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.

What difficulty level is this interview question?

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

What role is this question designed for?

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

Design a scalable photo deduplication service | Abnormal Security Interview Question

Quick Overview

Design a scalable photo deduplication service evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

Design a scalable photo deduplication service

System Design: Productionizing Duplicate-Photo Removal at Scale

Context

Design a production system that detects and removes duplicate or near-duplicate photos across tens of millions of files stored in multiple storage locations (e.g., object stores, NAS, user devices) and processed by multiple machines. Assume batch and incremental runs, multi-tenant data, and strict safety/observability requirements.

Requirements

Cover the following decisions and trade-offs:

Dedupe index
- Choose a distributed KV/DB (e.g., Redis vs alternatives) for the dedupe index.
- Key schema, memory sizing, and eviction strategy.
Batch pipeline
- Use MapReduce/Spark (or similar) to scan and hash at scale.
- Partitioning strategy and data locality across storage locations/regions.
Correctness under concurrency
- Idempotency, exactly-once processing, and handling race conditions when workers overlap.
Safety and rollout
- Verification before deletion, canarying, soft-delete/restore workflow, and immutable audit logs.
Reliability
- Fault tolerance, retries, backpressure, and monitoring (latency, throughput, error rates).
Incrementality
- Incremental runs for newly added files and periodic re-hashing when algorithms change.
Security and isolation
- Permissions model and multi-tenant isolation.
Cost and throughput
- Provide rough cost and throughput estimates and capacity sizing assumptions.

Constraints & Assumptions

Preserve the scope, facts, inputs, and requested outputs from the prompt above.
If the prompt leaves a detail unspecified, state a reasonable assumption before relying on it.
Keep the answer interview-ready: concise enough to present, but concrete enough to implement or evaluate.

Clarifying Questions to Ask Guidance

Clarify users, core use cases, read/write patterns, scale, latency, availability, and data retention.
State explicit assumptions before making sizing or architecture decisions.
Prioritize the functional path first, then address reliability, security, observability, and rollout.

What a Strong Answer Covers Guidance

A scoped requirements summary with concrete non-goals and success metrics.
API, data model, architecture, consistency, capacity, and operations.
Reasoned trade-offs among simple and scalable designs, including bottlenecks and failure modes.
A validation, monitoring, migration, and launch plan appropriate for the risk level.

Follow-up Questions Guidance

What breaks first at 10x traffic or data volume?
How would you degrade gracefully during dependency failures?
What metrics and alerts would prove the design is healthy after launch?

Quick Overview

Context

Requirements

Cover the following decisions and trade-offs:

Dedupe index

Choose a distributed KV/DB (e.g., Redis vs alternatives) for the dedupe index.
Key schema, memory sizing, and eviction strategy.

Batch pipeline

Use MapReduce/Spark (or similar) to scan and hash at scale.
Partitioning strategy and data locality across storage locations/regions.

Correctness under concurrency

Idempotency, exactly-once processing, and handling race conditions when workers overlap.

Safety and rollout

Verification before deletion, canarying, soft-delete/restore workflow, and immutable audit logs.

Reliability

Fault tolerance, retries, backpressure, and monitoring (latency, throughput, error rates).

Incrementality

Incremental runs for newly added files and periodic re-hashing when algorithms change.

Security and isolation

Permissions model and multi-tenant isolation.

Cost and throughput

Provide rough cost and throughput estimates and capacity sizing assumptions.

Constraints & Assumptions

Preserve the scope, facts, inputs, and requested outputs from the prompt above.

If the prompt leaves a detail unspecified, state a reasonable assumption before relying on it.

Keep the answer interview-ready: concise enough to present, but concrete enough to implement or evaluate.

Clarifying Questions to Ask Guidance

Clarify users, core use cases, read/write patterns, scale, latency, availability, and data retention.

State explicit assumptions before making sizing or architecture decisions.

Prioritize the functional path first, then address reliability, security, observability, and rollout.

What a Strong Answer Covers Guidance

A scoped requirements summary with concrete non-goals and success metrics.

API, data model, architecture, consistency, capacity, and operations.

Reasoned trade-offs among simple and scalable designs, including bottlenecks and failure modes.

A validation, monitoring, migration, and launch plan appropriate for the risk level.

Follow-up Questions Guidance

What breaks first at 10x traffic or data volume?

How would you degrade gracefully during dependency failures?

What metrics and alerts would prove the design is healthy after launch?

Design a scalable photo deduplication service

Quick Overview

Design a scalable photo deduplication service

Design a scalable photo deduplication service

System Design: Productionizing Duplicate-Photo Removal at Scale

Context

Requirements

Constraints & Assumptions

Clarifying Questions to Ask Guidance

What a Strong Answer Covers Guidance

Follow-up Questions Guidance

Submit Your Answer to Earn 20XP

Design a scalable photo deduplication service

Quick Overview

Design a scalable photo deduplication service

Design a scalable photo deduplication service

System Design: Productionizing Duplicate-Photo Removal at Scale

Context

Requirements

Constraints & Assumptions

Clarifying Questions to Ask Guidance

What a Strong Answer Covers Guidance

Follow-up Questions Guidance

Submit Your Answer to Earn 20XP