Meta System Design Interview

What Meta actually tests, how it evaluates, and how to think at Staff level. 27 episodes covering distributed systems fundamentals, 13 real Meta-style design problems, and capstone mock interviews.

27 modules~7 hours total

About This Course

This is not another generic system design course.

Meta's system design interviews have specific evaluation criteria, specific signals interviewers look for, and specific problems drawn from their own infrastructure. This series teaches you exactly what those are.

We start with how Meta interviews actually work — the format, the rubric, the levels. Then we build a design framework and estimation toolkit calibrated to what Meta evaluates.

Before diving into design problems, we cover 5 foundational building blocks that appear in nearly every answer: consistent hashing, Redis (from basics to advanced patterns like distributed Top-K and rate limiting), Kafka and event-driven architecture, Meta's TAO graph storage internals, and leader election protocols.

From there, we tackle 12 real Meta-style design problems across four groups: social products (Instagram Feed, News Feed, Messenger, WhatsApp), real-time delivery (Notification System, Live Video Streaming), infrastructure (Distributed Cache, Social Graph/TAO, Rate Limiter), and data-intensive systems (Typeahead/Autocomplete, Trending Topics, Ad Click Analytics, Real-time Ranking, Experimentation Platform).

Finally, we cover product-system hybrid questions, Staff-level (IC6) thinking, tradeoff depth, and run a complete mock interview.

Every episode includes architecture diagrams, estimation practice, and explicit callouts for what an IC4, IC5, or IC6 answer looks like.

Original curriculum inspired by publicly available Meta engineering blog posts, InfoQ talks, and the experiences of Staff+ engineers.

Prerequisites

  • Working knowledge of distributed systems basics (load balancers, databases, caching)
  • Familiarity with at least one backend language (Python, Java, Go, C++)
  • Understanding of basic data structures and algorithms
  • No prior Meta interview experience required

What You Will Learn

  • Understand the Meta system design interview format, rubric, and evaluation signals
  • Apply a structured design framework calibrated to Meta's expectations
  • Perform capacity estimation and back-of-envelope calculations confidently
  • Master foundational building blocks: consistent hashing, Redis, Kafka, TAO, leader election
  • Design core Meta systems: feeds, messaging, notifications, live streaming, caching, social graph
  • Design data-intensive systems: typeahead search, trending topics, ad analytics, real-time ranking
  • Articulate tradeoffs at Staff level (IC6) depth with quantitative reasoning
  • Recognize what separates IC4, IC5, and IC6 answers on the same problem
  • Handle streaming aggregation, approximate counting, and OLAP query patterns
  • Execute a full 45-minute mock Meta system design interview

Terminology Mapping

How classic concepts map to the terminology used in this course.

ClassicThis Course (Meta)
Load BalancerProxygen / L7 LB
CacheMemcache / TAO cache layer
Message QueueScribe / LogDevice
DatabaseMySQL + TAO / ZippyDB
Service MeshServiceRouter / Thrift
CDNMeta CDN / PoPs
Feature FlagsGatekeeper
A/B TestingQuick Experiments (QE)
Coordination ServiceZooKeeper / ShardManager
Stream ProcessingScribe + Stylus / Flink

Published artifact provenance

How this course was made

This record is derived from the published course and deck manifests. It describes what the artifacts document—and states what they do not.

Source attribution
Original curriculum inspired by publicly available Meta engineering blog posts, InfoQ talks, and the experiences of Staff+ engineers.
Published lesson decks
27 decks published across 27 lessons
Slides
387 slides across 27 decks (11–17 per deck)
Measured narration
2 hr 39 min; duration recorded for 10 of 27 lessons
Estimated study time
Approximately 7 hours of study time—not video length
Decks generated
Feb 22, 2026 to Feb 28, 2026
Course manifest generated
Mar 3, 2026

