Design a scalable tagging system

Q: Design a scalable tagging system

This question evaluates system architecture and scalability competencies — data modeling, indexing strategies, caching, sharding/partitioning, consistency models, de-duplication and access-control semantics — for designing a multi-tenant, low-latency tagging platform that handles high-cardinality and skewed workloads, and is in the System Design domain. It is commonly asked to assess trade-off reasoning between read/write latency, consistency and storage/index choices, and operational concerns such as monitoring, backfills and capacity planning, and it emphasizes practical application of architectural design principles rather than purely conceptual understanding.

Q: How do I approach System Design interview questions?

System Design questions require understanding of core concepts and practice. PracHub provides solutions with explanations to help you master system design interviews.

Q: What difficulty level is this interview question?

This is a hard difficulty System Design question, commonly asked during Technical Screen rounds at Atlassian.

Q: What role is this question designed for?

This question is commonly asked for Software Engineer candidates at Atlassian during technical interviews.

Question

System Design: Scalable Tagging System for Arbitrary Resources

Context

You are designing a multi-tenant tagging platform that supports attaching tags to arbitrary resources (documents, issues, pages, etc.). Each resource is uniquely identified and may belong to a tenant. The system must provide low-latency reads at scale and handle skewed/high-cardinality tags.

Assume each resource has a stable unique key (resource_key = tenant_id + resource_type + resource_id).

Requirements

Core operations
- Attach and remove tags on resources (idempotent, de-duplicated).
- Query by single tag and multi-tag combinations:
  - AND (resources having all tags)
  - OR (resources having any tag)
- List top-N items per tag (e.g., by recency or score).
- Count items per tag.
- Suggest/autocomplete tags (prefix-based, ranked by usage/recency).
Platform/architecture
- Specify data model and storage choices.
- Indexing strategies for fast writes and reads (e.g., inverted indexes).
- Caching strategy.
- Sharding/partitioning and secondary indexes to handle high cardinality and multi-tenancy.
Data and ops
- Consistency model (eventual vs. strong) and read-your-writes behavior.
- De-duplication, tag rename and merge semantics.
- Access control (tenant boundaries; optional per-resource ACL filtering).
- Pagination approach for result lists.
- Backfill/rebuild and cleanup jobs.
Non-functional
- Provide capacity estimates (orders of magnitude are fine).
- Monitoring, alerting, and SLAs/SLOs.

Design a scalable tagging system

Quick Overview

System Design: Scalable Tagging System for Arbitrary Resources

Context

Requirements

Solution

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