InfoQ Homepage Infrastructure Content on InfoQ
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How Facebook Scales Big Data Systems
Jeff Johnson introduces Apollo, a hierarchical NoSQL data system meant to deal with Facebook's distributed storage needs.
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Migrating to Cloud Native with Microservices
Adrian Cockcroft discusses strategies, patterns and pathways to perform a gradual migration towards modern enterprise applications based on cloud, microservices and denormalized NoSQL databases.
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Wix Architecture at Scale
Aviran Mordo introduces Wix's architecture, a highly available eventually consistent system, along with patterns for rendering many websites with a relatively small number of servers.
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Mobile Web Performance - Getting & Staying Fast!
Andy Davies, Aaron Peters present how networks, browsers and the way sites are built affect user experience, and take a look at some of the latest techniques for measuring and improving performance.
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Analyzing Big Data On The Fly
Shawn Gandhi overviews real-time processing use cases, and how developers are using AWS Kinesis to shift from a traditional batch-oriented approach to a continual real-time data processing model.
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Mapping Etsy's Front-end
Daniel Espeset talks about how Etsy built an incremental compiler for the JavaScript modules, and used it to see how static assets are compiled, being deployed, and loaded.
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How WebMD Maintains Operational Flexibility with NoSQL
Rajeev Borborah, Matthew Wilson discuss using NoSQL at WebMD -architecture, benefits, roadmap-, with details on caching and key-value storage implementation behind a few of the WebMD applications.
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Deployed in 60 Minutes: Increasing Production Deployments from Six Months to Every Hour
Sponsored by Twilio. Matt Makai explores why deployments are difficult and shows solutions with case studies on how other organizations cut their production deployment times down from months to hours.
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The Game of Big Data: Scalable, Reliable Analytics Infrastructure at KIXEYE
Randy Shoup describes KIXEYE's analytics infrastructure from Kafka queues through Hadoop 2 to Hive and Redshift, built for flexibility, experimentation, iteration, testability, and reliability.
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Doing Data Science with F#
Tomas Petricek introduces F#’s capabilities in dealing with scientific data: type providers -CSV, XML, JSON, REST-, interactive development, data visualization libraries, integration with R or MathLab
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Canonical Models for API Interoperability
Ted Epstein shows how a shared canonical model can make life easier for API consumers, while still allowing the flexibility to expose different services, with different contextual requirements.
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The Next Wave of SQL-on-Hadoop: The Hadoop Data Warehouse
Marcel Kornacker presents a case study of an EDW built on Impala running on 45 nodes, reducing processing time from hours to seconds and consolidating multiple data sets into one single view.
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