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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.

HardTechnical
0 practiced
Compare and analyze the trade-offs of performing personalization at the edge using edge functions (e.g., Cloudflare Workers, Lambda@Edge) vs performing personalization server-side and delivering fully personalized HTML. Consider latency, cacheability, operational complexity, and data privacy.
MediumTechnical
0 practiced
Explain the differences, pros, and cons between CDN caching of dynamic API responses at the edge and application-level caching (e.g., Redis) in the origin. For what kinds of content and use-cases would you use each, and when would you combine them?
MediumTechnical
0 practiced
Cold cache during deploys causes latency spikes. Design a blue/green deploy approach with cache warm-up and graceful traffic shifting. Include steps for warming caches, running background refreshers, and metrics to watch during cutover to detect cold-start problems.
HardTechnical
0 practiced
You need to convince a non-technical executive to fund a project to implement a multi-layer caching solution to reduce 99th percentile latency and improve conversions. Draft the outline of a pitch that includes the problem statement, measurable objectives, expected benefits, estimated costs, key risks, and a phased delivery plan with quick wins.
HardSystem Design
0 practiced
A user's shopping cart must remain consistent across devices and support offline edits. Architect a cache and persistence strategy to ensure correctness while keeping latency low. Discuss choice of data store, conflict resolution, sync mechanisms, and cache invalidation when a cart is modified on another device.

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