A complex system that works is invariably found to have evolved from a simple system that worked. A complex system designed from scratch never works and cannot be patched to make it work. You have to start over with a simple working system.

Use autoscaling for traffic spikes design for scalability from the start plan for and implement fault tolerance prioritize horizontal scaling for scalability implement data partitioning and sharding use data lakes for analytics and reporting employ CDNs for global latency reduction make operations idempotent for simplicity use event-driven architecture for flexibility employ blob/object storage for media files embrace tradeoffs; perfection is unattainable implement Data Replication and Redundancy Implement rate Limiting for system protection use a read-through cache for read-heavy apps utilize write-through cache for write-heavy apps opt for NoSQL Databases for unstructured data use Heartbeat Mechanisms for failure detection adopt WebSockets for real-time communication employ Database Sharding for horizontal scaling clearly define system use cases and constraints consider microservices for flexibility and scalability design for flexibility; expect requirements to evolve utilize Database Indexing for efficient data retrieval understand requirements thoroughly before designing Utilize asynchronous processing for background tasks consider denormalizing databases for read-heavy tasks avoid over-engineering; add functionality only as needed prefer SQL Databases for structured data and transactions use Load Balancers for high availability and traffic distribution consider message queues for asynchronous communication