InfoQ Homepage Performance 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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Reactive & Asynchronous - Adventures with APIs in Financial Trading
Michael Barker discusses several low-latency APIs used for financial trading, what makes them fast and how they compare to HTTP/REST/JSON/XML APIs.
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Performance and Search
Dan Luu discusses how to estimate performance using back of the envelope calculations that can be done in minutes or hours, even for applications that take months or years to implement.
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Scaling up Near Real-Time Analytics @Uber &LinkedIn
Chinmay Soman and Yi Pan discuss how Uber and LinkedIn use Apache Samza, Calcite and Pinot along with the analytics platform AthenaX to transform data to make it available for querying in minutes.
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ScyllaDB: Achieving No-Compromise Performance
Avi Kivity discusses ScyllaDB, the many necessary design decisions, from the programming language and programming model through low-level details and up to the advanced cache design, and more.
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Speedup Your Java Apps with Hardware Counters
Sergey Kuksenko discusses how Performance Monitoring Unit works, what Hardware Counters are, which tools have friendship with Java and how to use HWC for speeding up our Java applications.
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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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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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Keep Calm and Carry on: Scaling Your Org
Charity Majors talks about what it means to do quality operations and software engineering in the year 2016 and beyond, as well as the implications for engineering teams and social systems.
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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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Scaling Counting Infrastructure @Quora
Chun-Ho Hung and Nikhil Garg discuss Quanta, Quora's counting system powering their high-volume near-real-time analytics, describing the architecture, design goals, constraints, and choices made.
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Scaling Quality on Quora Using Machine Learning
Nikhil Garg talks about the various Machine Learning problems that are important for Quora to solve in order to keep the quality high at such a massive scale.
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