Zachary Cava - Scalable Per-User Ad Insertion in Live OTT

Описание: As more users shift their viewing from traditional linear mechanisms to over the top streaming services, Live OTT providers are facing ground-breaking levels of scale as they attempt to bring live streams to millions of concurrent users. One very important aspect of this scale is stream monetization through ad insertion as it allows providers to recoup the cost of deployment. Classically, Server-Side Ad Insertion (SSAI) has been the choice for seamless and targeted ad insertion, but this mechanism directly fights a providers ability to scale as targeting granularity becomes a direct multiplier for stream uniqueness. To our address this, we've designed a new paradigm called Server-Guided Ad Insertion (SGAI) which allows user specific ad targeting without compromising on features such as full program rewind and seamless insertion and would like to share this with the community.

This talk will walk through the construction of this new ad insertion paradigm and how we've applied it in production with DASH. First we will briefly discuss why SSAI is constrained at scale and how this relates back to the typical live manifest polling mechanism: manifests must be consistent across updates, thus ad targeting inherently requires response variation and server-state to persist it. Next we will walk through how we decouple manifest updates from response consistency by having the server only provide clients with information they don't already know, aka a patch update, pushing state persistence to the client and making the server state-less. Then we will use this patch update mechanism and an "explode-collapse" routing pattern to show how the main content distribution of the live stream can be shared across all users, while ad opportunities can be uniquely resolved for every client, achieving our goals of per-user ad targeting without feature compromise. Finally we will close on observations from our production deployment of this mechanism and how we are working to make this a standard paradigm in the industry.

Presented at Demuxed 2019 in San Francisco.