system-design

Vertical scaling increases the resources of a single server, while horizontal scaling adds more server instances to distribute load. Horizontal scaling requires stateless service design to achieve higher availability and scalability.

Choosing a caching strategy involves evaluating cache-aside, write-through, and write-behind patterns against your data consistency needs. You must implement proper cache invalidation strategies to ensure system availability and data accuracy.

Database scaling for high availability relies on read replicas to distribute query load and sharding to partition data across multiple nodes. These techniques ensure continuous uptime and performance during traffic spikes.

The CAP theorem dictates that distributed systems can only guarantee two out of three properties: Consistency, Availability, and Partition Tolerance. Designing distributed systems requires comprehending these trade-offs to handle network partitions effectively.

Implement the circuit breaker pattern to prevent cascading failures and ensure high availability when a downstream service becomes unresponsive. It provides redundancy by stopping traffic to failing components until they recover.

Scalable systems utilize Point-to-Point and Pub/Sub message queue patterns to decouple services. Understanding delivery guarantees for these patterns ensures reliable asynchronous communication and load balancing across components.