Theoretical knowledge of databases and load balancers is a start but seeing how they are applied under extreme pressure is where the real learning happens. These case studies teach you about:
Scalability: How to grow from 1,000 to 1 billion users.
Availability: Ensuring services never go down, even during updates.
Latency: Reducing the milliseconds between a user's click and the system's response.
1. YouTube & MySQL (The Power of Sharding)
Most people assume a giant like YouTube would abandon traditional relational databases for something "fancier." However, YouTube famously scaled MySQL by using Vitess, a database clustering system.
The Lesson: You don't always need a NoSQL database to scale; horizontal sharding can allow traditional SQL databases to handle massive throughput.
2. Uber’s Geospatial Indexing
Uber processes over 1 million requests per second to match riders with drivers. This isn't just a simple query; it requires calculating distances in real-time.
The Lesson: Uber uses hexagonal hierarchical spatial indexing (H3). By dividing the world into hexagons, they can quickly calculate "proximity" without taxing the CPU with complex geometry.
3. Meta’s Serverless Scale
Handling 11.5 million serverless function calls per second is an exercise in extreme orchestration. Meta (Facebook) has to manage resource allocation and "cold starts" at a scale most companies will never see.
The Lesson: Serverless isn't just for small hobby projects; with the right infrastructure, it can power the world's largest social network.
System design is less about finding the "perfect" tool and more about understanding trade-offs. Whether it's choosing between the consistency of Google Docs or the massive throughput of Kafka, these 12 examples provide the blueprint for modern engineering.
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