InfoQ Homepage Netflix Content on InfoQ
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Monitoring and Tracing @Netflix Streaming Data Infrastructure
Allen Wang talks about the design and implementation details of the dev/ops tools used by Netflix and highlights the critical roles they play in operating their data infrastructure.
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Passion, Grace, & Fire - The Elements of High Performance
Josh Evans talks about the elements of high performance - passion, grace, and fire -, and what really matters when trying to build, shape, and guide teams for high performance.
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Quantifying Risk
Markus De Shon talks about the Netflix risk quantification that they introduced in their highest impact areas, and are gradually expanding across the enterprise.
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Evolution of Edge @Netflix
Vasily Vlasov reviews Netflix’s edge gateway ecosystem - multiple traffic gateways performing different functions deployed around the world.
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User & Device Identity for Microservices @ Netflix Scale
Satyajit Thadeshwar provides useful insights on how Netflix implemented a secure, token-agnostic, identity solution that works with services operating at a massive scale.
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Scaling Patterns for Netflix's Edge
Justin Ryan talks about Netflix’ scalability issues and some of the ways they addressed it.
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How to Live in a Post–Spring Cloud Netflix World
Marcin Grzejszczak and Olga Maciaszek-Sharma discuss how Netflix has frozen certain projects running on Spring Cloud and moved to new ones.
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Not Sold Yet, GraphQL: A Humble Tale from Skeptic to Enthusiast
Garrett Heinlen talks about how Netflix builds and deploys GraphQL and how they are running it in production.
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Reducing Risk of Credential Compromise @Netflix
Will Bengtson and Travis McPeak talk about Netflix Infrastructure Security.
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Disenchantment: Netflix Titus, Its Feisty Team, and Daemons
Andrew Spyker talks about Netflix's feisty team’s work across container runtimes, scheduling & control plane, and cloud infrastructure integration.
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Crisis to Calm: Story of Data Validation @ Netflix
Lavanya Kanchanapalli discusses safe data propagation at Netflix, circuit breakers, data canaries and staggered rollout effective, and efficient validations via sharing data and isolating change.
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Human-centric Machine Learning Infrastructure @Netflix
Ville Tuulos discusses the tools Netflix built for the data scientists and some of the challenges and solutions made to create a paved road for machine learning models to production.