Recorded speaker configuration

  • Lena Brookshost · curiousVoice ID: English_CaptivatingStoryteller
  • Dr. Weiteacher · socraticVoice ID: Weidong2025
  • Samstudent · engagedVoice ID: English_CalmWoman
  • Avery Chenassistant · engagedVoice ID: English_CalmWoman
Lesson-by-lesson build record
LessonPublishedSlidesGeneratedRecorded versionsMeasured narration
How Meta System Design Interviews Work01-how-meta-interviews-workYes13Feb 28, 2026Lecture 2026-02-28 · Deck schema v3Not recorded
The Meta Design Framework02-meta-design-frameworkYes13Feb 28, 2026Lecture 2026-02-28 · Deck schema v3Not recorded
Estimation for Meta03-estimation-for-metaYes12Feb 28, 2026Lecture 2026-02-28 · Deck schema v3Not recorded
Consistent Hashing & Partitioning04-consistent-hashingYes15Feb 28, 2026Lecture 2026-02-28 · Deck schema v3Not recorded
Redis — Crash Course to Advanced Patterns05-redis-crash-courseYes17Feb 28, 2026Lecture 2026-02-28 · Deck schema v3Not recorded
Kafka & Event-Driven Architecture06-kafka-event-streamingYes14Feb 28, 2026Lecture 2026-02-28 · Deck schema v3Not recorded
Graph Storage & TAO Internals07-graph-storage-tao-internalsYes15Feb 28, 2026Lecture 2026-02-28 · Deck schema v3Not recorded
Leader Election & Distributed Coordination08-leader-electionYes14Feb 28, 2026Lecture 2026-02-28 · Deck schema v3Not recorded
Design Instagram Feed09-design-instagram-feedYes14Feb 24, 2026Lecture 2026-02-24 · Deck schema v317 min
Design Facebook News Feed10-design-facebook-newsfeedYes15Feb 24, 2026Lecture 2026-02-24 · Deck schema v321 min
Design Messenger11-design-messengerYes15Feb 22, 2026Lecture 2026-02-22 · Deck schema v3Not recorded
Design WhatsApp at Scale12-design-whatsappYes14Feb 24, 2026Lecture 2026-02-24 · Deck schema v312 min
Design Notification System13-design-notification-systemYes14Feb 28, 2026Lecture 2026-02-28 · Deck schema v3Not recorded
Design Live Video Streaming14-design-live-video-streamingYes16Feb 28, 2026Lecture 2026-02-28 · Deck schema v3Not recorded
Design Distributed Cache15-design-distributed-cacheYes15Feb 24, 2026Lecture 2026-02-24 · Deck schema v315 min
Design Social Graph (TAO)16-design-social-graph-taoYes15Feb 24, 2026Lecture 2026-02-24 · Deck schema v316 min
Design Rate Limiter17-design-rate-limiterYes15Feb 24, 2026Lecture 2026-02-24 · Deck schema v316 min
Design Typeahead / Autocomplete18-design-typeahead-autocompleteYes15Feb 28, 2026Lecture 2026-02-28 · Deck schema v3Not recorded
Design Trending Topics (Top-K)19-design-trending-topics-topkYes14Feb 28, 2026Lecture 2026-02-28 · Deck schema v3Not recorded
Design Ad Click Analytics20-design-ad-click-analyticsYes13Feb 28, 2026Lecture 2026-02-28 · Deck schema v3Not recorded
Design Real-Time Ranking System21-design-realtime-rankingYes14Feb 24, 2026Lecture 2026-02-24 · Deck schema v312 min
Design Experimentation Platform22-design-experimentation-platformYes15Feb 24, 2026Lecture 2026-02-24 · Deck schema v319 min
Design WeChat Steps Ranking23-design-wechat-steps-rankingYes15Feb 28, 2026Lecture 2026-02-28 · Deck schema v3Not recorded
Product-System Design: The Meta Hybrid Question24-product-system-designYes15Feb 22, 2026Lecture 2026-02-22 · Deck schema v3Not recorded
Staff-Level Thinking (IC6)25-staff-level-thinkingYes12Feb 24, 2026Lecture 2026-02-24 · Deck schema v311 min
Tradeoff Deep Dive26-tradeoff-deep-diveYes11Feb 22, 2026Lecture 2026-02-22 · Deck schema v3Not recorded
Mock Full Meta System Design Interview27-mock-meta-interviewYes17Feb 24, 2026Lecture 2026-02-24 · Deck schema v319 min

Your Learning Path

Each module builds on the last. Take your time—the AI tutor is with you at every step.

1

M0 How Meta System Design Interviews Work — Format, rubric, levels, and what interviewers actually evaluate

Understand the Meta system design interview format: 45-minute structure, the 4 evaluation signals (Problem Exploration, Design & Architecture, Communication, Tradeoffs), how IC4/IC5/IC6 answers differ, and common mistakes that tank interviews.

12 minVideo lecture
2

M1 The Meta Design Framework — A repeatable 4-phase approach calibrated to Meta's rubric

Learn a structured framework for Meta SD interviews: Scope → Estimate → Design → Evaluate. Each phase maps directly to Meta's evaluation signals. Practice applying it to a warm-up problem.

