Caching and Performance Optimization Questions

Covers design and implementation of multi layer caching and end to end performance strategies for web and backend systems. Topics include client side techniques such as browser caching, service worker strategies, code splitting, and lazy loading for components images and data; edge and distribution techniques such as content delivery network design and caching of static assets; and server side and data layer caching using in memory stores such as Redis and Memcached, query result caching, and database caching patterns. Includes cache invalidation and coherence strategies such as time to live, least recently used eviction, cache aside, write through and write behind, and prevention of cache stampedes. Covers when to introduce caching and when not to, performance and consistency trade offs, connection pooling, monitoring and metrics, establishing performance budgets, and operational considerations such as cache warm up and invalidation during deploys. Also addresses higher level concerns including search engine optimization implications and server side rendering trade offs, and how performance decisions map to user experience and business metrics at senior levels.

MediumSystem Design

34 practiced

Design a practical CDN invalidation and deployment plan for frontend releases to avoid serving stale JS/CSS while minimizing costly full-cache purges. Explain how you would use versioned assets, surrogate keys, and a staged invalidation approach.

EasyTechnical

50 practiced

Describe lazy loading of images and components on the web. Explain how IntersectionObserver helps implement lazy loading and outline a simple fallback strategy for browsers that do not support that API.

HardTechnical

27 practiced

At scale, how would you prevent cache stampedes when many concurrent requests miss a hot cache key? Design and compare practical server-side mechanisms such as distributed locks using Redis SETNX, request coalescing, mutex with short TTL, and probabilistic early expiration. Discuss latency, availability, and correctness trade-offs.

MediumTechnical

33 practiced

Which frontend and backend metrics should you track to measure the effectiveness of caching changes and enforce performance budgets? Sketch a dashboard and list alerts that indicate regressions specific to caching problems.

HardTechnical

29 practiced

You want to A/B test a new caching strategy that changes TTLs and introduces edge stale-while-revalidate behavior. Design the experiment: what metrics to track (performance and business), how to split traffic safely, required sample size considerations for conversion metrics, and rollback criteria if customers are negatively impacted.

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