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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.

HardSystem Design
0 practiced
Design a multi-tenant caching strategy to prevent a noisy tenant from evicting others in a shared Redis cluster. Discuss approaches: key namespacing, per-tenant quotas, client-side caches, separate DB IDs, and eviction isolation. Outline how you'd enforce quotas and monitor for cross-tenant interference.
MediumTechnical
0 practiced
You cache per-region copies of some data in regional Redis clusters. When a write occurs in region A, describe strategies to ensure other regions see the update quickly: remote invalidation, background replication, versioned keys, or TTLs. Discuss trade-offs between staleness, write amplification, and cross-region latency.
EasyTechnical
0 practiced
You're implementing caching for static website assets (JS/CSS/images) served to browsers. Explain how you would use HTTP headers (Cache-Control, ETag, Last-Modified) and when to choose aggressive caching vs revalidation. Include examples of header values for assets that are content-addressed (fingerprinted) and for frequently-changing assets.
MediumTechnical
0 practiced
How would you implement a thread-safe LRU cache for a multi-core Java service that needs O(1) operations and high concurrency? Describe data structures, locking strategy (coarse vs segmented), and how you'd minimize contention under heavy read load.
EasyTechnical
0 practiced
Describe scenarios where introducing caching is detrimental or unnecessary. Give concrete examples (e.g., low read volume, strict strong consistency, small dataset that fits in a fast DB cache) and explain the risks and added operational costs of caching in those cases.

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