12 minVideo lecture
3

M1 Estimation for Meta — Back-of-envelope math that impresses interviewers

Master capacity estimation for Meta-scale systems. Learn the key numbers (DAU, QPS, storage ratios), practice estimation workflows, and understand how to use estimates to drive design decisions — not just as a checkbox exercise.

12 minVideo lecture
4

F1 Consistent Hashing & Partitioning — The backbone of every distributed system at Meta scale

Master consistent hashing: the hash ring, virtual nodes, rebalancing on node add/remove, and bounded-load variants. Then connect it to real Meta use cases — Memcache shard routing, TAO partition assignment, rate limiter bucket distribution, and Kafka partition assignment.

15 minVideo lecture
5

F1 Redis — Crash Course to Advanced Patterns — From basic caching to distributed rate limiting, Top-K, and leaderboards

Redis fundamentals and advanced patterns for system design interviews. Cover data structures (strings, hashes, sorted sets, HyperLogLog, streams), persistence modes (RDB/AOF), replication and Redis Cluster, then dive into advanced use cases: distributed rate limiting (token bucket via Lua scripts), real-time Top-K (sorted sets + probabilistic structures), leaderboards, session stores, and pub/sub.

18 minVideo lecture
6

F1 Kafka & Event-Driven Architecture — The event backbone behind notifications, analytics, and real-time pipelines

Kafka fundamentals and event-driven architecture for system design interviews. Cover topics, partitions, consumer groups, offset management, and delivery guarantees (at-least-once, exactly-once). Then connect to Meta patterns: Scribe/LogDevice as Meta's Kafka equivalent, event sourcing for notifications, click-stream pipelines for ad analytics, and CDC for cache invalidation.

15 minVideo lecture
7

F1 Graph Storage & TAO Internals — How Meta stores and queries the social graph for 3 billion users

Deep dive into Meta's TAO (The Associations and Objects): the objects-and-associations data model, read-after-write consistency via cache invalidation, the MySQL + cache architecture, association queries (assoc_get, assoc_count, assoc_range), write-through caching, and cross-region replication. Builds the foundation for the Design Social Graph module.

15 minVideo lecture
8

F1 Leader Election & Distributed Coordination — ZooKeeper, Raft consensus, and coordination primitives at Meta scale

Leader election protocols and distributed coordination for system design interviews. Cover why leader election is needed, the Raft consensus algorithm (leader election, log replication, safety), ZooKeeper's coordination primitives (ephemeral nodes, watches, sequential nodes), and practical applications: Kafka controller election, distributed locks, config management, and service discovery.

15 minVideo lecture
9

M2 Design Instagram Feed — Fan-out, ranking, and serving 2 billion users their personalized feed

Design Instagram's home feed end-to-end: post ingestion, fan-out strategies (push vs pull vs hybrid), feed ranking, and timeline serving. Understand how Meta handles celebrity accounts, cold-start users, and real-time updates.

15 minVideo lecture
10

M2 Design Facebook News Feed — Aggregation, EdgeRank, and multi-source feed merging

Design the Facebook News Feed, which differs from Instagram by aggregating content from friends, pages, groups, and ads. Cover the evolution from EdgeRank to ML-based ranking, story aggregation, and the unique challenges of multi-source feeds.

15 minVideo lecture
11

M2 Design Messenger — Real-time messaging, presence, and delivery guarantees at Meta scale

Design Facebook Messenger: real-time 1:1 and group messaging, online presence, message delivery guarantees (sent/delivered/read), offline message queuing, and end-to-end encryption considerations.

15 minVideo lecture
12

M2 Design WhatsApp at Scale — E2E encryption, media delivery, and extreme engineering efficiency

Design WhatsApp, which handles 2B users with a famously small engineering team. Focus on what differentiates WhatsApp from Messenger: end-to-end encryption by default, media message handling, status/stories, and the Erlang-based backend architecture.

15 minVideo lecture
13

M2 Design Notification System — Cross-platform push delivery, deduplication, and priority ranking at Meta scale

Design Meta's notification system: real-time push delivery across iOS, Android, and web; notification ranking and priority; deduplication and rate limiting to avoid spamming users; offline queuing and batching; notification preferences and muting.

15 minVideo lecture
14

M2 Design Live Video Streaming — Real-time ingest, adaptive bitrate, and live comments at Meta scale

Design a live video streaming platform like Facebook Live / Instagram Live: real-time video ingest and transcoding, adaptive bitrate streaming, CDN distribution, live comments and reactions overlay, viewer count tracking, and recording for replay.

