Seemed basic but I second-guessed myself halfway through.
Start with a clear definition of caching as a technique to store frequently accessed data in a faster storage layer to reduce latency and load on primary systems. Then explain why it's needed by discussing performance, scalability, and cost benefits, using concrete examples like database query caching or CDN. Finally, briefly mention trade-offs such as cache invalidation and consistency to show depth.
Pro tip: At Amazon, caching is critical for meeting low-latency SLAs at scale, so emphasize how caching directly impacts customer experience and operational efficiency. Also, mention that caching is not just about speed but also about reducing load on downstream services to prevent outages.
Explain that caching is the process of storing copies of data in a temporary, high-speed storage layer (e.g., memory) so future requests for that data can be served faster.
Discuss the primary reasons: reducing latency, decreasing load on databases or backend services, improving throughput, and saving cost by avoiding expensive computations or I/O.
Give concrete examples such as caching database query results, using a CDN for static assets, or in-memory caches like Redis/Memcached in a microservices architecture.
Acknowledge challenges like cache invalidation, stale data, consistency, and memory overhead, showing awareness of when caching might not be appropriate.
Tie it back to Amazon's scale and customer obsession: caching helps deliver low-latency experiences to millions of customers and reduces infrastructure costs.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.