InfoQ Homepage Social Networking Content on InfoQ
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Using Technology to Protect against Online Harassment Panel
The panelists discuss the changes society has seen since the advent of social media and how they're building the next generation of software tools to protect against online harassment.
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Canopy: Scalable Distributed Tracing & Analysis @ Facebook
Haozhe Gao and Joe O’Neill present Canopy, Facebook’s performance and efficiency tracing infrastructure. They talk about the lessons learned and present case studies of its use.
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Applied Performance Theory
Kavya Joshi explores the use of performance theory in real systems at companies like Facebook, and discusses how it can be leveraged, to prepare systems for flux and scale.
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Drivetribe: A Social Network on Streams
Aris Koliopoulos talks about how common problems in social media can be resolved with a healthy mix of stream processing and functional programming.
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Continuous Optimization of Microservices Using ML
Ramki Ramakrishna shares Twitter’s recent experience in applying Bayesian optimization to the performance tuning problem, discussing a service used for continuously optimizing microservices.
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Hardware & Provisioning Engineering @Twitter
M. Singer and N. Johnson present the Provisioning Engineering system at Twitter, called Wilson, which together with Audubon is designed to handle every part of a server's lifecycle.
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Scalable Chatbot Architecture with eBay ShopBot
Robert Enyedi discusses the ebay ShopBot, a personal shopping assistant available as a Facebook Messenger bot.
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Building Secure Player Experiences at Riot Games
David Rook talks about the Riot Games Application Security program. He focusses on the tech and social aspects of the program and why he feels both are important when it comes to writing secure code.
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Real-Time & Personalized Notifications @Twitter
Gary Lam and Saurabh Pathak talk about the hybrid push/pull-based architecture adopted by Twitter Notification platform.
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The Rise of Customer Experience Networks Powered by APIs
Stephane Castellani discusses why and how to build a customer experience network.
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Machine Learning at Scale
Aditya Kalro discusses using large-scale data for Machine Learning (ML) research and some of the tools Facebook uses to manage the entire process of training, testing, and deploying ML models.
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Freeing the Whale: How to Fail at Scale
Oliver Gould discusses Finagle, a library providing a uniform model for handling failure at the communications layer, enabling Twitter to fail, safely and often.