Preparation for System Design Interview

System Fundamentals to Know

Refreshing your fundamentals is an important step in preparation.

• Storage

• Scalability

• Networking

• Latency, Throughput & Performance

• Fault Tolerance & Redundancy

• CAP Theorem

Core Components to Know

Familiarize yourself with common system components:

• Server

• Database: Specific examples include PostgreSQL and DynamoDB

• Cache: Specific examples include Redis

• Message Queue: Specific examples include Kafka

• Load Balancer

• Blob Storage

• CDN

Common Problems to Practice

Practice common problems to solidify your understanding:

• Design a URL Shortener (Bitly): Tests understanding of hashing, databases, and caching.

• Design Dropbox: Tests file storage, synchronization, and metadata management.

• Design Ticketmaster: Tests concurrency, race conditions, and transactional integrity.

• Design a News Feed: Tests content delivery, personalization, and real-time updates.

• Design WhatsApp: Tests real-time communication, presence detection, and message delivery.

• Design LeetCode: Tests code execution environments, scaling compute, and security.

• Design Uber: Tests geospatial indexing, matching algorithms, and real-time updates.

• Design a Web Crawler: Tests distributed systems, scheduling, and politeness policies.

• Design an Ad Click Aggregator: Tests high-throughput event processing and analytics.

• Design Facebook's Post Search: Tests indexing, ranking, and search optimization.

Design a URL Shortener (Bitly): Tests understanding of hashing, databases, and caching.

A URL shortener like Bitly requires a system to efficiently store, retrieve, and redirect web addresses. Key components include a hashing algorithm for generating unique short codes, a database to store the mappings, and a caching system for fast lookups.

1. Hashing (Short Code Generation)

The core challenge is creating a short, unique, and collision-resistant code for each long URL.

• Hashing Algorithm: Base62 encoding is commonly used to generate compact codes because it includes 62 characters (A-Z, a-z, 0-9), meaning a 6-character code can represent

  billion unique URLs.

• Collision Resolution: A simple counter can be used, encoded in Base62. If two users submit the same long URL, the system returns the existing short URL. If two different long URLs somehow generate the same hash (a collision), append a salt or use a different hash value.

2. Database Design

A NoSQL database (like Cassandra or DynamoDB) or a relational database (like PostgreSQL or MySQL) can be used.

Example:

Short Code (Primary Key) Long URL Creation Date Click Count

aBcDeF https://verylongurl.com... 2026-02-11 1245

The Short Code is the primary key for rapid retrieval.

3. Caching and Retrieval

To handle high traffic volume, a caching layer is essential to avoid hitting the database for every single request.

• Caching Strategy: A distributed cache like Redis or Memcached sits in front of the database.

• Workflow:

  1. A user requests the long URL associated with https://bitly.com.

  2. The application checks the cache for aBcDeF.

  3. Cache Hit: If found, the long URL is returned immediately for redirection.

  4. Cache Miss: The application queries the database. The result is then stored in the cache (e.g., using a Write-Through or Lazy Loading approach) and the long URL is returned.

4. System Architecture

The overall architecture involves:

• Web Servers: Handle client requests for redirection (GET requests) and creation of new short URLs (POST requests).

• Load Balancer: Distributes incoming traffic across multiple web servers for scalability and reliability.

• Analytics Service: Processes clicks asynchronously to update analytics (click counts, user location, etc.) without slowing down the primary redirection service.

By using this design, the system achieves high availability, low latency for redirection, and efficient storage of mappings.

Design Dropbox: Tests file storage, synchronization, and metadata management.

The design process through several key phases:

• Requirements: Clarifying both functional (e.g., file upload/download, sharing, sync across devices) and non-functional (e.g., high availability, durability, low latency, security) requirements for a cloud storage service.

• Core Entities & APIs: Defining the fundamental components and interfaces of the system.

• High-Level Design: Outlining the overall architecture, often separating metadata storage from actual file storage (data plane and control plane separation).

• Deep Dives: Exploring complex challenges and solutions for specific aspects of the system, including:

  • Large Files & Resumable Uploads: Using client-side chunking, multipart uploads, and checksums to handle large files efficiently. This approach allows for retries by only re-uploading missing parts and uses short-lived pre-signed URLs for direct uploads to object storage, bypassing application servers.

  • Real-Time Synchronization: Implementing near real-time sync across devices using durable event logs, webSockets for notifications, and per-device cursors to fetch incremental changes (deltas).

  • Downloads & Bandwidth: Leveraging Content Delivery Networks (CDNs), signed URLs, and rate limits to scale downloads and manage costs.

  • Conflict Resolution: Managing offline edits and concurrent changes using versioned metadata, atomic operations for moves/renames, and strategies like "last-writer-wins" or automatic conflicted copies.