Course Content
Low Level System Design
LLD Topics
High Level System Design
Low & High Level System Design
1. Traffic Load Estimation

Global Reach:

 

  • YouTube has over 2 billion logged-in users each month and handles billions of hours of video watched daily.

 

  • Netflix has over 230 million subscribers globally, streaming hours of content each day.

 

  • The platforms must manage millions of concurrent users who are watching videos, uploading content, or browsing.

 

Peak Usage Times:

 

  • Both platforms experience traffic spikes during peak hours, typically in the evenings and weekends, or when new content (e.g., Netflix Originals) is released.

 

  • Traffic spikes during special events or viral trends can also cause short-term surges in demand.

 

Capacity Estimation:

 

  • The system must handle billions of requests per second (e.g., for starting a stream, pausing, skipping, and searching).

 

  • Netflix may need to serve multi-terabyte data during a busy weekend or holiday season.

 

  • YouTube processes petabytes of data daily for video uploads, views, and interactions.

 

2. Storage Requirements

Massive Data Volumes:

 

  • Both platforms need to store massive video files—for instance, Netflix’s library includes millions of hours of content, while YouTube hosts billions of videos.

 

  • YouTube needs to store videos, thumbnails, metadata, and user interactions (likes, comments, etc.).

 

  • Netflix stores video content in multiple resolutions (e.g., SD, HD, 4K) to serve users with varying internet speeds and devices.

 

Storage Estimation:

 

  • YouTube: Over 500 hours of video uploaded every minute (equivalent to several petabytes of data each day).

 

  • Netflix: Needs to store hundreds of petabytes of content to serve different regions and streaming quality.

 

Video Formats and Compression:

 

  • Videos must be stored in multiple formats and resolutions (e.g., 4K, HD, SD) to ensure compatibility with different devices and network speeds.

 

  • Efficient video compression techniques are essential to reduce storage overhead and ensure smooth streaming.


3. Bandwidth and Network Constraints

High Bandwidth Needs:

 

  • Streaming platforms like YouTube and Netflix require high-bandwidth connections for smooth playback.

 

  • Video streams, especially in HD or 4K, demand significant network resources—each 4K video can consume 25 Mbps or more.

 

Bandwidth Estimation:

 

  • For Netflix, a typical 4K stream may require 15-25 Mbps of bandwidth, HD requires 5-10 Mbps, and SD requires only 1-3 Mbps.

 

  • Global distribution of content must be optimized to handle traffic from users across different continents with varying internet speeds.

 

Content Delivery Networks (CDNs):

 

  • CDNs are crucial for efficient content delivery, ensuring that videos are served from servers geographically close to the users to minimize latency.

 

  • CDNs also help to distribute the load during traffic spikes and reduce server load.


4. System Constraints

Storage Costs:

 

  • Storing petabytes of data comes at a high cost. Both platforms use cloud-based storage solutions (e.g., AWS for YouTube, AWS and Google Cloud for Netflix), but optimizing storage costs is crucial.

 

  • The use of efficient data encoding (such as H.264 or H.265 compression for video) and tiered storage systems (hot vs cold storage) helps reduce costs.

 

Content Delivery Efficiency:

 

  • Efficiently delivering high-quality video content to millions of users without causing congestion or quality degradation is challenging.

 

  • Factors like latency, buffering, and load balancing need to be managed efficiently.

 

Server Resources and Compute Power:

 

  • Streaming requires massive server infrastructure for content encoding, decoding, and real-time playback.

 

  • Servers need to be able to handle millions of concurrent streams and facilitate real-time data analytics, user interactions (likes, comments), and recommendations.

 

Compute Estimation:

 

  • Platforms like Netflix and YouTube use cloud services for elastic compute scaling to handle high demand.

 

  • Transcoding (converting videos into multiple formats) is a compute-intensive process. On-demand transcoding during peak traffic times needs careful management.


5. Database and Data Constraints

Large-Scale Data Management:

 

  • Both platforms require databases to store user data, video metadata, ratings, and interaction data.

 

  • The database system must support rapid reads and writes due to the large volume of concurrent user interactions.

 

  • Replication and partitioning of databases are needed to ensure performance, availability, and scalability.

 

Database Estimation:

 

  • Each platform may use millions of database queries per second (e.g., searching for videos, recommendations, user preferences).

 

  • The system must support high availability with low-latency reads (e.g., retrieving the list of recommended videos) and eventual consistency for background data synchronization.

 

6. Fault Tolerance and Redundancy

Failover Systems: 

 

  • Both platforms require highly redundant infrastructure to ensure that a failure in one region doesn’t affect global availability.

 

  • Automatic failover mechanisms should redirect traffic to healthy servers or data centers in case of failure, maintaining service continuity.

 

Backup and Disaster Recovery:

 

  • Data backup systems must ensure that data is not lost during system crashes or data center outages.

 

  • Disaster recovery solutions are critical for fast recovery in case of catastrophic failures.


7. Legal and Regulatory Constraints

Data Sovereignty and Content Licensing:

 

  • Different countries have different regulations regarding data privacy (e.g., GDPR in Europe), which impacts storage and data processing practices.

 

  • Both platforms must comply with regional content licensing agreements, limiting where and how certain videos or content can be distributed.

Estimation:

 

  • Content stored and processed in certain regions might need to be duplicated or stored locally to comply with data sovereignty laws.


8. Cost Management Constraints

Storage and Network Costs:
The cost of serving billions of users and streaming high-quality content is significant. Both platforms need to efficiently manage their infrastructure costs.

 

  • Use of cloud storage is scalable, but expensive in the long run, especially when dealing with petabytes of data.

 

  • Peering agreements with ISPs and efficient data routing are important for minimizing costs in terms of network infrastructure.

 

Summary of Capacity Estimations & Constraints:

 

Category Estimation/Constraint
Traffic Load Billions of requests per second from global users.
Storage Petabytes of data for videos, metadata, and user data.
Bandwidth High bandwidth needs—4K streams: 15-25 Mbps per user.
Network & CDN Distributed via CDNs for efficient global delivery.
Compute Elastic compute resources to handle transcoding and real-time processing.
Database Millions of queries per second, partitioned and replicated databases.
Fault Tolerance Redundant systems, automatic failover, and disaster recovery.
Legal/Regulatory Compliance with data sovereignty, content licensing.
Cost Management Cloud storage costs and network peering agreements.
0% Complete
WhatsApp Icon

Hi Instagram Fam!
Get a FREE Cheat Sheet on System Design.

Hi LinkedIn Fam!
Get a FREE Cheat Sheet on System Design

Loved Our YouTube Videos? Get a FREE Cheat Sheet on System Design.