PinnedMigrating Critical Traffic At Scale with No Downtime — Part 2Shyam Gala, Javier Fernandez-Ivern, Anup Rokkam Pratap, Devang Shah Picture yourself enthralled by the latest episode of your beloved Netflix series, delighting in an uninterrupted, high-definition streaming experience. Behind these perfect moments of entertainment is a complex mechanism, with numerous gears and cogs working in harmony. But what happens when…Distributed Systems10 min readDistributed Systems10 min read
Published inNetflix TechBlog·PinnedMigrating Critical Traffic At Scale with No Downtime — Part 1Shyam Gala, Javier Fernandez-Ivern, Anup Rokkam Pratap, Devang Shah Hundreds of millions of customers tune into Netflix every day, expecting an uninterrupted and immersive streaming experience. Behind the scenes, a myriad of systems and services are involved in orchestrating the product experience. These backend systems are consistently being evolved and…Distributed Systems10 min readDistributed Systems10 min read
Published inNetflix TechBlog·PinnedImproved Alerting with Atlas Streaming EvalRuchir Jha, Brian Harrington, Yingwu Zhao TL;DR Streaming alert evaluation scales much better than the traditional approach of polling time-series databases. It allows us to overcome high dimensionality/cardinality limitations of the time-series database. It opens doors to support more exciting use-cases. Engineers want their alerting system to be realtime, reliable…Observability7 min readObservability7 min read
Published inNetflix TechBlog·PinnedBuilding a Media Understanding Platform for ML InnovationsBy Guru Tahasildar, Amir Ziai, Jonathan Solórzano-Hamilton, Kelli Griggs, Vi Iyengar Introduction Netflix leverages machine learning to create the best media for our members. Earlier we shared the details of one of these algorithms, introduced how our platform team is evolving the media-specific machine learning ecosystem, and discussed how data from…Machine Learning12 min readMachine Learning12 min read
Published inNetflix TechBlog·PinnedScaling Media Machine Learning at NetflixBy Gustavo Carmo, Elliot Chow, Nagendra Kamath, Akshay Modi, Jason Ge, Wenbing Bai, Jackson de Campos, Lingyi Liu, Pablo Delgado, Meenakshi Jindal, Boris Chen, Vi Iyengar, Kelli Griggs, Amir Ziai, Prasanna Padmanabhan, and Hossein Taghavi Introduction In 2007, Netflix started offering streaming alongside its DVD shipping services. As the catalog grew…Machine Learning11 min readMachine Learning11 min read
Published inNetflix TechBlog·2 days agoEnsuring the Successful Launch of Ads on NetflixBy Jose Fernandez, Ed Barker, Hank Jacobs Introduction In November 2022, we introduced a brand new tier — Basic with ads. This tier extended existing infrastructure by adding new backend components and a new remote call to our ads partner on the playback path. As we were gearing up for launch…Distributed Systems5 min readDistributed Systems5 min read
Published inNetflix TechBlog·May 19Debugging a FUSE deadlock in the Linux kernelTycho Andersen The Compute team at Netflix is charged with managing all AWS and containerized workloads at Netflix, including autoscaling, deployment of containers, issue remediation, etc. As part of this team, I work on fixing strange things that users report. This particular issue involved a custom internal FUSE filesystem: ndrive…Linux8 min readLinux8 min read
Published inNetflix TechBlog·May 19ABAC on SpiceDB: Enabling Netflix’s Complex Identity TypesBy Chris Wolfe, Joey Schorr, and Victor Roldán Betancort Introduction The authorization team at Netflix recently sponsored work to add Attribute Based Access Control (ABAC) support to AuthZed’s open source Google Zanzibar inspired authorization system, SpiceDB. Netflix required attribute support in SpiceDB to support core Netflix application identity constructs. …Authorization9 min readAuthorization9 min read
Published inNetflix TechBlog·Mar 3Data ingestion pipeline with Operation Managementby Varun Sekhri, Meenakshi Jindal, Burak Bacioglu — Introduction At Netflix, to promote and recommend the content to users in the best possible way there are many Media Algorithm teams which work hand in hand with content creators and editors. Several of these algorithms aim to improve different manual workflows so that we show the personalized promotional image, trailer…Annotations7 min readAnnotations7 min read
Published inNetflix TechBlog·Jan 30Discovering Creative Insights in Promotional ArtworkBy Grace Tang, Aneesh Vartakavi, Julija Bagdonaite, Cristina Segalin, and Vi Iyengar When members are shown a title on Netflix, the displayed artwork, trailers, and synopses are personalized. That means members see the assets that are most likely to help them make an informed choice. These assets are a critical…Data Science9 min readData Science9 min read
