Engineering solutions for OTT and connected TV

Getting video from an origin server to someone’s television involves more steps than most people expect. The encoding has to match what the device can decode. The packaging format has to work with the player. DRM keys have to arrive on time. The CDN has to cache segments correctly. And when something breaks at 9pm on a Friday, you need enough instrumentation to figure out where the problem actually is.

These solution areas reflect the kinds of work we do and the topics we cover in depth across the site.

Platform Engineering

Building for OTT means building for fragmentation. Every device family has its own runtime, its own media pipeline, and its own set of constraints. Roku runs BrightScript. Samsung TVs run Tizen with a Chromium-based web engine. Google TV is Android with a Leanback UI layer. LG uses webOS. Each one needs its own build, its own test plan, and often its own playback stack configuration.

Read more about OTT platform work

Video Delivery Performance

Latency, buffering, and rebuffering ratios are the metrics that matter most to viewers. But improving them requires understanding the full path: encoder output, segment duration, CDN cache behavior, manifest updates, and player buffer management. Small changes in any of these can have outsized effects on the viewing experience.

Explore video delivery performance

Streaming App Architecture

A streaming app is not just a video player with a menu. It is a client that manages authentication, entitlements, content catalogs, playback sessions, analytics, and error recovery, often running on hardware with limited memory and no dev tools. Getting the architecture right from the start saves months of rework later.

See our approach to streaming app architecture

Device QA and Release

Testing a streaming app means testing on real devices. Emulators miss too much: codec support, DRM behavior, HDMI handshake issues, CEC conflicts, memory limits under sustained playback. A good QA process includes a device matrix, automated smoke tests where possible, and a release pipeline that catches regressions before they reach production.

Learn about device QA and release