Design Instagram Feed Ranking — System Design Practice | AmanAI Lab

Sheet›Design Instagram Feed Ranking

MetaGoogle

45:00

Hard

The Problem

Problem

Design Instagram's feed ranking system that selects and orders posts for 2 billion users from their followed accounts and recommended content.

The system must:

•Maximise meaningful engagement (comments, shares > passive scrolling)
•Balance posts from followed accounts with recommended content
•Ensure creator equity (small creators get fair distribution)
•Detect and demote harmful or low-quality content

What you'll be assessed on

Multi-objective ranking, candidate generation from followed accounts vs recommendations, creator equity, and measuring "meaningful" vs vanity engagement.

Scale & Constraints

▸2B users, 50M posts/day
▸Average user follows 500 accounts
▸Feed generation latency ≤ 500ms
▸Mix: 70% followed accounts + 30% recommended content
▸New posts from followed accounts appear in feed within 5 minutes
▸Creator equity: small creators (< 10K followers) receive proportional distribution

Must Cover0/10

Hints (if stuck)

💡 Long-form engagement (comments, DMs) correlates better with satisfaction than likes.

💡 Post freshness decay: an older post from a close friend outranks a newer post from a distant connection.

💡 Creator equity: if everyone saw at rate proportional to follow count, small creators would disappear.

💡 Cascade ranking: first rank all followed-account content, then interleave recommended content at fixed positions.

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Problem

Design Instagram's feed ranking system that selects and orders posts for 2 billion users from their followed accounts and recommended content.

The system must:

•Maximise meaningful engagement (comments, shares > passive scrolling)

•Balance posts from followed accounts with recommended content

•Ensure creator equity (small creators get fair distribution)

•Detect and demote harmful or low-quality content

What you'll be assessed on