InfoQ Homepage QCon San Francisco 2016 Content on InfoQ
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Social Coding for Effective Teams and Products
Phil Haack discusses the secret ingredient to great teams and products, usually misnamed "soft" skills, and how they help teams be more effective, backing all of it with hard data.
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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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Better Tests, Less Code: Property-Based Testing
Matt Bachmann presents a few patterns meant to inspire developers to get started with Property-based Testing.
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Creating a Collaborative Culture between Dev & Ops
Pedro Canahuati discusses some of the ways the Production Engineering (PE) team at Facebook has worked on building a collaborative culture between the software and operations teams.
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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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Fundamentals of Stream Processing with Apache Beam
Frances Perry and Tyler Akidau discuss Apache Beam, out-of-order stream processing, and how Beam’s tools for reasoning simplify complex tasks.
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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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Is Managing Men & Women Really That Different?
Mitch Shepard’s presentation combines cutting-edge gender research and practical strategies for being exceptional leaders to diverse talent.
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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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Elastic Data Analytics Platform @Datadog
Doug Daniels discusses the cloud-based platform they have built at DataDog and how it differs from a traditional datacenter-based analytics stack, pros and cons and the tooling built.
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Architecting for Failure in a Containerized World
Tom Faulhaber discusses the new container-based toolbox for building systems that are robust in the face of failures, how to recover from failure and how the tools can be used to best effect.
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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.