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Java 9 - The (G1) GC Awakens!
Monica Beckwith talks about G1 pause (young and mixed) composition, G1's remembered sets and collection set and G1's concurrent marking algorithm, providing performance tuning advice.
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The Mechanics of Testing Large Data Pipelines
Mathieu Bastian explores the mechanics of unit, integration, data and performance testing for large, complex data workflows, along with the tools for Hadoop, Pig and Spark.
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Hot Code is Faster Code - Addressing JVM Warm-up
Mark Price explores the life cycle of Java code, and how the JVM evolves the runtime representation of code during program execution, providing tips to make sure Java code runs fast.
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Nordstrom’s 114-year-old Culture in the Tech Era
Sarah Lake Hagan explains what NorDNA is, how they introduced this concept to the Nordstrom Technology teams, and shows concrete examples of how the employees have embraced this culture.
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React Native in Production
Adam Miskiewicz goes beyond the React Native docs and talks about best practices for building responsive and production-ready React Native applications with Redux, Relay, and GraphQL.
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The Case for TypeScript
Mohamed Hegazy provides a guided tour to TypeScript, showing how the language and toolset simplify application-scale JavaScript development.
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Understanding Real-time Conversations on Facebook
Janet Wiener discusses using a data pipeline and graphic visualizations to extract and analyze the Chorus – the aggregated, anonymized voice of the people communicating on Facebook - in real time.
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Engineering for the Long Game
Astrid Atkinson discusses approaches to making sure systems and organizations can support continuous innovation, from breaking systems into microservices to engineering for organizational resilience.
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#LearningIsHorrible, and Other Harsh Realities
Jeffrey Fredrick talks about how human psychology works against successful Agile adoption and that seeking excellence in Agile development requires difficult emotional work.
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DDD and Microservices: At Last, Some Boundaries!
Eric Evans introduces a few strategic design concepts and explains how they apply to development of microservices, as a tool for teams trying to grow large systems more coherently.
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Startup ML: Bootstrapping a Fraud Detection System
Michael Manapat talks about how to choose, train, and evaluate models, how to bridge the gap between training and production systems, and avoiding pitfalls.
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Microservices Antipatterns
Tammer Saleh talks about the mistakes made building microservices, when microservices are appropriate, where to draw the lines between services, performance issues, testing, debugging, failure, etc.
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