15 minVideo lecture
15

M3 Design Distributed Cache — Memcache at Meta scale: consistency, eviction, and thundering herds

Design a distributed caching system inspired by Meta's Memcache deployment. Cover cache topologies, consistency models, eviction strategies, thundering herd mitigation, and cross-datacenter cache invalidation.

15 minVideo lecture
16

M3 Design Social Graph (TAO) — Meta's graph database: objects, associations, and read-after-write consistency

Design a social graph storage system inspired by Meta's TAO. Cover the objects-and-associations data model, read-after-write consistency, caching graph queries, and handling the friend-of-friend query pattern at billions of nodes.

15 minVideo lecture
17

M3 Design Rate Limiter — Token buckets, sliding windows, and distributed rate limiting

Design a distributed rate limiting system for Meta's API platform. Cover rate limiting algorithms (token bucket, sliding window, fixed window), distributed coordination, per-user and per-API limits, and graceful degradation under load.

15 minVideo lecture
18

M4 Design Typeahead / Autocomplete — Low-latency prefix search and ranking at Meta scale

Design a typeahead autocomplete system for Meta search: prefix-based suggestion with sub-100ms latency, personalized ranking, multi-entity results (people, pages, groups, posts), real-time index updates, and handling of trending queries.

15 minVideo lecture
19

M4 Design Trending Topics (Top-K) — Real-time streaming aggregation and approximate counting at Meta scale

Design a trending topics system that identifies the top-K most discussed topics across Meta's platform in real time. Cover streaming aggregation, approximate counting algorithms (Count-Min Sketch, HeavyKeeper), time-windowed rankings, spam/bot filtering, and geographic trending.

15 minVideo lecture
20

M4 Design Ad Click Analytics — Real-time event aggregation, exactly-once counting, and OLAP at Meta scale

Design Meta's ad click analytics system: real-time ingestion of click/impression events, exactly-once counting for billing accuracy, multi-dimensional aggregation (by campaign, audience, geo, time), near-real-time dashboards for advertisers, and fraud detection.

15 minVideo lecture
21

M4 Design Real-Time Ranking System — Feature stores, model serving, and ranking at 100K QPS

Design a real-time ranking system for feed, search, and recommendations at Meta scale. Cover feature stores, online vs offline features, model serving infrastructure, and the candidate generation → ranking → re-ranking pipeline.

15 minVideo lecture
22

M4 Design Experimentation Platform — A/B testing, feature flags, and statistical rigor at Meta scale

Design Meta's experimentation platform (Quick Experiments / Gatekeeper). Cover experiment configuration, traffic splitting, metric collection, statistical analysis, and the challenges of running thousands of concurrent experiments without interference.

15 minVideo lecture
23

M5 Design WeChat Steps Ranking — Social leaderboards, write amplification, and friend-scoped ranking at scale

Design a daily fitness step ranking system among friends (WeChat-style). Cover data ingestion from mobile health APIs, friend-scoped leaderboard design, on-demand vs precomputed ranking tradeoffs, write amplification analysis, Redis sorted sets for real-time ranking, midnight reset strategies, anti-cheating heuristics, and privacy controls.

15 minVideo lecture
24

M5 Product-System Design: The Meta Hybrid Question — When the interviewer says 'design a feature to increase engagement' — bridging product thinking and system architecture

Meta increasingly asks hybrid questions that blend product intuition with system design. Learn the PMAS framework (Product goal → Metric → Architecture capability → System design) through three worked examples: Stories engagement, Messenger reply rate, and Marketplace trust. Understand what separates IC5 from IC6 on these questions.

14 minVideo lecture
25

M5 Staff-Level Thinking (IC6) — What separates Senior from Staff in Meta's system design interviews

Understand what Meta expects from Staff-level (IC6) system design answers. Cover driving ambiguity, quantitative tradeoff analysis, phased rollout planning, cross-team impact awareness, and demonstrating technical leadership through design decisions.

12 minVideo lecture
26

M5 Tradeoff Deep Dive — Quantitative analysis of the hard choices in system design

Deep dive into the most common system design tradeoffs with quantitative analysis. Cover consistency vs availability, latency vs throughput, storage vs computation, and how to articulate tradeoff decisions at Staff level.

12 minVideo lecture
27

M5 Mock Full Meta System Design Interview — 45-minute simulation with real-time coaching

A full 45-minute mock Meta system design interview. Sam tackles a novel problem (not covered in earlier episodes) while Dr. Wei acts as the interviewer, providing real-time coaching and IC6-level feedback at each phase.

18 minVideo lecture