Module 7: Review & Cheat Sheet
🧠 Interactive Flashcards
Test your knowledge. Click a card to reveal the answer.
📝 System Design Cheat Sheet
Scaling Patterns
| Pattern | Concept | Use Case | Trade-off | | :— | :— | :— | :— | | Vertical (Scale Up) | Bigger Hardware | Startups, Monoliths | NUMA Bottleneck, High Cost | | Horizontal (Scale Out) | More Nodes | Big Tech, Stateless Apps | Network Overhead, Complexity | | Sharding | Partition Data | massive DBs (>5TB) | Hot Partitions, No Joins | | Virtual Buckets | Indirection Layer | Couchbase, Cassandra | Complex Mapping Logic |
Theorems & Models
| Model | Key Idea |
| :— | :— |
| CAP | Pick 2: Consistency, Availability, Partition Tolerance (Always Pick P). |
| PACELC | Extends CAP. “Else” (Healthy) -> Latency vs Consistency. |
| Spanner TrueTime | Uses Atomic Clocks to minimize uncertainty window (<7ms). |
| Quorum | R + W > N guarantees overlap (Strong Consistency). |
Replication & Consistency
| Type | Speed | Durability | Cons | | :— | :— | :— | :— | | Chain Replication | Medium | High (All nodes ack) | High Latency (Tail latency) | | Async | Fast | Low (Risk of Data Loss) | Replication Lag | | Read Repair | N/A | High (Self-healing) | Extra Read Overhead | | Sloppy Quorum | Fast | Medium (Hinted Handoff) | Possible Data Loss |
🕵️ Scenario Quiz
🔗 Next Steps
You have mastered Data Scaling. Now, let’s move to Module 8: Messaging & Async Communication to learn how to decouple these systems using Queues and Event Streams.