30-Day FAANG System Design Curriculum
Structured progression: Foundations → Data & Storage → Scaling → Reliability → Advanced → Case Studies.
Each topic maps to one day (~60 min). Order matters — later topics assume earlier ones.
Phase 1 — Foundations (Days 1–7)
| Day | Topic | Why it matters |
|---|---|---|
| 1 | Client-Server model, HTTP/HTTPS, DNS | Every design starts here |
| 2 | Latency, Throughput, and "Numbers every engineer knows" | Back-of-envelope math is a FAANG staple |
| 3 | TCP vs UDP, WebSockets, Long Polling, SSE | Choosing the right transport |
| 4 | Load Balancers (L4 vs L7, algorithms, health checks) | Nearly every design uses one |
| 5 | Caching fundamentals (client, CDN, app, DB) | Biggest lever for latency & scale |
| 6 | Cache strategies (write-through, write-back, TTL, eviction) | Depth on caching wins interviews |
| 7 | Content Delivery Networks (CDN) deep dive | Static/dynamic content, edge caching |
Phase 2 — Data & Storage (Days 8–14)
| Day | Topic | Why it matters |
|---|---|---|
| 8 | SQL vs NoSQL — when to pick which | The single most-asked trade-off |
| 9 | ACID vs BASE, Isolation levels | Data correctness under load |
| 10 | Indexing (B-tree, LSM-tree, hash indexes) | Query performance |
| 11 | Replication (leader-follower, multi-leader, leaderless) | High availability & read scaling |
| 12 | Sharding / Partitioning (range, hash, directory) | Horizontal scale |
| 13 | Consistent Hashing | Foundation for distributed caches, DBs, LBs |
| 14 | Data warehousing basics (OLTP vs OLAP, columnar stores) | Analytics vs transactions |
Phase 3 — Distributed Systems (Days 15–21)
| Day | Topic | Why it matters |
|---|---|---|
| 15 | CAP theorem & PACELC | The mental model for every distributed choice |
| 16 | Consistency models (strong, eventual, causal, read-your-writes) | Nuance that separates senior candidates |
| 17 | Message queues & event streaming (Kafka, SQS, RabbitMQ) | Async architectures |
| 18 | Pub/Sub patterns & fan-out | Notifications, feeds, real-time |
| 19 | Consensus overview (Raft/Paxos at a high level) | Understanding coordination |
| 20 | Distributed transactions (2PC, Sagas, Outbox) | Cross-service correctness |
| 21 | Idempotency, retries, exactly-once semantics | Reliability under failure |
Phase 4 — API, Reliability & Ops (Days 22–25)
| Day | Topic | Why it matters |
|---|---|---|
| 22 | API design: REST vs gRPC vs GraphQL | Interface choices |
| 23 | Rate limiting algorithms (token bucket, leaky bucket, sliding window) | Classic mini-design question |
| 24 | Observability: metrics, logging, tracing | Ops maturity signal |
| 25 | Auth & security (OAuth2, JWT, TLS, encryption at rest) | Bare-minimum expected knowledge |
Phase 5 — FAANG Case Studies (Days 26–30)
| Day | Case Study | Focus |
|---|---|---|
| 26 | Design a URL Shortener (bit.ly) | Hashing, key generation, DB choice, caching, analytics |
| 27 | Design a Rate Limiter | Algorithms, distributed state, Redis |
| 28 | Design Twitter/News Feed | Fan-out on write vs read, caching, timelines |
| 29 | Design WhatsApp / Chat | WebSockets, message delivery, ordering, storage |
| 30 | Design YouTube / Video Streaming | CDN, chunked storage, transcoding pipelines |
Post-30 (bonus deep dives — unlocked after Day 30)
- Design Uber / Ride-hailing (geospatial, matching)
- Design Instagram (media pipeline, feed)
- Design Dropbox / Google Drive (block storage, sync)
- Design Google Docs (CRDTs, OT, real-time collab)
- Design a Distributed Search Engine
- Design Netflix (CDN, recommendations, adaptive bitrate)
- Design a Payment System (idempotency, ledger, reconciliation)
Spaced repetition rule
Any topic where diagnostic/quiz score is < 70% gets re-quizzed on Day+3 and Day+10.