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System Design

24 chapters

1System Design Basics2Vertical vs Horizontal Scaling3CAP Theorem4Load Balancers & Algorithms5Proxy Servers (Forward & Reverse)6Caching Strategies & Eviction7Content Delivery Networks (CDNs)8Database Replication9Database Sharding & Partitioning10Database Scaling & Sharding11Consistent Hashing12Choosing Databases (SQL vs NoSQL)13Message Queues (Kafka, RabbitMQ)14Microservices Architecture15API Gateways16Rate Limiting Algorithms17Long Polling vs WebSockets vs SSE18Heartbeat & Health Checks19Bloom Filters & Probabilistic Data Structures20Leader Election in Distributed Systems21Event-Driven Architecture22Distributed Locking23Circuit Breaker Pattern24Case Study: Design URL Shortener
SubjectsSystem Design

System Design Basics

Updated 2026-05-01
3 min read

System Design Basics

System Design is the process of defining the architecture, components, modules, interfaces, and data for a system to satisfy specified requirements. Unlike coding problems that test your ability to write algorithms, system design tests your ability to architect an entire application from scratch—like designing Twitter, Netflix, or Uber—to handle millions of users.

1. Why Learn System Design?

Every modern application you use daily is a massive distributed system:

  • Google Search processes over 8.5 billion queries per day.
  • Netflix serves 250 million subscribers streaming 4K video simultaneously across 190 countries.
  • WhatsApp delivers over 100 billion messages per day.

These systems cannot run on a single computer. They require hundreds of thousands of servers, sophisticated networking, intelligent caching, and redundant databases.

2. Key Characteristics of Distributed Systems

When designing a system, you must optimize for several competing properties:

Scalability

The capability of a system to grow and manage increased demand. A scalable system can continuously evolve to support growing amounts of work. A system might need to scale because of increased data volume, increased transaction count, or increased user traffic.

Reliability

The probability a system will fail in a given period. A distributed system is considered reliable if it keeps delivering its services even when one or several of its software or hardware components fail. Amazon cannot afford to have their "Add to Cart" button fail even for a millisecond during Black Friday.

Availability

The percentage of time that a system remains operational. A system with 99.999% availability ("Five Nines") has less than 5.26 minutes of downtime per year.

Efficiency

Two standard measures of efficiency: Latency (the delay to obtain the first item, measured in milliseconds) and Throughput (the number of items delivered per second). Google mandates that search results appear in under 200ms.

Maintainability

How easy is it for a team of engineers to understand, fix, and extend the system? A system that requires 20 engineers to deploy a single feature is poorly maintainable.

3. The System Design Interview Framework

When tackling any system design problem, follow this structured 4-step approach:

Step 1: Requirements Clarification (3-5 min)

Always ask clarifying questions. You must define both:

  • Functional Requirements: What should the system do? (e.g., "Users should be able to post tweets, follow other users, and view a timeline.")
  • Non-Functional Requirements: How should the system perform? (e.g., "The system should support 500 million daily active users with sub-200ms latency.")

Step 2: Back-of-the-Envelope Estimation (3-5 min)

Estimate the scale of the system to determine if you need 1 server or 10,000.

  • How many users? How many requests per second? How much storage?

Step 3: High-Level Design (10-15 min)

Draw the architecture diagram. Identify the core components: Clients, Load Balancers, Application Servers, Databases, Caches, Message Queues.

Step 4: Deep Dive (10-15 min)

Drill into the most critical components. Discuss trade-offs: SQL vs NoSQL, Sharding strategies, Caching policies, etc.



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