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Migrating Critical Traffic At Scale with No Downtime?—?Part 1

The Netflix TechBlog

Migrating Critical Traffic At Scale with No Downtime — Part 1 Shyam 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. This approach has a handful of benefits.

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Migrating Critical Traffic At Scale with No Downtime?—?Part 2

The Netflix TechBlog

Migrating Critical Traffic At Scale with No Downtime — Part 2 Shyam 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. This is where large-scale system migrations come into play.

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Title Launch Observability at Netflix Scale

The Netflix TechBlog

As Netflix scaled, we faced the mounting challenge of providing accurate, timely answers to increasingly complex queries about title performance and discoverability. By logging all titles as they are displayed, we can process these logs to identify anomalies and gain insights into system performance.

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Title Launch Observability at Netflix Scale

The Netflix TechBlog

Accurately Reflecting Production Behavior A key part of our solution is insights into production behavior, which necessitates our requests to the endpoint result in traffic to the real service functions that mimics the same pathways the traffic would take if it came from the usualcallers. We call this capability TimeTravel.

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Introducing Impressions at Netflix

The Netflix TechBlog

Our Flink configuration includes 8 task managers per region, each equipped with 8 CPU cores and 32GB of memory, operating at a parallelism of 48, allowing us to handle the necessary scale and speed for seamless performance delivery. This integration will not only optimize performance but also ensure more efficient resource utilization.

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Best Practices for Scaling RabbitMQ

Scalegrid

Scaling RabbitMQ ensures your system can handle growing traffic and maintain high performance. Optimizing RabbitMQ performance through strategies such as keeping queues short, enabling lazy queues, and monitoring health checks is essential for maintaining system efficiency and effectively managing high traffic loads.

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Migrating Netflix to GraphQL Safely

The Netflix TechBlog

This blog post will share broadly-applicable techniques (beyond GraphQL) we used to perform this migration. The control group’s traffic utilized the legacy Falcor stack, while the experiment population leveraged the new GraphQL client and was directed to the GraphQL Shim. The Replay Tester tool samples raw traffic streams from Mantis.

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