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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.

EasyTechnical
0 practiced
What is cache poisoning in the context of CDN or HTTP caches? Describe ways an attacker or misbehaving client might poison caches and list mitigation strategies SREs should implement (validation, header restrictions, key normalization).
HardTechnical
0 practiced
Explain Redis eviction policies (volatile-lru, allkeys-lru, volatile-ttl, volatile-random, allkeys-random, volatile-lfu, allkeys-lfu). For each, describe how it works, memory and CPU tradeoffs, and which policy you'd choose for a large cache with many short-lived keys.
HardTechnical
0 practiced
You need to migrate a large production cache tier from Memcached to Redis with minimal downtime and consistent semantics for an existing application. Outline a migration plan addressing key compatibility, TTL preservation, atomicity during cutover, and how to validate correctness.
HardSystem Design
0 practiced
Design a sharding (partitioning) strategy for a large cache tier to distribute keys across many nodes. Explain hash-based sharding, consistent hashing, and how to handle rebalancing with minimal cache churn when nodes are added/removed.
HardTechnical
0 practiced
Discuss cache consistency models: strong consistency, eventual consistency, session consistency, and read-after-write guarantees. For each model explain how it maps to caching layers and what application-level constraints are implied.

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