InfoQ Homepage Performance & Scalability Content on InfoQ
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Delivering Performance Under Schedule and Resource Pressure: Lessons Learned at Google and Microsoft
Ivan Filho shares lessons learned during the development and release of several large scale services at Microsoft and Google from the perspective of a performance manager.
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Everything I Learned About Scaling Online Games I Learned at Google and eBay: Scalability at KIXEYE
Randy Shoup shares war stories from eBay and Google about performance, consistency, iterative development, and autoscaling, connecting them with experiences building KIXEYE's gaming platform.
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Scaling Pinterest
Details on Pinterest's architeture, its systems -Pinball, Frontdoor-, and stack - MongoDB, Cassandra, Memcache, Redis, Flume, Kafka, EMR, Qubole, Redshift, Python, Java, Go, Nutcracker, Puppet, etc.
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Evolution of the Netflix API
Ben Christensen describes Netflix API's evolution to a web service platform serving all devices and users, the challenges met in operations, deployment, performance, fault-tolerance, and innovation.
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How a Small Team Scales Instagram
Mike Krieger discusses Instagram's best and worst infrastructure decisions, building and deploying scalable and extensible services.
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Deploying Machine Learning and Data Science at Scale
Nick Kolegraff discusses common problems and architecture to support all the phases of data science and how to start a data science initiative, sharing lessons from Accenture, Best Buy, and Rackspace.
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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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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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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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You Can Improve Scalability over 10 Years
Marton Anka shares lessons learned and technical details scaling LogMeIn over a decade.