Outlier detection can be a pain point for all data driven companies, especially as data volumes grow. At Netflix we have multiple datasets growing by 10B+ record/day and so there’s a need for automated anomaly detection tools ensuring data quality and identifying suspicious anomalies. Today we are open-sourcing our outlier detection function, called...
الخميس، 19 فبراير 2015
الأربعاء، 18 فبراير 2015
A Microscope on Microservices
by Coburn Watson, Scott Emmons, and Brendan GreggAt Netflix we pioneer new cloud architectures and technologies to operate at massive scale - a scale which breaks most monitoring and analysis tools. The challenge is not just handling a massive instance count but to also provide...
الثلاثاء، 10 فبراير 2015
What's trending on Netflix?
By Prasanna Padmanabhan, Kedar Sadekar, Gopal KrishnanEvery day, millions of members across the globe, from thousands of devices, visit Netflix and generate millions of viewing hours. The majority of these viewing hours are generated through the videos that are recommended by...
Nicobar: Dynamic Scripting Library for Java
By James Kojo, Vasanth Asokan, George Campbell, Aaron TullThe Netflix API is the front door to the streaming service, handling billions of requests per day from more than 1000 different device types around the world. To provide the best experience to our subscribers, it is critical...
الاثنين، 2 فبراير 2015
SPS : the Pulse of Netflix Streaming
We want to provide an amazing experience to each member, winning the “moments of truth” where they decide what entertainment to enjoy. To do that, we need to understand the health of our system. To quickly and easily understand the health of the system, we need a...
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