Skip to Content
System DesignOverview

System Design Preparation

Master the art of designing scalable, reliable, and maintainable systems. This section covers everything from high-level architecture to low-level implementation details.

Core Design Problems

High-Level Design (HLD)

In Progress

End-to-end system architecture, component design, and scalability patterns.

Rate LimiterLast Mile DeliveryMore coming...

Low-Level Design (LLD)

Complete

Object-oriented design, class diagrams, and implementation patterns.

Parking LotElevatorChess

Foundational Concepts

Distributed Systems

Complete

CAP theorem, consensus algorithms, replication, partitioning, and failure handling.

CAPRaftReplicationSharding

Databases

Complete

SQL vs NoSQL, ACID, indexing, schema design, sharding, and replication.

SQL vs NoSQLIndexingShardingACID

Caching

Complete

Cache strategies, invalidation patterns, CDN, and distributed caching.

RedisMemcachedCache-Aside

Messaging Queues

Complete

Event-driven architecture, message brokers, and stream processing.

KafkaRabbitMQSQS

Patterns & Practices

Scalability Patterns

Complete

Sharding, load balancing, horizontal scaling, and auto-scaling strategies.

Load BalancingShardingCQRS

Tradeoffs

Complete

CAP theorem, consistency vs availability, latency vs throughput decisions.

CAPPACELCConsistency Models

Case Studies

📋Planned

Real-world system design walkthroughs from top tech companies.

NetflixUberTwitter

Interview Approach

Framework for System Design Interviews

  1. Requirements Clarification (3-5 min)

    • Functional requirements: What should the system do?
    • Non-functional requirements: Scale, latency, availability
    • Constraints and assumptions
  2. High-Level Design (10-15 min)

    • Core components and their interactions
    • Data flow and API design
    • Technology choices with justification
  3. Deep Dive (15-20 min)

    • Scale one or two critical components
    • Address bottlenecks and failure modes
    • Discuss tradeoffs explicitly
  4. Wrap-up (5 min)

    • Summarize key decisions
    • Discuss future improvements
    • Address operational concerns

Key Principles

  • Start simple, then scale – Don’t over-engineer from the start
  • Quantify everything – Back of envelope calculations matter
  • Trade-offs over perfection – There’s no perfect solution
  • Think about failures – What happens when things go wrong?
Last updated on