Sep 23–26, 2019
Arun Kejariwal

Arun Kejariwal
Lead Engineer, Facebook

@arun_kejariwal

Until recently, Arun Kejariwal was a statistical learning principal at Machine Zone (MZ), where he led a team of top-tier researchers and worked on research and development of novel techniques for install and click fraud detection and assessing the efficacy of TV campaigns and optimization of marketing campaigns. In addition, his team built novel methods for bot detection, intrusion detection, and real-time anomaly detection. Previously, Arun worked at Twitter, where he developed and open-sourced techniques for anomaly detection and breakout detection. His research includes the development of practical and statistically rigorous techniques and methodologies to deliver high-performance, availability, and scalability in large-scale distributed clusters. Some of the techniques he helped develop have been presented at international conferences and published in peer-reviewed journals.

Sessions

9:00am12:30pm Tuesday, September 24, 2019
Location: 1E 09
Secondary topics:  Cloud Platforms and SaaS, Data, Analytics, and AI Architecture, Streaming and IoT, Temporal data and time-series analytics
Arun Kejariwal (Facebook), Karthik Ramasamy (Streamlio)
In this tutorial, we shall walk the audience through the landscape of streaming systems and overview the inception and growth of the serverless paradigm. Next, we shall present a deep dive of Apache Pulsar which provides native serverless support in the form of Pulsar functions and paint a bird’s eye view of the application domains where Pulsar functions can be leveraged. Read more.

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