Video Encoding at Scale of Netflix
Ever Wondered how Netflix is able to achieve Scalable Video Encoding?
?? Netflix has built a video encoding pipeline that can efficiently and reliably scale to process large numbers of titles and video encodes, while guaranteeing a high quality of experience for its members.
?? The video encoding pipeline runs on EC2 Linux cloud instances and can easily scale up or down based on demand. It also utilizes Netflix's internal spot market to dynamically allocate compute resources.
?? To ensure high quality output streams, Netflix inspects its source videos and rejects those that contain distortion or artifacts that would result in bad quality video encodes. This is done to ensure that the best source video available is ingested into the system, and to avoid unnecessary burden on the pipeline from complex error mitigation techniques downstream.
?? Netflix supports a variety of source types, including Interoperable Master Format (IMF), ProRes, DPX, and MPEG.
?? To efficiently support large 4K source files, Netflix inspects the files in smaller chunks and performs bitstream-level and pixel-level analysis on each chunk in parallel on different instances.
?? To generate multiple quality representations at different bitrates, Netflix performs encoding on chunks of the source file, allowing for efficient parallelization. Each encoded chunk is verified for correctness immediately after it completes encoding to ensure quality control at every step of the pipeline.
?? Netflix uses a content delivery network (CDN) to stream video encodes to its members. During a streaming session, the client requests the encodes it can play and adaptively switches among quality levels based on network conditions.
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?? The Netflix encoding pipeline is designed to handle transient errors and recover from them, ensuring the robustness of the cloud-based system.
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