InfoQ Homepage Scalability Content on InfoQ
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Machine Learning & Recommender Systems at Netflix Scale
Xavier Amatriain discusses the machine learning algorithms and architecture behind Netflix' recommender systems, offline experiments and online A/B testing.
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Grails and the Real-time Web
Stephane Maldini on addressing several issues concerning web applications written with Grails: scrolling large data sets without blocking, streaming to the browser, scale Grails in the cloud, etc.
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Redesigning PayPal APIs for Scale and Simplicity
Deepak Nadig, Praveen Alavilli present how PayPal redesigned its APIs based on lessons learnt developing their services in over 14 years, and the principles, patterns and anti-patterns used.
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Graph Computing at Scale
Matthias Broecheler discusses graph computing, introducing the Aurelius graph cluster enabling graph computing at scale by building on distributed systems like Cassandra, HBase, and Hadoop.
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Growing from the Few to the Many: Scaling the Operations Organization at Facebook
Pedro Canahuati describes how Facebook's operations maintains their infrastructure, including challenges faced and lessons learned: prioritizing calls, managing technical debt, incident management.
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The Magic Behind Enterprise Apps: How to Expose Reliable, Scalable and Secure Enterprise APIs?
Blake Dournaee covers the often forgotten back-end architecture for mobile apps which should expose cross-platform APIs to mitigate some of the effects of mobile O/S fragmentation.
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Grails SOA: Building Distributed Scalable Services with Grails and RabbitMQ
Steve Pember discusses creating Grails applications integrating message broker technologies, especially RabbitMQ, and applying SOA principles.
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Partitions for Everyone!
Kyle Kingsbury discusses some of the limitations found in distributed systems and the way some of them behave under partitioning.
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One to Many: The Story of Sharding at Box
Tamar Bercovici presents Box’s transition from a single MySQL database to a fully sharded MySQL architecture, all the while serving 2 billion queries per day.
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Which Is Easier? 100T-10M or 10M-1B
Zoltan Toth-Czifra shares scalability lessons learned at Softonic, a company that has developed and grew along with the Internet for over 15 years.
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Scaling out with Akka Actors
Joshua Suereth designs a scalable distributed search service with Akka and Scala using actors, and covering practical aspects of how to scale out with Akka’s clustering API.
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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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