TL;DR Someone on a call asks why buffering spiked on mobile in Germany yesterday afternoon. The old answer is to open a dashboard, find the right filters, and get back to the call ten minutes later with a screenshot. That gap between the question and the answer is where most teams lose time, and it…
TLDR Multi-language output for a live stream means new audio and subtitle streams, manifest changes to signal them, and a translation and dubbing pipeline running in real time, not a toggle in an encoder config. Picking one language and living with it is the easy path, but it leaves viewers who don’t speak that language…
TL;DR MOQT (Media over QUIC Transport) is still an evolving standard, which means the libraries and implementations built on it are a moving target. For Bitmovin as a member of the OpenMOQ consortium, staying current is not optional. A Player built on a library that does not implement the full IETF drafts will fall behind…
TL;DR Live streaming protocols have long been shaped by the constraints of TCP. RTMP and SRT both work around those constraints in different ways, but neither was designed for the low-latency, resilient delivery that modern live streaming demands. MoQ (Media over QUIC Transport) takes a different approach: built natively on QUIC and WebTransport, packet loss,…
TL;DR Ad opportunities are being missed. Someone is watching a thriller on a streaming service. A character pulls on a jacket that looks incredible. They reach for their phone, open a browser, try to describe what they just saw, scroll through three pages of results, and by the time they find something close, the scene…
Advertising in video has not changed much in decades. You watch content, it stops, an ad plays, and then your content resumes. For viewers, that interruption breaks immersion and trains people to tune out the moment a cut happens. The assumption baked into this model is that interruption is just the price of doing business on both sides. I think generative AI gives us a real opportunity to question that.
Most AI coding tools are built around a single user. You work with the agent in a private window, and when the session ends, everything it learned stays with you. The next person on the team starts from zero. That bothered us, so for Bitmovin’s Q2 2026 hackathon…
Bitmovin’s Observability solution already gives teams deep visibility into playback quality and audience behavior. But when an operations team wants to assemble its own view of that data via our API, the current answer is to build it in a tool like Grafana. That works, and it is powerful, but spinning up and maintaining…
Cloud encoder provisioning is live streaming’s most quietly worked-around problem. When a broadcast triggers, the cloud allocates a machine, deploys software, and only then is the encoder ready, an unpredictable delay that breaks news teams, sports platforms, and UGC services have long patched with lead-time buffers and over-provisioning. This post explains why that structural problem exists and how Bitmovin’s Live Encoder Standby Pools solve it with pre-configured, instantly available encoders held in a ready state before they are ever needed.
Ad servers confirm that an ad was sent. They cannot tell you whether it actually played. For streaming platforms where ad revenue is the model, that blind spot is a direct and silent revenue leak. This post examines why player-native, real-time ad analytics have become an operational necessity across FAST channels, live events, and on-demand content, how the failure modes differ by format, and how Bitmovin’s Ad Observability closes the gap with session-level data available at one-minute intervals across CSAI, SSAI, and SGAI delivery.
The Bitmovin Blog. Keeping you informed.