System Design

Design large-scale, distributed systems. Learn architectural principles, scalability patterns, and trade-offs for building systems that serve millions of users.

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Topics

Fundamentals

Scalability - Load Balancing - Caching - Database Sharding - Replication - Consistency
System design basics: horizontal vs. vertical scaling, load distribution, data partitioning, consistency models (ACID, BASE, CAP theorem), trade-offs between availability and consistency.

Building Blocks

Load Balancers - Caches - Databases - Message Queues - CDN - Rate Limiting - API Gateways
Core components: when to use each, configuration patterns, failure modes, monitoring, cost-benefit analysis, integration strategies.

Scalability & Resilience

Auto-scaling - Circuit Breakers - Timeouts - Retries - Bulkhead - Failover - Graceful Degradation
Building resilient systems: handling failures, recovery strategies, monitoring metrics (latency, throughput, error rates), alerting, chaos engineering.

Worked Examples

Twitter - YouTube - Uber - Payment System - Notification Service - Case Studies
Real-world system design examples: problem breakdown, architecture evolution, component interactions, trade-off decisions, estimated capacity calculations.

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Quick Interview Prep

System design interview flow: 1. Clarify requirements (functional + non-functional) 2. Estimate scale (users, QPS, storage, bandwidth) 3. High-level architecture (APIs, components, databases) 4. Deep-dive components (caching, queues, replication, partitioning) 5. Identify bottlenecks & scaling strategies 6. Discuss trade-offs (consistency, latency, cost)

Key metrics to estimate: - QPS (queries per second), P99 latency, storage requirements - Bandwidth, concurrent connections, cache hit ratio