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.

MediumTechnical

0 practiced

You operate a Redis cluster. Describe how you would size memory, tune maxmemory-policy, and manage memory fragmentation for a workload with lots of short-lived keys and some large value objects. Explain trade-offs between volatile-ttl, allkeys-lru, and noeviction policies and their impact on application behavior.

MediumTechnical

0 practiced

During a rolling deployment, caches become cold causing elevated origin traffic and higher latency for users. Describe a warm-up strategy to prevent this: options include pre-warming, progressive traffic shifting, prioritized key warm-up, and client-side fallbacks. Propose an operational runbook that minimizes user-visible impact during deployments.

HardTechnical

0 practiced

Your company wants to roll out caching across multiple backend services to reduce DB costs, but leaders worry about correctness risk. Prepare a short plan (technical + rollout) describing how you'd pilot caching, measure success, handle invalidation, implement circuit-breakers, and provide rollback. Include what success metrics you'd track and how to mitigate data-staleness issues.

MediumTechnical

0 practiced

You cache aggregate query results (e.g., daily sales totals) to speed dashboards. When underlying transaction tables are updated, how do you design invalidation or incremental cache updates to keep aggregates accurate while minimizing recomputation? Discuss materialized views, event-driven incremental updates, and cache-aside approaches.

HardTechnical

0 practiced

Design a session store backed by Redis with high availability. Discuss session key design, persistence (RDB/AOF), replication strategy (master-replica), failover, sticky session vs stateless JWT alternatives, and how to ensure sessions remain valid through Redis failovers without compromising security.

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