System Design Interview - Volume 2

System Design Interview Framework

Follow a structured approach: Use a consistent framework for all system design interviews
Start with requirements clarification: Begin by clarifying functional and non-functional requirements
Establish constraints and assumptions: Define system constraints and make reasonable assumptions
Calculate system scale: Estimate traffic, storage, bandwidth, and other relevant metrics
Define APIs: Design clear and intuitive APIs early in the process
Design high-level architecture: Create a high-level design before diving into details
Design detailed components: Elaborate on the key components identified in the high-level design
Identify potential bottlenecks: Proactively discuss system bottlenecks and limitations
Propose scaling strategies: Suggest ways to scale the system as requirements grow
Make trade-offs explicit: Clearly articulate trade-offs made in your design decisions

Design a Rate Limiter

Understand rate limiting purposes: Recognize the importance of preventing abuse, managing resource usage, and controlling costs
Choose appropriate algorithms: Select suitable rate limiting algorithms (token bucket, leaky bucket, fixed window, sliding window)
Determine rate limiting granularity: Decide whether to limit by IP, user, API endpoint, or other dimensions
Design for distributed systems: Create a rate limiter that works effectively across multiple servers
Implement consistent enforcement: Ensure consistent rate limiting in distributed environments
Handle edge cases: Consider clock drift, synchronization issues, and other edge cases
Make rate limiting observable: Design for monitoring and alerting on rate limiting events
Create graceful degradation: Implement strategies for what happens when limits are reached
Minimize performance impact: Ensure rate limiting doesn’t significantly impact system performance
Design for configurability: Allow for easy adjustment of rate limiting parameters

Design a Distributed Message Queue

Understand message queue use cases: Recognize when to use a message queue for decoupling, buffering, and asynchronous processing
Choose appropriate delivery semantics: Design for at-least-once, at-most-once, or exactly-once delivery as needed
Ensure message durability: Implement strategies to prevent message loss during failures
Design for high throughput: Optimize the queue for high message processing rates
Implement efficient scaling: Create a design that scales horizontally with increasing load
Balance producer and consumer speeds: Handle scenarios where producers and consumers operate at different speeds
Design effective partitioning: Create a partitioning strategy that distributes messages efficiently
Implement proper ordering guarantees: Design for message ordering requirements (global or partition-level)
Create resilient failure handling: Implement strategies for handling node failures and network partitions
Optimize for different workload patterns: Consider different message sizes, frequencies, and consumption patterns

Design a URL Shortener

Generate unique short URLs: Create an efficient algorithm for generating short, unique identifiers
Design for high availability: Ensure the system remains available during component failures
Optimize for read performance: Design for extremely fast URL lookups
Create an efficient storage strategy: Select appropriate storage systems for short URL mappings
Implement analytics capabilities: Design features to track click statistics and usage patterns
Handle custom short URLs: Support user-defined custom short URLs when requested
Prevent abuse: Implement mechanisms to prevent abuse and spam
Design for scalability: Create a system that can handle billions of URLs and redirects
Optimize for global performance: Design for low latency access across global regions
Implement proper error handling: Create strategies for handling expired or invalid URLs

Design a Web Crawler

Define clear crawling policies: Establish rules for what to crawl, how often, and how deeply
Respect robots.txt: Design the crawler to follow robots.txt guidelines
Implement politeness policies: Avoid overloading target websites with too many requests
Create an efficient URL frontier: Design a system to manage URLs to be crawled
Implement duplicate detection: Avoid crawling the same content multiple times
Design content extraction: Create systems to extract and process relevant content
Implement proper storage: Design storage systems for the various types of crawled data
Create a distributed architecture: Scale the crawler across multiple machines
Implement fault tolerance: Design for resilience against failures and crashes
Handle diverse content types: Create strategies for different content types and formats

Design a Notification System

Support multiple notification channels: Design for push notifications, SMS, email, and in-app notifications
Create reliable delivery: Ensure notifications are delivered reliably across all channels
Implement priority levels: Design a system that handles different notification priorities
Create user preferences management: Allow users to control what notifications they receive
Design for global scale: Create a system that works across different regions and time zones
Optimize for high throughput: Handle millions of notifications efficiently
Implement rate limiting: Prevent overwhelming users with too many notifications
Design for observability: Create comprehensive monitoring and alerting
Implement retry mechanisms: Handle failures in notification delivery gracefully
Create personalization capabilities: Support personalized content in notifications

