Remove Servers Remove Traffic Remove Tuning
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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.

Traffic 285
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Introducing Impressions at Netflix

The Netflix TechBlog

These events are promptly relayed from the client side to our servers, entering a centralized event processing queue. This approach ensures high availability by isolating regions, so if one becomes degraded, others remain unaffected, allowing traffic to be shifted between regions to maintain service continuity.

Tuning 166
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Migrating Netflix to GraphQL Safely

The Netflix TechBlog

Before GraphQL: Monolithic Falcor API implemented and maintained by the API Team Before moving to GraphQL, our API layer consisted of a monolithic server built with Falcor. A single API team maintained both the Java implementation of the Falcor framework and the API Server. To launch Phase 1 safely, we used AB Testing.

Traffic 357
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TCP: Out of Memory — Consider Tuning TCP_Mem

DZone

The application was running on a GNU/Linux OS, Java 8, Tomcat 8 application server. All other application instances were handling the traffic properly. Proxy Error The proxy server received an invalid response from an upstream server. Proxy Error The proxy server received an invalid response from an upstream server.

Tuning 173
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RabbitMQ vs. Kafka: Key Differences

Scalegrid

Kafka clusters can be deployed in Kubernetes using Helm charts to simplify scaling and management across multiple servers. Optimizing RabbitMQ requires clustering, queue management, and resource tuning to maintain stability and efficiency. However, performance can decline under high traffic conditions.

Latency 147
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Rapid Event Notification System at Netflix

The Netflix TechBlog

To this end, we developed a Rapid Event Notification System (RENO) to support use cases that require server initiated communication with devices in a scalable and extensible manner. We thus assigned a priority to each use case and sharded event traffic by routing to priority-specific queues and the corresponding event processing clusters.

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