InfoQ Homepage Infrastructure Content on InfoQ
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Tumblr - Bits to Gifs
John Bunting talks about different services Tumblr has built and how their architecture helps them be fault tolerant as they continue to grow.
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1.5 Million Log Lines Per Second: Building and Maintaining Flume Flows at Conversant
Mike Keane presents how Conversant migrated to Flume, managing 1000 agents across 4 data centers, processing over 50B log lines per day with peak hourly averages of over 1.5 million log lines/sec.
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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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Continuous Delivery for the Rest of Us
Lisa Van Gelder provides simple tips and tricks for improving delivery without investing lots of time up front creating complex deployment frameworks.
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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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Caching and Messaging Improvements in Spring Framework 4.1
Juergen Hoeller and Stéphane Nicoll present major new features in Spring Framework 4.1: the numerous improvements around the caching abstraction, and messaging-related features.
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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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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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Unleash the Power of HBase Shell
Jayesh Thakrar shows what can be done with irb, how to exploit JRuby-Java integration, and demonstrates how the Shell can be used in Hadoop streaming to perform complex and large volume batch jobs.
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Dashboarding: The Developers’ Role in Data Analysis
Seth Juarez shares insight on how to create applications that use dashboards to drive value, convert raw data into answers, and simplify business processes.