Design a scalable tagging system

Q: Design a scalable tagging system

This question evaluates understanding of distributed systems, data modeling, indexing, sharding, caching, consistency models, and multi-tenant architecture for building high-throughput tagging and query services.

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Question

System Design: Scalable Tagging Service

Context

You are designing a multi-tenant tagging service for a large-scale SaaS product. Items (e.g., documents, issues, pages) can have multiple tags. The system must support high read/write throughput and efficient queries by one or multiple tags.

Assume scale on the order of:

100M items, 10M distinct tags, average 5–20 tags per item
Peak 10k read QPS, 2k write QPS (tag add/remove)
Multi-tenant isolation is required

Requirements

Create and manage tags
Associate/dissociate multiple tags with an item
Query items:
- by a single tag
- by a combination of tags (AND/OR), with pagination and sort (e.g., recency)
High availability and low latency for reads; scalable writes
Consistency model: clearly define and implement (eventual vs read-your-writes)
Sharding, caching, and indexing strategies for scale
Operability: monitoring, reindexing, backfills

Deliverables

Data model and storage choices
Read and write paths (including APIs)
Indexing strategy for tag queries (single and combined)
Sharding/partitioning plan
Caching strategy and invalidation
Consistency trade-offs and mechanisms
Handling hot tags, skew, and growth

Design a scalable tagging system

System Design: Scalable Tagging Service

Context

Requirements

Deliverables

Solution

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