Design ads frequency capping service
Overview
This question evaluates a candidate's ability to design a low-latency, high-QPS, multi-tenant frequency capping service, testing competencies in identity resolution, hierarchical cap modeling, window semantics, counter and storage architecture, consistency versus latency trade-offs, real-time decisioning APIs, configuration/versioning, backfill, reporting, privacy/compliance, and failure handling. It is commonly asked to assess systems-design proficiency in distributed systems, databases, caching, API design, and operational reliability; it belongs to the System Design domain and emphasizes practical application with system-level conceptual reasoning rather than purely algorithmic detail.
Design an Ads Frequency Capping Service
Context
You are designing a service that ensures a user does not see the same ad creative or campaign more than a configured number of times within specified time windows (for example, 3/day per campaign, 10/week across an advertiser). The service must support real-time ad decisioning at high QPS with low latency, multi-tenant advertiser onboarding, and reliable reporting.
Assume an ad-supported video application with: high read QPS during ad selection, sub-10 ms p99 decision latency, multi-region deployment, and strict privacy/compliance requirements. The system integrates with an ad server/selector that provides candidate ads and expects an allow/deny decision before rendering.
Task
Design the frequency capping service and compare it to a generic rate limiter. Explain the extra components required for advertiser configuration and onboarding.
Cover the following topics:
- Identity resolution: cookies, device graph, logged-in IDs; user/household scoping.
- Cap dimensions: creative, ad group, campaign, advertiser (hierarchical caps and combinations).
- Window semantics: sliding vs tumbling windows and calendar anchoring (day/week).
- Counter and storage design: keying, bucketization, TTL, atomicity across multiple caps, memory/scale estimates.
- Consistency vs latency trade-offs: within and across regions; concurrency/race conditions; acceptable overshoot.
- Real-time decisioning at high QPS: API design, check/reserve/commit flow, batching/vectorized lookups, concurrency.
- Configuration APIs and validation: schema, constraints, default caps, targeting/scope.
- Config propagation, versioning, and rollback: canaries, pub/sub to caches, freeze/rollback plans.
- Backfill and migrations: enabling new caps mid-flight, identity merges/splits, data warmup.
- Reporting needs: aggregates, rejection reasons, near-real-time dashboards, retention.
- Privacy and compliance: consent, minimization, retention, deletion, cross-device linking safeguards.
- Failure handling: store outages, partial availability, stale config, decision policy (fail-open vs fail-closed).
Also include a brief comparison to a generic rate limiter and highlight the additional components needed for advertiser onboarding and configuration.
Solution
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