Rate limiting isn’t about rejection , it’s about survival. Used in: - APIs → fair usage - Auth → brute-force prevention - Queues → backpressure control It protects good systems from good users who go wild

How gRPC Works from Start to End

Kubernetes - All You Need to Know

CDN All You Need to Know

How to Handle 10,000 Concurrent Users

Linked Lists walk - arrays teleport One node knows only the next - nothing more. Used in: - LRU caches (LinkedHashMap) - Undo/Redo stacks - Memory allocators - TCP/IP packet buffers - Concurrent queues - Blockchain history Not fast, but flexible.

You have millions of cache entries (Redis) and want to reduce cache misses when keys are dynamically generated. How do you approach it?

SQL Complete Roadmap

Database Scaling Rules 1 table → fine 10 tables → add indexes 100 tables → need query optimization + caching 1000 tables → need sharding, read replicas, schema governance

Anyone can build an app now just like anyone can take a photo. But not everyone can capture light. Understanding data structures and architecture is how you learn where to point the camera

System Design: Build Your Own Caching System (Like Redis/Memcached)

Docker vs Kubernetes

Docker Components Explained

Load Balancing Algorithms – All You Need to Know

The clearer your mental model, the fewer tokens you’ll need

How to choose Relational Databases PostgreSQL – if your data is mostly structured, relational, and long-lived. MySQL – if your data is mostly simple web CRUD and you care more about uptime than fancy features. SQLite – if your data is mostly local or embedded and doesn’t need

One Liner Explanation to All Design Patterns