System Design Basics

Scalability

Vertical Scaling (Scaling Up)

Adding more power (CPU, RAM) to an existing machine.

• Pros: simple.
• Cons: limit to how much you can upgrade. Single point of failure.

Horizontal Scaling (Scaling Out)

Adding more machines to the pool of resources.

• Pros: unlimited scaling.
• Cons: complex complexity, needs Load Balancer.

Load Balancing

Distributes network traffic across multiple servers.

• Algorithms: Round Robin, Least Connections, IP Hash.
• Tools: Nginx, HAProxy, AWS ELB.

Caching

Temporary storage for frequently accessed data.

• Application Cache: In-memory (e.g., Caffeine).
• Distributed Cache: Redis/Memcached.
• Cache Strategies:
  • Write-through: Write to cache and DB same time.
  • Write-back: Write to cache, update DB later.
  • Cache-aside: App checks cache first, then DB.

Database Scaling

Sharding

Splitting a large database into smaller, faster, more easily managed parts called shards.

• Horizontal Partitioning: Splitting rows based on key (e.g., UserID).

Replication

Copying data from one server to another.

• Master-Slave: Master handles writes, slaves handle reads.

Microservices

Architectural style where an app is a collection of small services.

• Communication: REST (JSON) or gRPC (Protobuf).
• Service Discovery: Eureka / Consul.
• Fault Tolerance: Circuit Breaker (Resilience4j).

Quiz