{"id":7243,"date":"2014-04-02T02:00:49","date_gmt":"2014-04-01T20:30:49","guid":{"rendered":"http:\/\/blog.fusioncharts.com\/?p=7243"},"modified":"2026-01-20T14:41:56","modified_gmt":"2026-01-20T09:11:56","slug":"how-netflix-plans-to-improve-its-operational-visibility-with-real-time-data-visualization","status":"publish","type":"post","link":"https:\/\/www.fusioncharts.com\/blog\/how-netflix-plans-to-improve-its-operational-visibility-with-real-time-data-visualization\/","title":{"rendered":"How Netflix Improves Its Visibility with Real-Time Data 2026"},"content":{"rendered":"This is the second post in our Data Visualization Spotlight<\/b><\/a> series where we showcase how different organizations are using data visualization and analytics to solve their day to day problems.<\/em>\r\n\r\nIn mid-March 2013, Netflix reported a global streaming subscriber list of 33 million.\u00a0It increased to 36.3 million (29.2 million in U.S.) in April 2013. It had 40.4 million subscribers (31.2 million in U.S.) in September 2013. \u00a0By Q4 2013, it reported 33.1 million subscribers in U.S alone.\r\n\r\n\"Netflix\"\r\n\r\nWith its subscriber list growing by leaps and bounds, Netflix faces the daunting task of supporting millions of connected devices spread across 40+ countries. At such a big a scale, it is impossible to manually monitor all that data. Imagine having to detect a system fault in an environment that is not only large and complex but also highly distributed!\r\n\r\nTo thwart such operational nightmares from occurring, the Netflix team is working on a greenfield project that focuses on building the next generation tools for operational visibility that can proactively detect and communicate system faults and identify areas of improvement.\r\n\r\n
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