InfoQ Homepage Architecture & Design Content on InfoQ
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The Big Data Imperative: Discovering & Protecting Sensitive Data in Hadoop
Jeremy Stieglitz discusses best practices for a data-centric security , compliance and data governance approach, with a particular focus on two customer use cases.
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How DevOps and the Cloud Changed Google Engineering
Melody Meckfessel explores how Google's engineering teams use CD to build products and scale them, and how their strain of DevOps speeds launches and helps their engineering culture thrive.
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REST Services with RabbitMQ, Spring Integration and Node.JS
The speakers provide insight into design and architectural challenges for creating REST services with Spring Integration with RabbitMQ.
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Inside spring.io: a Production Spring Reference Application
Brian Clozel talks about the newly open-sourced reference application that powers the spring.io site, built with Spring Boot, Spring Framework 4 features, cujoJS, Bower and Gulp.
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Why Spark Is the Next Top (Compute) Model
Dean Wampler argues that Spark/Scala is a better data processing engine than MapReduce/Java because tools inspired by mathematics, such as FP, are ideal tools for working with data.
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Unified Big Data Processing with Apache Spark
Matei Zaharia talks about the latest developments in Spark and shows examples of how it can combine processing algorithms to build rich data pipelines in just a few lines of code.
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Customer Analytics on Hadoop
Bob Kelly presents case studies on how Platfora uses Hadoop to do analytics for several of their customers.
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Experiences Using Grails in a Microservice Architecture
Jeff Beck describes how Grails fits into a larger polyglot architecture and goes through his team's experiences building and maintaining these micro services.
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My Three Ex’s: A Data Science Approach for Applied Machine Learning
Daniel Tunkelang focuses on the data science mindset for successfully applying machine learning to solve problems: express, explain, experiment.
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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.
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Mantis: Netflix's Event Stream Processing System
The authors discuss Netflix's new stream processing system that supports a reactive programming model, allows auto scaling, and is capable of processing millions of messages per second.
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