System Design Interview: Design Netflix

Summary

In this Exponent mock interview, Andreas, a software engineer at Modern Health, is tasked with designing Netflix's core system for handling users and video content. The focus is on aggregating and processing user activity data to support the recommendation engine, while ensuring high availability and low latency. Andreas discusses various technical aspects, including data storage, caching, and content delivery using a CDN. He also touches on scaling considerations for 200 million users. The session concludes with feedback on his approach, highlighting the importance of balancing user experience and technical trade-offs.

Takeaways

• 😀 Exponent offers online courses, expert coaching, and peer-to-peer mock interviews to help people get their dream tech careers.
• 💼 Andreas, the interviewee, is a software engineer at Modern Health, a mental health tech startup.
• 🎬 The design challenge focuses on the core functionality of Netflix—users and video content, excluding features like search and subscriptions.
• 📊 Andreas focuses on user activity data to inform Netflix's recommendation engine, specifically how to aggregate and process this data.
• 🌐 The design prioritizes low latency and global availability, meaning fast access to video content around the world.
• 💾 Video data storage is estimated using assumptions about video sizes, standard and high-definition formats, and average video length.
• 📁 Blob storage is suggested for storing large static video files, while relational databases (e.g., PostgreSQL) are proposed for static metadata.
• ⚡ Andreas recommends using caching techniques to speed up data retrieval and ensure a smooth user experience.
• 🗂 Sharding is proposed for handling user metadata efficiently, with user IDs determining the distribution of data across shards.
• 🌍 Andreas also introduces the use of a CDN (Content Delivery Network) to ensure fast content delivery to users based on geographic location.

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