System design interviews test your ability to design scalable systems. This comprehensive guide covers all the concepts and patterns you need to ace your interviews.
System design is the process of defining the architecture, components, and data flow of a system to satisfy specified requirements. In interviews, you're asked to design real-world systems like URL shorteners, chat apps, or video streaming platforms.
Step 1: Clarify Requirements (5 min)
Ask questions. Define scope. Understand constraints. Who are the users? What features are needed? What scale?
Step 2: High-Level Design (10 min)
Draw the big picture. Main components, how they connect, data flow. Keep it simple initially.
Step 3: Deep Dive (15-20 min)
Dive into critical components. Database schema, caching strategy, scaling approach. Show depth.
Step 4: Trade-offs & Wrap-up (5 min)
Discuss trade-offs, bottlenecks, and future improvements. Show awareness of limitations.
| Aspect | Vertical (Scale Up) | Horizontal (Scale Out) |
|---|---|---|
| Method | Bigger server | More servers |
| Cost | Expensive at scale | Cost-effective |
| Limit | Hardware ceiling | Virtually unlimited |
| Complexity | Simpler | More complex |
| Downtime | Required for upgrade | Zero downtime possible |
Estimate scale to inform design decisions:
| Factor | SQL (PostgreSQL, MySQL) | NoSQL (MongoDB, DynamoDB) |
|---|---|---|
| Schema | Fixed, structured | Flexible, schemaless |
| Relationships | Excellent (JOINs) | Denormalized |
| Scaling | Vertical (harder horizontal) | Horizontal (built-in) |
| ACID | Strong | Eventual consistency |
| Best For | Transactions, complex queries | High write volume, flexibility |
Distributed systems can only guarantee 2 of 3:
In practice, you must tolerate partitions, so choose between consistency (CP) or availability (AP).
Caching reduces database load and improves response times. It's essential for any high-scale system.
Cache-Aside (Lazy Loading)
App checks cache first. If miss, fetch from DB and update cache. Most common pattern.
Write-Through
Write to cache and DB together. Data in cache is always fresh. Higher write latency.
Write-Behind
Write to cache immediately, async write to DB. Fast writes but risk of data loss.
Load balancers distribute traffic across multiple servers for reliability and scalability.
| Factor | L4 (Transport) | L7 (Application) |
|---|---|---|
| Routes by | IP + Port | HTTP headers, URL, cookies |
| Speed | Faster | Slower (more processing) |
| Flexibility | Limited | Highly flexible |
| Scenario | Recommended |
|---|---|
| Small team, MVP | Monolith |
| Large scale, many teams | Microservices |
| Need independent scaling | Microservices |
| Quick iteration needed | Monolith |
Message queues enable async communication between services. Essential for decoupling and reliability.
Key Components:
Key Components:
Key Components:
Key Components:
System design interviews test your ability to think architecturally. With practice and understanding of core concepts, you can design systems that serve millions of users.
Master the framework, learn the building blocks, and practice regularly. The ability to design scalable systems is what separates senior engineers from juniors.
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