Design an Instagram-like photo-sharing platform

Q: Design an Instagram-like photo-sharing platform

This question evaluates system design competencies including distributed systems, scalability and capacity planning, data modeling and storage strategies, API design, media processing and CDN integration, consistency models, operational reliability, observability, and estimation.

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 Onsite rounds at Meta.

Q: What role is this question designed for?

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

Question

System Design: Instagram-like Photo and Short-Video Platform

Goal

Design an Instagram-like platform for photos and short videos. The design should cover product features, scale assumptions, APIs, storage, feed/ranking, media handling, and operational concerns.

Functional Requirements

Post: create, edit (caption), delete; single image or short video; hashtags, mentions, location
Follow graph: follow/unfollow; follower and following lists
Interactions: like/unlike, comment/delete, counts
Feed: home timeline combining followed accounts and recommendations; infinite scroll; pagination
Notifications: likes, comments, follows, mentions; push and in-app
Profiles: public/private accounts; block/mute; profile media grid

Non-Functional Goals

Availability: high availability across regions for read path (feed/media). State explicit SLOs.
Latency: sub-200 ms p95 for metadata APIs; smooth media playback
Scalability: support 100M+ DAU; elastic fan-out; hot accounts handling
Consistency: read-your-writes for own actions; eventual for others; clear timeline semantics

Deliverables

APIs (CRUD for posts, follow, like, comment, feed, notifications)
Data model and storage choices
Media handling: upload, transcode, storage, CDN
Feed generation and ranking pipeline
Timeline consistency model
Caching and search
Sharding/partitioning and replication
Background jobs (fan-out, media processing)
Rate limiting and abuse prevention
Privacy/permissions model
Observability (metrics, logs, traces), disaster recovery
Back-of-the-envelope capacity: QPS, storage, bandwidth, and rough cost

Estimation

State reasonable scale assumptions (e.g., MAU/DAU, posts/day, follower distribution) and compute QPS, storage, and bandwidth.
Justify any additional assumptions you make.