Speaker: Seth Katz

Senior Software Engineer, Operational Insights @Netflix

Seth Katz has been responsible for building the insights tooling around Netflix servers for the past 5 years. He has specifically focused on the systems that ensure people can browse and play movies. During that time, he pioneered Netflix's streaming visualization data platforms, our contextual system tracing tools and analytics, and our anomaly systems for detecting and troubleshooting problems on Netflix’s most mission critical servers.

Prior to that he worked at Microsoft and Yahoo on scalable transaction systems.

Talk : How Machines Help Humans Root Cause Issues @Netflix

Track : Practical Machine Learning
Location : Broadway Ballroom South Center, 6th fl.
Duration : 4:10pm - 5:00pm

Automated root cause detection represents a holy grail goal for many systems monitoring tools. It’s also an extremely challenging domain. A successful approach must generalize well from limited examples, handle highly dimensional data, understand the application domain, and perform well in a real time environment where baseline behavior changes over time. Those are all problems humans are good at, but state of the art machine learning approaches often struggle with.   

In this talk, we’ll discuss ways to build tools designed to enhance the cognitive ability of humans through automated analysis to speed root cause detection in distributed systems. We’ll focus on examples from large scale systems at Netflix. In particular, we’ll focus on the systems directly involved in browsing and playing Netflix movies, and how pairing automation with human feedback reduces mean time to detect and resolve issues.

Other talks from track Practical Machine Learning

ML Data Pipelines for Real-Time Fraud Prevention @PayPal
Lead Data Architect, Risk and Compliance Management Platform @PayPal
Mikhail Kourjanski
Machine Learning Open Space
Agile & Software Craftsmanship Coach
Harold Shinsato
From Software Development to ML - A Team's Transformation
PhD in AI and Computational Biology
Golestan Sally Radwan
Engineering Systems for Real-Time Predictions @DoorDash
Engineering systems for real-time predictions @DoorDash
Raghav Ramesh
Deep Learning for Application Performance Optimization
Java and Neural Network Expert, Creator @Neuroph, & Founder @DeepNetts
Zoran Sevarac

Tracks

Schedule