How to design a DSP architecture for 1M QPS CPM ads without overspending?
adtechdsparchitecturehigh-throughput
I’m working on the system architecture for a high-throughput AdTech DSP and would love feedback from people who’ve built large-scale bidding / serving systems. Constraints / Goals: DSP only (no exchange), Target: 1M ad requests/sec, End-to-end DSP latency budget: ~100ms, Pricing model: CPM, Hard requirement: no advertiser or campaign overspend. Open Questions: At 1M QPS, how do people actually enforce budget guarantees? Is Redis bitmap–based targeting viable at this scale? How do you balance strict budget enforcement, low latency, and high throughput?
Synthesized Answer
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Designing a DSP architecture for 1M QPS CPM ads without overspending requires a combination of efficient data structures, scalable architecture, and robust budget enforcement mechanisms. To achieve this, consider using a distributed, in-memory data grid for campaign fetching and targeting, such as Apache Ignite or Hazelcast, which can handle high QPS and provide low-latency responses. For budget enforcement, a combination of techniques such as probabilistic data structures (e.g., HyperLogLog) and asynchronous budget updates can help minimize overspend while maintaining high throughput.
Key Takeaways
Use a distributed, in-memory data grid for campaign fetching and targeting
Implement probabilistic data structures for budget tracking and asynchronous budget updates
Balance strict budget enforcement with low latency and high throughput using techniques like rate limiting and budget pacing
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