InfoQ Homepage Case Study Content on InfoQ
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Deep Learning at Scale
Scott Le Grand describes his work at NVidia, Amazon and Teza, including the DSSTNE distributed deep learning framework.
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Big Data Infrastructure @ LinkedIn
Shirshanka Das describes LinkedIn’s Big Data Infrastructure and its evolution through the years, including details on the motivation and architecture of Gobblin, Pinot and WhereHows.
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Further Together: Curated Pairing Culture @Pivotal
Neha Batra presents her experience with pair programming at Pivotal Labs. They pair program eight hours/day every workday and help enable other companies to practice it with them.
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Stream Processing & Analytics with Flink @Uber
Danny Yuan discusses how Uber builds its next generation of stream processing system to support real-time analytics as well as complex event processing.
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Data Driven Products Now!
Dan McKinley discusses how Etsy is using data to validate their ideas and prototypes, turning some into real products.
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Creating a Kaizen Culture for the Food Bank of New York City
Margarette Purvis shares Food Bank’s kaizen journey of rethinking and improving operations by implementing small incremental improvements across the organization.
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Winston: Helping Netflix Engineers Sleep at Night
Sayli Karmarkar discusses Winston, a monitoring and remediation platform built for Netflix engineers.
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Incident Management at the Edge
Lisa Phillips discusses the typical struggles a company runs into when building around-the-clock incident operations and the things Fastly has put in place to make dealing with incidents easier.
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Data Science in the Cloud @StitchFix
Stefan Krawczyk discusses how StitchFix used the cloud to enable over 80 data scientists to be productive and have easy access, covering prototyping, algorithms used, keeping schema in sync, etc.
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Petabytes Scale Analytics Infrastructure @Netflix
Tom Gianos and Dan Weeks discuss Netflix' overall big data platform architecture, focusing on Storage and Orchestration, and how they use Parquet on AWS S3 as their data warehouse storage layer.
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Automatic Discovery of Service Metadata for Systems at Scale
Martina Iglesias Fernández discusses Spotify’s approach to documentation through automatic discovery of existing endpoints, service configuration, and deployment information at runtime.
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Scaling the Data Infrastructure @Spotify
Mārtiņš Kalvāns and Matti Pehrs overview the Data Infrastructure at Spotify, diving into some of the data infrastructure components, such us Event Delivery, Datamon and Styx.
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