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Caching Strategies and Patterns Questions

Comprehensive knowledge of caching principles, architectures, patterns, and operational practices used to improve latency, throughput, and scalability. Covers multi level caching across browser or client, edge content delivery networks, application in memory caches, dedicated distributed caches such as Redis and Memcached, and database or query caches. Includes cache design and selection of technologies, defining cache boundaries to match access patterns, and deciding when caching is appropriate such as read heavy workloads or expensive computations versus when it is harmful such as highly write heavy or rapidly changing data. Candidates should understand and compare cache patterns including cache aside, read through, write through, write behind, lazy loading, proactive refresh, and prepopulation. Invalidation and freshness strategies include time to live based expiration, explicit eviction and purge, versioned keys, event driven or messaging based invalidation, background refresh, and cache warming. Discuss consistency and correctness trade offs such as stale reads, race conditions, eventual consistency versus strong consistency, and tactics to maintain correctness including invalidate on write, versioning, conditional updates, and careful ordering of writes. Operational concerns include eviction policies such as least recently used and least frequently used, hot key mitigation, partitioning and sharding of cache data, replication, cache stampede prevention techniques such as request coalescing and locking, fallback to origin and graceful degradation, monitoring and metrics such as hit ratio, eviction rates, and tail latency, alerting and instrumentation, and failure and recovery strategies. At senior levels interviewers may probe distributed cache design, cross layer consistency trade offs, global versus regional content delivery choices, measuring end to end impact on user facing latency and backend load, incident handling, rollbacks and migrations, and operational runbooks.

EasyTechnical
95 practiced
Compare TTL (time-to-live) based expiration with explicit eviction/purge. Provide examples of use-cases where TTL is sufficient and where explicit invalidation is necessary. Also list drawbacks of using long TTL values.
MediumTechnical
102 practiced
You're designing an in-memory distributed cache for user sessions (session tokens plus small profile state). Sessions are frequently accessed soon after login then rarely. Explain your choice of eviction policy and TTL strategy, how to handle sticky versus distributed session approaches, and how to ensure session invalidation on logout across the system.
HardSystem Design
97 practiced
Multiple microservices need overlapping data (for example user profile and preferences). Evaluate trade-offs between a centralized shared cache (one Redis cluster) versus service-local caches with asynchronous synchronization. Propose an architecture that minimizes latency and coupling while keeping consistency predictable. Include data ownership, invalidation patterns, and operational considerations.
MediumTechnical
129 practiced
You observe occasional spikes of origin DB load because many clients simultaneously miss the cache for the same key (cache stampede). Describe at least four practical mitigation techniques (application and cache features) and explain the trade-offs of each technique.
MediumTechnical
69 practiced
Compare Redis, Memcached, and in-process application caches (e.g., Guava Cache or LRU maps) across these criteria: persistence, replication, data structures, scalability, operational complexity, and common use-cases. For a small startup building social feeds, which would you choose and why?

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