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Navigating The Rapids:Real-World Lessons in Adopting Agile
This talk investigates technical issues encountered when moving to an Agile process.
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Codename "M": Language, Data, and Modeling, Oh My!
Don Box and Amanda Laucher present “M”, a declarative language for building data models, domain models or external DSLs. Don Box's demos show some of M’s features and latest changes of the language.
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7 Fundamentals of Mission-Critical Service Testing
Schneider on 7 service testing fundamentals: thoroughly testing, large amounts of realistic data, security testing, high productivity, tracking test results, realistic loads, and proper governing.
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Pragmatic F# in Action
Amanda Laucher and Josh Graham introduce the audience to F# basics showing some of its main features, emphasizing what makes it better than imperative languages, and also showing F# code samples.
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Rails 3
Yehuda Katz explains Rails 3: the performance improvements, the new architecture, the influence of Merb, and much more. Also: a look at the Bundler tool.
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LinkedIn: Network Updates Uncovered
Belkin and Dawson discuss LinkedIn’s requirements, then the internal architecture of the social network, presenting the service API, especially Network Updates, and the applications built on them.
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Facebook’s Petabyte Scale Data Warehouse using Hive and Hadoop
Ashish Thusoo and Namit Jain explain how Facebook manages to deal with analysis of 12 TB of compressed new data everyday with Hive’s help, an open source data warehousing framework built on Hadoop.
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The State and Future of JavaScript
Douglas Crockford talks on the history of JavaScript unveiling some of the struggles the Ecma Technical Committee has had in advancing the language over the years, concluding with lessons learned.
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SOA @ eBay: What Makes It Successful?
Malladi talks about challenges met while implementing large scale SOA deployments, giving eBay as an example of an efficient, extensible and scalable SOA platform with an automated governing process.
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JRuby: You've Got Java in my Ruby
Tom Enebo explains reasons for choosing JRuby: Hotspot optimizations, JVM Garbage Collectors, tools like profilers. Also: how JRuby helps to write cleaner, more expressive code with Java libraries.
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Evolving the Key/Value Programming Model to a Higher Level
Billy Newport discusses the ways that developers interact with key/value stores, entity vs column-oriented approaches, sync vs async operations, large data sets, and collocating closures and data.
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Standards are Great, but Standardisation is a Really Bad Idea
Paul Downey covers the risks of premature standardisation, partial implementations and open extensions, cloud computing lock-in, and formal activities vs lightweight open processes like open source.