Design an Ad Click Aggregator
Architect a realtime ad click aggregation system with event collection, stream processing, deduplication, time-window aggregation, fraud detection, and reconciliation.
What You Will Learn
Break Design an Ad Click Aggregator into core user flows, write paths, read paths, and offline/background work.
Model the dominant data entities, indexing strategy, and hot-path caches before tuning secondary features.
Identify where realtime updates, fan-out, ranking, or matching logic becomes the main scaling constraint.
Plan abuse prevention, reconciliation, and operational visibility alongside the happy path.
Key Decisions
What is the dominant read/write path that makes Design an Ad Click Aggregator hard at scale?
Where do you need async boundaries, queues, or precomputation instead of synchronous work?
Which data becomes hottest first, and how do you partition or cache it safely?
What correctness risks remain after the first scalable design is in place?
Related Topics