System Design Interview Questions
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Introduction to High-Level System Design
System Design Fundamentals
- Functional vs. Non-Functional Requirements
- Scalability, Availability, and Reliability
- Latency and Throughput Considerations
- Load Balancing Strategies
Architectural Patterns
- Monolithic vs. Microservices Architecture
- Layered Architecture
- Event-Driven Architecture
- Serverless Architecture
- Model-View-Controller (MVC) Pattern
- CQRS (Command Query Responsibility Segregation)
Scaling Strategies
- Vertical Scaling vs. Horizontal Scaling
- Sharding and Partitioning
- Data Replication and Consistency Models
- Load Balancing Strategies
- CDN and Edge Computing
Database Design in HLD
- SQL vs. NoSQL Databases
- CAP Theorem and its Impact on System Design
- Database Indexing and Query Optimization
- Database Sharding and Partitioning
- Replication Strategies
API Design and Communication
Caching Strategies
- Types of Caching
- Cache Invalidation Strategies
- Redis vs. Memcached
- Cache-Aside, Write-Through, and Write-Behind Strategies
Message Queues and Event-Driven Systems
- Kafka vs. RabbitMQ vs. SQS
- Pub-Sub vs. Point-to-Point Messaging
- Handling Asynchronous Workloads
- Eventual Consistency in Distributed Systems
Security in System Design
Observability and Monitoring
- Logging Strategies (ELK Stack, Prometheus, Grafana)
- API Security Best Practices
- Secure Data Storage and Access Control
- DDoS Protection and Rate Limiting
Real-World System Design Case Studies
- Distributed locking (Locking and its Types)
- Memory leaks and Out of memory issues
- HLD of YouTube
- HLD of WhatsApp
How Video Streaming Platforms Like YouTube Handle Millions of Users
Introduction
Ever wondered how platforms like YouTube seamlessly deliver high-quality video content to millions of users worldwide? The engineering behind video streaming is a marvel of modern computing, involving content delivery networks (CDNs), load balancing, adaptive bitrate streaming, and complex caching mechanisms. If you are interested in learning more about how such massive-scale systems work, we invite you to sign up for our free course on system design here.
Also Read: Top 10 Distributed System Design Challenges
Content Delivery Networks (CDNs): The Backbone of Video Streaming
What are CDNs?
Content Delivery Networks (CDNs) are globally distributed networks of servers that cache and deliver video content closer to users. This reduces latency and enhances streaming speed.
How CDNs Work in Video Streaming
CDNs ensure that videos are replicated across multiple data centers worldwide. When a user clicks on a video, they are connected to the nearest CDN node, reducing load on the central servers
Benefits of CDNs
- Reduced Latency: Ensures quick content delivery
- Load Distribution: Prevents central server overload
- Improved Reliability: Maintains uptime even during high traffic
- Efficient Bandwidth Usage: Lowers costs for streaming platforms
|
Feature |
Benefit for Video Streaming |
|
Reduced Latency |
Faster video load times |
|
Load Balancing |
Distributes traffic evenly |
|
Redundancy |
Increases system reliability |
Load Balancing: Handling Massive User Traffic
Why Load Balancing is Essential
With millions of users accessing videos simultaneously, load balancers distribute traffic among multiple servers, ensuring no single machine is overwhelmed.
Load Balancing Techniques Used in Streaming
- Round Robin Load Balancing: Distributes traffic sequentially across servers.
- Least Connections Load Balancing: Directs new requests to the server with the fewest active connections.
- Geo-Load Balancing: Routes users to the closest server for better performance.
How Load Balancing Enhances Streaming Quality
- Prevents server crashes during traffic spikes
- Ensures consistent streaming speeds
- Reduces buffering and video lag
- Improves fault tolerance
Also Read: Roadmap to Crack Startup Design Interviews
Adaptive Bitrate Streaming: Ensuring Smooth Playback
How Adaptive Bitrate Streaming Works
Adaptive Bitrate (ABR) streaming dynamically adjusts video quality based on network speed and device capability, ensuring users get the best possible experience.
Types of Adaptive Bitrate Streaming
- Progressive Download: Downloads video in chunks and adjusts quality accordingly.
- HTTP Live Streaming (HLS): Uses segmented video files to optimize performance.
- Dynamic Adaptive Streaming over HTTP (DASH): Modern standard for real-time video quality adjustments.
Advantages of ABR Streaming
- Prevents buffering by adjusting quality dynamically
- Optimizes bandwidth usage to avoid excess data consumption
- Enhances user experience by ensuring smooth playback
Also Read: Top 10 Cloud App Design Questions
Video Caching: Speeding Up Content Delivery
The Role of Caching in Video Streaming
Caching stores frequently accessed video segments closer to users to reduce latency and improve streaming performance.
Types of Caching Used by YouTube
- Edge Caching: Stores popular videos at CDN edge servers
- Client-Side Caching: Temporarily saves video data on users’ devices
- Proxy Caching: Caches content at network nodes to serve multiple users efficiently
Benefits of Caching in Video Streaming
- Reduces repeated data fetching
- Minimizes load on origin servers
- Enhances video start-up time
Also Read: Instagram: Low-Level Design Guide
Video Encoding & Compression: Reducing Bandwidth Usage
What is Video Encoding?
Video encoding compresses raw video files into formats that can be efficiently transmitted over the internet without quality loss.
Common Video Encoding Standards
- H.264: Most widely used, balances quality and compression
- VP9: Google’s high-efficiency codec for YouTube
- AV1: Advanced open-source codec for superior compression
Why Video Compression is Important
- Reduces file sizes without degrading quality
- Minimizes buffering by optimizing bandwidth usage
- Speeds up streaming by lowering data transmission requirements
Also Read: Top 10 API Design Questions from Companies
Scalability & Fault Tolerance in Video Streaming Platforms
How YouTube Scales to Handle Millions of Users
YouTube’s architecture is designed to scale horizontally, meaning new servers can be added dynamically to handle increased traffic.
Fault Tolerance Strategies
- Data Replication: Ensures multiple copies of videos exist across servers
- Microservices Architecture: Decouples services to prevent total failures
- Redundant Data Centers: Prevents outages by routing traffic elsewhere
Why Scalability Matters
- Handles growing traffic effortlessly
- Reduces risk of downtime
- Improves overall performance
Also Read: Ultimate Guide to DSA & Design in 2025
How does YouTube manage high traffic without crashing?
YouTube leverages CDNs (Content Delivery Networks), load balancing, and distributed databases to distribute traffic efficiently and prevent downtime. If you want to learn more about handling large-scale traffic and system design, check out this Master DSA, Web Dev & System Design Course.
How does YouTube manage high traffic without crashing?
YouTube leverages CDNs (Content Delivery Networks), load balancing, and distributed databases to distribute traffic efficiently and prevent downtime. If you want to learn more about handling large-scale traffic and system design, check out this Master DSA, Web Dev & System Design Course.
How does YouTube manage high traffic without crashing?
YouTube leverages CDNs (Content Delivery Networks), load balancing, and distributed databases to distribute traffic efficiently and prevent downtime. If you want to learn more about handling large-scale traffic and system design, check out this Master DSA, Web Dev & System Design Course.
How does YouTube manage high traffic without crashing?
YouTube leverages CDNs (Content Delivery Networks), load balancing, and distributed databases to distribute traffic efficiently and prevent downtime. If you want to learn more about handling large-scale traffic and system design, check out this Master DSA, Web Dev & System Design Course.
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