InfoQ Homepage Infrastructure Content on InfoQ
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Implementing Software Machines in Go and C
Eleanor McHugh discusses writing virtual machines using hardware emulation, including code snippets in Go and C.
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Fault-Tolerant Sensor Nodes with Erlang/OTP and Arduino
Kenji Rikitake discusses using Erlang/OTP for IoT, covering communication protocols, design principles and overcoming hardware limitations for endpoint devices in fault-tolerant systems.
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How Will Persistent Memory Change Software Design?
Maciej Maciejewski discusses persistent memory, storage devices, and DRAM, accessing persistent memory with ACPI 6.0 extensions, existing support in the Linux kernel and the NVM library.
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Predicting the Future: Surprising Revelations trom Truly Big Data
Pushpraj Shukla discusses how Microsoft Bing predicts the future based on aggregate human behavior using one of the largest scale data sets, and recent progress in large scale deep learnt models.
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Much Faster Networking
David Riddoch talks about the technologies that make high performance networking possible on commodity servers, with a special focus on direct access to the network adapter by bypassing the kernel.
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Netflix Keystone - How We Built a 700B/day Stream Processing Cloud Platform in a Year
Peter Bakas presents in detail how Netflix has used Kafka, Samza, Docker, and Linux to implement a multi-tenant pipeline processing 700B events/day in the Amazon AWS cloud.
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Hunting Criminals with Hybrid Analytics
David Talby demos using Python libraries to build a ML model for fraud detection, scaling it up to billions of events using Spark, and what it took to make the system perform and ready for production.
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Resilient Predictive Data Pipelines
Sid Anand discusses how Agari is applying big data best practices to the problem of securing its customers from email-born threats, presenting a system that leverages big data in the cloud.
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Big-Data Analytics Misconceptions
Irad Ben-Gal discusses Big Data analytics misconceptions, presenting a technology predicting consumer behavior patterns that can be translated into wins, revenue gains, and localized assortments.
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How Comcast Uses Data Science and ML to Improve the Customer Experience
Jan Neumann presents how Comcast uses machine learning and big data processing to facilitate search for users, for capacity planning, and predictive caching.
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Immutable Infrastructure: Rise of the Machine Images
Axel Fontaine looks at what Immutable Infrastructure is and how it affects scaling, logging, sessions, configuration, service discovery and more.
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The Mechanics of Testing Large Data Pipelines
Mathieu Bastian explores the mechanics of unit, integration, data and performance testing for large, complex data workflows, along with the tools for Hadoop, Pig and Spark.
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