Data powering frequent updates of Netflix's video player
Who is this presentation for?Data engineers, data architects, developers
Among the Netflix streaming video player team’s top operational risks is the deployment process. The team’s application runs on machines they don’t control, unlike the server applications, which results in unique challenges. This means there are opportunities to reduce friction, improve velocity, and the release and rollback decision. To meet these opportunities, the team has invested in solutions to enable real-time metrics derived from thousands of player events sent every second and run analyses to detect shifts.
Minal Mishra walks you through Netflix’s video player release process, the challenges with deriving time series metrics from a firehose of events, and some of the oddities in running analysis on real-time metrics.
- General knowledge of time series data stores, stream and event processing, and data analytics
What you'll learn
- Learn how to leverage real-time time series metrics to improve the client application's lifecycle
Minal Mishra is an engineering manager at Netflix, where he’s part of an effort to improve the software delivery of Netflix’s streaming player. Previously, he was with Xbox Live ecommerce and music and video services teams at Microsoft. Outside work, he enjoys playing tennis.
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