Design a News Feed System

Define clear feed composition rules: Establish how posts are selected and ranked in the feed
Create efficient content delivery: Design for fast feed loading and updates
Implement intelligent caching: Cache feeds and feed components appropriately
Design for feed personalization: Create systems that personalize feeds based on user interests
Optimize read path performance: Ensure extremely fast feed retrieval
Balance freshness and performance: Find the right balance between updating feeds and system load
Design for content diversity: Ensure feeds aren’t dominated by a single content source
Implement proper fan-out strategies: Choose between push, pull, or hybrid approaches for feed updates
Handle high-profile users: Create special strategies for users with many followers
Design for different content types: Support various media types in the feed

Design a Chat System

Ensure message delivery reliability: Design for reliable message delivery across devices
Implement real-time capabilities: Create low-latency message delivery systems
Support offline messaging: Handle message delivery to offline users
Design for message ordering: Ensure proper ordering of messages
Implement group chat capabilities: Design efficient group messaging features
Create presence indicators: Implement online/offline status and typing indicators
Design for message synchronization: Synchronize messages across multiple devices
Implement media sharing: Support sharing of images, videos, and other media
Design for message storage: Create efficient storage for message history
Ensure end-to-end security: Implement proper encryption and security measures

Design a Search Autocomplete System

Create efficient prefix matching: Design fast algorithms for matching user input prefixes
Implement personalized suggestions: Tailor suggestions based on user history and preferences
Design for real-time updates: Update suggestions based on trending topics and changes
Optimize for low latency: Ensure extremely fast suggestion generation
Create an effective ranking system: Rank suggestions based on relevance and popularity
Implement error tolerance: Handle misspellings and typos gracefully
Design for multi-language support: Support autocomplete across different languages
Create efficient storage: Store suggestion data in optimized data structures
Implement caching strategies: Cache suggestions for common prefixes
Design for continuous improvement: Create systems to learn from user selections

Design Google Maps

Implement efficient routing algorithms: Design algorithms for finding optimal routes
Create effective map data storage: Store massive geographical data efficiently
Design for location tracking: Implement accurate real-time location tracking
Optimize for low latency: Ensure fast response times for map interactions
Implement traffic prediction: Design systems to predict and display traffic conditions
Create efficient geocoding: Convert addresses to coordinates and vice versa quickly
Design for offline capabilities: Allow basic functionality without internet connection
Implement point of interest search: Create fast and relevant POI search functionality
Design for different zoom levels: Support efficient rendering at various zoom levels
Create turn-by-turn navigation: Implement reliable real-time navigation features

Design a Distributed Key-Value Store

Ensure data consistency: Design appropriate consistency models for different use cases
Implement efficient data partitioning: Create strategies for distributing data across nodes
Design for high availability: Ensure the system remains available during failures
Create effective replication: Implement data replication for reliability and performance
Design for scalability: Allow horizontal scaling as data volume grows
Implement proper failure detection: Detect and handle node failures quickly
Create efficient read/write paths: Optimize both read and write operations
Design effective data structures: Choose appropriate on-disk and in-memory data structures
Implement proper conflict resolution: Handle conflicts when they occur in distributed operations
Create comprehensive monitoring: Design for observability and troubleshooting

Design a Distributed Search Engine

Implement efficient indexing: Create fast and memory-efficient indexing mechanisms
Design for relevance ranking: Implement algorithms for ranking search results by relevance
Create effective query processing: Design systems to process complex queries quickly
Implement distributed indexing: Distribute indexing work across multiple machines
Design for low latency searches: Ensure fast response times for user queries
Create index partitioning strategies: Distribute the index effectively across machines
Implement fault tolerance: Handle node failures gracefully
Design for result caching: Cache common search results for improved performance
Create query understanding systems: Interpret user intent from search queries
Implement result diversification: Present diverse results rather than similar ones

Key Takeaways

Follow a structured approach: Use a consistent framework for system design that includes requirements, constraints, high-level design, and detailed components
Calculate system scale: Estimate key metrics like queries per second, storage needs, and bandwidth requirements to inform your design
Make trade-offs explicit: Clearly articulate the trade-offs in your design decisions and why you made them
Design for scalability: Create systems that can scale horizontally as load increases
Ensure high availability: Implement redundancy and fault tolerance to maintain service during failures
Optimize for performance: Design for low latency and high throughput in your core operations
Implement proper data partitioning: Create effective strategies for distributing data across multiple nodes
Design for global distribution: Consider the challenges of globally distributed systems when relevant
Address security concerns: Include security considerations in your design where appropriate
Create observability: Design for monitoring, debugging, and understanding system behavior