Today was all about understanding how real-world systems are designed for scalability, speed, and reliability.
🔹 Username Availability Check (Backend Logic)
Ever wondered how apps instantly tell you “username already taken”?
I explored:
Using Redis HashMap for fast lookup (cache hit ⚡)
Storing key-value pairs like username → userId
Result: Super fast checks without hitting the database every time
Also learned about:
Tries (Prefix Trees) → Efficient string search
Time Complexity: O(m), where m = length of string
🔹 Data Structures for Scale
B+ Trees → Used in databases (O(log N))
Bloom Filters → Memory-efficient, fast checks (with small error probability)
🔹 System Design Components
💡 API Gateway
Handles requests
Authentication & Authorization
Rate limiting
Request/Response transformation
Monitoring & analytics
💡 Load Balancer
Distributes traffic across servers
Improves scalability & availability
Algorithms:
Round Robin
Least Connections
IP Hash
Weighted
💡 Reverse Proxy (like Nginx)
Sits in front of servers
Adds caching, security, compression
Flow: Client → Proxy → Backend → Proxy → Response
🔹 AWS Storage Deep Dive
📦 EBS (Elastic Block Storage)
Virtual hard disk for EC2
Persistent storage
Can detach & attach to other instances
Works within same Availability Zone
📦 S3 (Object Storage)
Stores files, backups
Access via API (HTTP)
Highly scalable
📦 Instance Storage
Temporary (ephemeral)
Very fast
Used for cache/temp data
🔥 Key Takeaway
Speed = Cache (Redis)
Scalability = Load Balancer + API Gateway
Efficiency = Right Data Structure (Trie, Bloom Filter)
Storage = Use the right AWS service
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