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Groupon recently completed a year-long project to migrate its U.S. web traffic from a monolithic Ruby on Rails application to a new multi-application stack with substantial results. Learn about how Groupon achieved this great architecture migration and the business results it is driving.
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In the last year Docker has taken the DevOps world by storm. Eric will tell you what Docker. is, how it works, and how to add it to your development toolbox
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a new library for ClojureScript called Om, a simple functional layer over Facebook’s React, makes some traditional hard problems in MVC based UIs simple without abandoning the abtractions OO programmers find useful.
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From the abstract: “The game has changed: we write interactive web applications, we distribute the processing of huge data sets and our services need to be available at all times. This new breed of applications comes with its own set of requirements and forces us to establish new blueprints for designing our systems. In this talk we ask the crucial questions along this path, show which answers work and which don’t, and distill the essence of the common theme—Going Reactive.”
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This talk discussed lessons learned by Donn while writing highly successful Android applications hosted on the Google Play store. You’ll learn about how to use RoboElectric, JUnit and Mockito together in your testing regime.
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Neo’s Max DeMarzi talks about a number of use cases for Graph Databases, referencing open source projects.
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In this talk, Hive and Cassandra author (and Hive committer and PMC member) Edward Capriolo will discuss common big-data software challenges and how they can be solved using both batch and stream processing. Technology focus will primarily be on Apache Kafka for publish-subscribe messaging, Storm for stream processing, and Apache Cassandra as a NoSQL data store.
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As Mahout rolls towards a 1.0 release, Mahout committer and co-founder Grant Ingersoll, will provide an overview of what’s happening with the machine learning project and what to look forward to next.
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Predictive modeling is one of the figureheads of big data. Machine Learning Theory asserts that the more data the better, and empirical observations suggest that the more granular data, the better the performance (provided you have modern algorithms and big data) but the paradox of predictive modeling is that when you need models the most, even all the data is not enough.
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Vert.x is an asynchronous, event-driven application platform similar in style to Node.js, except it runs on the JVM. It supports several JVM languages, including Javascript, and uses a multi-reactor event loop to handle a very high number of concurrent connections. Learn about it in this screencast from Data I/O 2013.
