InfoQ Homepage Infrastructure Content on InfoQ
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High Speed Smart Data Ingest into Hadoop
Oleg Zhurakousky discusses architectural tradeoffs and alternative implementations of real-time high speed data ingest into Hadoop.
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Innovation in the Enterprise: The Intrapreneurs behind the Scene
Debbie Madden discusses the types of attributes intrapreneurs have in common, how one can identify an intrapreneur, and what can be done to impact technical innovation from a human perspective?
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Orchestrating Tasks from the Cloud with Groovy and AWS SWF
Clay McCoy discusses using Groovy’s metaprogramming capabilities and AWS SWF to deal with unreliable remote services, parallelization, scheduling critical timers, and server failures.
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Asgard, the Grails App that Deploys Netflix to the Cloud
Joe Sondow presents how Netflix uses Asgard to deploy code updates and manage resources in the Amazon cloud.
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Making the Internet a Better Place: Scaling AppNexus
Mike Nolet shares lessons learned scaling AppNexus and architectural details of their system processing 30TB/day: Hadoop, DNS built in GSLB and Keepalived, and real-time data streaming built in C.
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VMFest: Wrapping VirtualBox to Speedup Dev and Test Since 2010
Antoni Batchelli introduces VMFest, a PalletOps project used to turn VirtualBox into a lightweight cloud provider, good for developing cloud automation.
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First, Let's Kill All the Product Owners
Tim Berglund shares the vision of an organization without product managers with its implications and boundaries, provoking the listener to take a bold step into that direction.
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Apache Drill - Interactive Query and Analysis at Scale
Michael Hausenblas introduces Apache Drill, a distributed system for interactive analysis of large-scale datasets, including its architecture and typical use cases.
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The Unavoidable Big Bang
Gareth Rushgrove provides reasons for avoiding a big bang release and what to do to make it work in case that’s the only option.
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MySQL Usage of Web Applications with 1 User and 100 Million
Peter Boros discusses a MySQL architecture useful for the majority of projects, backup, online schema changes, reliability and scalability issues, and basics of sharding.
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A Guide to Python Frameworks for Hadoop
Uri Laserson reviews the different available Python frameworks for Hadoop, including a comparison of performance, ease of use/installation, differences in implementation, and other features.
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Evolving Panorama of Data
Rebecca Parsons reviews some of the changes in how data is used and analyzed, looking at how data is used to track violence, and attempts to predict famine and other crises before they happen.
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