scalability Lessons from eBay, Google, and Real-time Games
Randy Shoup tells war stories from Google and eBay focusing on how to scale code, infrastructure, performance, and operations, along with hard-won lessons learned in scaling them.
01:03:55
Scalable Big Data Stream Processing with Storm and Groovy
Eugene Dvorkin provides an introduction to Storm framework, explains how to build real-time applications on top of Storm with Groovy, how to process data from Twitter in real-time, etc.
53:49
Applications of Enterprise Integration Patterns to Near Real-Time Radar Data Processing
Garrett Wampole describes an experimental methodology of applying Enterprise Integration Patterns to the near real-time processing of surveillance radar data, developed by MITRE.
49:40
Samza in LinkedIn: How LinkedIn Processes Billions of Events Everyday in Real-time
Neha Narkhede of Kafka fame shares the experience of building LinkedIn's powerful and efficient data pipeline infrastructure around Apache Kafka and Samza to process billions of events every day.
43:53
My Mobile App Only Works on My Phone? How to Scale Enterprise Mobile Apps
The authors discuss patterns and technologies needed to scale large enterprise mobile systems, covering handling network connectivity, data reliability and real-time communication.
56:02
Real-Time Systems at Twitter
Brian Degenhardt discusses lessons that Twitter learned managing a high rate of change and complexity, and how those can be applied anywhere.
36:18
Building Real-time Web Applications with Stratified JavaScript
Alexander Fritze shows how to build real-time web app with Conductance, a web app server built on Stratified JavaScript which includes support for modularity and composability of asynchronous code.
43:05
Design Patterns for Large-Scale Real-Time Learning
Sean Owen provides examples of operational analytics projects, presenting a reference architecture and algorithm design choices for a successful implementation based on his experience Oryx/Cloudera.
44:45
From The Lab To The Factory: Building A Production Machine Learning Infrastructure
Josh Wills discusses using Hadoop technologies to build real-time data analysis models with a focus on strategies for data integration, large-scale machine learning, and experimentation.
