Machine Learning and Better Rails Asset Management

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Three exciting talks in this video: First Ben McRedmond will share his experiences with machine learning and go over some simple concepts (and practical details) which most web developers will benefit from knowing. In the second talk, James Rosen will talk about ways to make it simple for web developers to access front-end libraries at the HTTP layer for a faster and more automated development process. In the third talk Rudy Rigot, from, will share his painful past experiences around manageable content, and will share his critical look on the various ways developers handle it today in their applications. These talks were recorded at the SF Ruby on Rails meetup group at Zendesk.


Bio: Ben McRedmond is the Head of Labs at Intercom. He is working on experimental projects and cool algorithms.

Bio: James Rosen has been User Happiness Engineer at Zendesk for three years and a card-carrying Rubyist for 7, having previously lost his soul to Java. He holds a degree in Information Security from Carnegie Mellon, as well as degrees in Music and Italian Culinary Arts. He prefers his spaghetti all 'arrabbiata and his code non-spaghetti-like.

Bio: Rudy Rigot's mission in life is to solve people's content issues in simple ways. He's the developer evangelist at, working on new ways to approach the issue, and getting feedback from communities about these new approaches. He was previously also a regular speaker and writer in Europe, and is brand new to San Francisco!

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Realtime Data Analytics at Datadog

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Imagine you are tasked with building a platform to monitor the performance of 500,000 servers in real-time. How would you design it? What tools would you choose? (Cassandra? Storm? Spark? HBase? ...) What technical challenges would you expect? As a monitoring company, Datadog receives tens of billions of telemetry data points every day and is working to change the way operations teams understand and troubleshoot their infrastructure and applications. In this talk, Alexis Lê-Quôc from Datadog talks about how they built their (Python-based) low-latency, real-time analytics pipeline. This talk was recorded at the NYC Data Engineering meetup at The Huffington Post.