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# JioHotstar Explains the Distributed Engineering Behind Personalized Ad Requests at Streaming Scale

**[InfoQ](https://daily.dev/sources/infoq)** · 3 min read · 0 upvotes · 0 comments

## Summary

JioHotstar has published an engineering overview of its real-time ad request workflow, detailing how the platform coordinates distributed services to select and deliver personalized ads during video playback. The system uses a waterfall tiering approach combined with pacing algorithms (PID and SHALE) to select ads from thousands of candidates within a 100ms latency budget, even during high-concurrency live sports events. Key engineering challenges include managing inventory allocation, campaign pacing, failure handling, and cross-team coordination across ad decisioning, tracking, and analytics services. The architecture aligns with industry standards like OpenRTB while adding internal layers for personalization and content-aware targeting.

## Full article

daily.dev links to this article rather than hosting it. Read it at the original source: <https://www.infoq.com/news/2026/08/jiohotstar-ad-decisioning-flow>

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---

Tags: [#microservices](https://daily.dev/tags/microservices), [#distributed-systems](https://daily.dev/tags/distributed-systems)

[View this post on daily.dev](https://daily.dev/posts/jiohotstar-explains-the-distributed-engineering-behind-personalized-ad-requests-at-streaming-scale-9m7kmpinr)

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