A streaming pipeline is a directed graph of components: source, ingest, transcoder, packager, origin, CDN, edge cache, player. Each one has a defined input format, an output format, a scaling policy and a failure mode. The art of operating a streaming service is keeping every node within its tolerance while traffic patterns, content catalogues and codec mixes change underneath.
The classic OTT pipeline for VOD: source MXF/MOV → transcoder farm (FFmpeg, x264, SVT-AV1) producing an ABR ladder → packager (Shaka, Bento4) emitting CMAF segments and HLS/DASH manifests → object storage (S3, GCS) as origin → multi-CDN front (Akamai, CloudFront, Fastly) → player (hls.js, Shaka, AVPlayer). The live pipeline adds a contribution leg (RTMP, SRT or WebRTC) feeding a live transcoder, and a low-latency variant chains CMAF chunks straight from packager through origin shield to LL-HLS or LL-DASH players.
The pipeline is rarely one vendor end-to-end. Most teams stitch best-of-breed tools and operate the seams: a webhook fires when a new asset is uploaded, a queue picks up the job, the transcoder reports progress to a state store, the packager publishes to a bucket, a CDN invalidation pings the edge. The pipeline's reliability is bounded by its weakest seam, and the streaming engineer's job is mostly hardening seams.
The book · Volume 2 of 7
Video Streaming: A Complete Guide to Video Delivery: From Network Protocols and Transport to Ingest, HLS, and MPEG-DASH
A streaming pipeline is only as stable as its weakest stage, and most outages start at a hand-off between ingest, transcoding, packaging and origin. This volume covers the streaming pipeline in detail from encoder to network, with live and VOD workflows, the latency budget, ingest protocols and HLS, DASH and CMAF packaging. Written by Nikolay Sapunov, CEO at Fora Soft.
Designing or fixing a streaming pipeline end to end?
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