Remove Latency Remove Traffic Remove Tuning Remove Video
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Bending pause times to your will with Generational ZGC

The Netflix TechBlog

More than half of our critical streaming video services are now running on JDK 21 with Generational ZGC, so it’s a good time to talk about our experience and the benefits we’ve seen. Reduced tail latencies In both our GRPC and DGS Framework services, GC pauses are a significant source of tail latencies.

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Turbocharge Your Content Delivery With CDN Multiple Origins Load Balancer!

IO River

‍Just as a well-coordinated airport directs flights to multiple runways based on traffic and weather conditions, a CDN with Multiple Origins Load Balancing ensures that web traffic is distributed across various data centers, optimizing performance and reliability. ‍But how does it decide where to send this traffic?

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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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Turbocharge Your Content Delivery With CDN Multiple Origins Load Balancer!

IO River

Just as a well-coordinated airport directs flights to multiple runways based on traffic and weather conditions, a CDN with Multiple Origins Load Balancing ensures that web traffic is distributed across various data centers, optimizing performance and reliability. But how does it decide where to send this traffic?

Traffic 40
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Building Netflix’s Distributed Tracing Infrastructure

The Netflix TechBlog

Investigating a video streaming failure consists of inspecting all aspects of a member account. If we had an ID for each streaming session then distributed tracing could easily reconstruct session failure by providing service topology, retry and error tags, and latency measurements for all service calls.

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Rebuilding Netflix Video Processing Pipeline with Microservices

The Netflix TechBlog

The Netflix video processing pipeline went live with the launch of our streaming service in 2007. This architecture shift greatly reduced the processing latency and increased system resiliency. For example, in Reloaded the video quality calculation was implemented inside the video encoder module.

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Migrating Netflix to GraphQL Safely

The Netflix TechBlog

We could also swap out the implementation of a field from GraphQL Shim to Video API with federation directives. 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. How does it work?

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