Most systems start with push because it feels natural — the server knows when something changes, so it notifies clients immediately. But at scale, push embeds a hidden cost multiplier: connected users × open items × update rate. Every millisecond of freshness is paid for by every connected user, even those who aren't watching. This talk is based on a real-world production case study at DraftKings. We’ll explore how the data delivery model shapes the cost curve, rather than just the latency profile. We walk through: — the original push-based system and how it accumulated complexity over the years — the scaling pain points that made it unsustainable under peak load — the evaluation process that led to short polling as the answer — a zero-downtime migration strategy across four phases The results were counter-intuitive: a pull-based architecture with short polling outperformed push on data freshness at peak load, while achieving significant CPU and infrastructure cost reduction. The talk closes with a practical framework for deciding when push wins, when pull wins, and what question to ask first.

When data is scattered across dozens of services, traditional approaches don’t work. We’ll explain how we built an aggregated read model for over 30 million documents, handled 1,500 write RPS, and why Elasticsearch became a key component of the catalog.

Taking a system from 66 million to over 25 billion records is not for the faint of heart—especially when the system in question is financial, where precision is non-negotiable and data latency isn’t an option. In this talk, I’ll walk through the real-world journey of scaling such a system while staying sane and keeping the numbers right. You’ll get a look at how to juggle the need for ultra-high accuracy and low-latency performance, streamline your app logic, and sidestep the usual traps that come with database scaling. This session isn’t about deep-diving into internals—it’s about sharing pragmatic strategies that help you scale without drowning in complexity. Ideal for engineers and system architects eager to tackle serious scale challenges with clarity and confidence.</p> <h4>Abstract