Remove Efficiency Remove Latency 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.

Latency 237
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Why Preventive Maintenance Requires Real-Time Decisioning

VoltDB

By continuously monitoring and analyzing video data, preventive maintenance algorithms can predict when equipment is likely to fail. Cameras or sensors capture live or recorded video footage of machinery and equipment in operation. Cameras or sensors capture live or recorded video footage of machinery and equipment in operation.

IoT 52
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Why Predictive Maintenance Requires Real-Time Decisioning

VoltDB

By continuously monitoring and analyzing video data, predictive maintenance algorithms can predict when equipment is likely to fail. Cameras or sensors capture live or recorded video footage of machinery and equipment in operation. Cameras or sensors capture live or recorded video footage of machinery and equipment in operation.

IoT 52
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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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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. Storage: don’t break the bank!

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Introducing Netflix TimeSeries Data Abstraction Layer

The Netflix TechBlog

Rajiv Shringi Vinay Chella Kaidan Fullerton Oleksii Tkachuk Joey Lynch Introduction As Netflix continues to expand and diversify into various sectors like Video on Demand and Gaming , the ability to ingest and store vast amounts of temporal data — often reaching petabytes — with millisecond access latency has become increasingly vital.

Latency 240
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Netflix Video Quality at Scale with Cosmos Microservices

The Netflix TechBlog

Moorthy and Zhi Li Introduction Measuring video quality at scale is an essential component of the Netflix streaming pipeline. Perceptual quality measurements are used to drive video encoding optimizations , perform video codec comparisons , carry out A/B testing and optimize streaming QoE decisions to mention a few.

Media 179