Netflix

Optimizing Recommendation Systems with JDK’s Vector API

Netflix's Ranker service had a video serendipity scoring feature (computing how different a title is from a user's watch history) consuming ~7.5% of total CPU per node, creating a significant performance bottleneck at their enormous scale.

ml-systems real-time-systems
5 min
Netflix

Mount Mayhem at Netflix: Scaling Containers on Modern CPUs

Netflix needed to spin up hundreds of containers in seconds to serve streaming traffic, but after modernizing their container runtime, they hit an unexpected performance bottleneck rooted in CPU architecture that impaired container scaling efficiency.

distributed-systems real-time-systems
5 min
Netflix

How Temporal Powers Reliable Cloud Operations at Netflix

Netflix needed reliable orchestration for business-critical cloud operations across teams like Open Connect CDN and Live reliability, but faced operational challenges as Temporal adoption grew since 2021.

distributed-systems microservices
5 min
Netflix

Netflix Live Origin

Netflix needed a custom origin server to bridge its cloud-based live streaming pipelines with its CDN (Open Connect), handling the unique challenges of live content delivery such as low-latency requirements, reliability, and the real-time nature of live streams compared to on-demand content.

real-time-systems distributed-systems
5 min
Netflix

AV1 — Now Powering 30% of Netflix Streaming

Delivering high-quality streaming video across diverse devices and varying network conditions requires efficient video encoding; legacy codecs like H.264 and VP9 were limiting compression efficiency, consuming more bandwidth for equivalent visual quality.

real-time-systems storage-systems
5 min