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Counting is Hard: Probabilistic Algorithms for View Counting at Reddit
Krishnan Chandra explains the challenges of building a view counting system at scale, and how Reddit used probabilistic counting algorithms to make scaling easier.
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Developing Data and ML Pipelines at Stitch Fix
Jeff Magnusson discusses thoughts and guidelines on how Stitch Fix develops, schedules, and maintains their data and ML pipelines.
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Building a Reliable Cloud-Based Bank in Java
Jason Maude talks about the server-side implementation of Starling Bank and shows how, even though Java is over two decades old, it can still be used for cutting edge applications.
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Attack Trees, Security Modeling for Agile Teams
Michael Brunton-Spall talks about Attack Trees, a new way of understanding how a system might be attacked and how to prioritize security measures to be implemented.
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Counterfactual Evaluation of Machine Learning Models
Michael Manapat discusses how Stripe evaluates and trains their machine learning models to fight fraud.
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Machine Learning Pipeline for Real-Time Forecasting @Uber Marketplace
Chong Sun and Danny Yuan discuss how Uber is using ML to improve their forecasting models, the architecture of their ML platform, and lessons learned running it in production.
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Security Champions: Only You Can Prevent File Forgery
Marisa Fagan discusses how to become a Security Champion in five steps, what the benefits are, and what to do when there is no Security Champions program or even a Product Security program.
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EternalBlue: Exploit Analysis and beyond
Emma McCall talks about the EternalBlue exploit that was leaked in early 2017 which was then abused to great effect throughout the year.
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Bigger, Faster and More Secure
Laura Bell talks about how security can look when it stops being about fear and starts being a tool for building systems of the future.
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Encryption without Magic, Risk Management without Pain
Anastasiia Voitova talks about cryptography in a wider context: how it helps to narrow more significant risks to controlled attack surfaces, enables managing the risk efficiently & elegantly, and more
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Streaming Reactive Systems & Data Pipes w. Squbs
Anil Gursel and Akara Sucharitakul focus on modeling and building software that considers all input and all output as stream of events, and introducing Squbs.
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Streaming SQL Foundations: Why I ❤ Streams+Tables
Tyler Akidau explores the relationship between the Beam Model and stream & table theory and explains what is required to provide robust stream processing support in SQL.
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