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Presentation: High Performance Cooperative Distributed Systems in Adtech

Track: High-Performance Computing: Lessons from FinTech & AdTech

Location: Soho Complex, 7th fl.

Duration: 2:55pm - 3:45pm

Day of week: Wednesday

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Typical large Adtech platforms handle 99th percentile response latency under 10ms and throughput in millions of requests per second while generating TBs of logs per day. Detection of invalid traffic  (fabricated by bots) is fraught with many of the same engineering challenges to satisfy similar low-latency and high-throughput requirements.  While an Adtech platform aspires to maximize ad relevancy, the goal of fraud detection is to minimize such invalid traffic. By design, both types of platforms are high-performance distributed systems that must cooperate to be successful.  

In this talk, we will explore a set of core building blocks exhibited by Adtech platforms and apply them towards building a fraud detection platform. Our claim is by leveraging Cloud and OSS we can drastically reduce the time to production and infrastructure cost.  Thus, bare-metal and proprietary software should no longer be deemed a barrier of entry.  

After addressing performance, we will touch on the key attributes of system reliability and quality in an Adtech system. We will conclude with many insights learned from building one of the leading fraud detection platforms from the ground up.

Speaker: Stan Rosenberg

VP of Engineering @Forensiq

Stan Rosenberg is a passionate software engineer, leader and scientist; he holds a Ph.D. in Computer Science from Stevens Institute of Technology.  He currently heads up engineering at Forensiq--a leading fraud detection platform for online advertising.  Prior to Forensiq, he built distributed platforms for startups.  His Ph.D. dissertation explored formal methods of software verification by leveraging "local reasoning" in conjunction with decision procedures.  Stan revels in all challenges at the intersection of software engineering, research and leadership.

Find Stan Rosenberg at


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