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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.

HardSystem Design
0 practiced
Design an architecture that maintains strong consistency between a database and cache for operations spanning multiple services where staleness is unacceptable. Discuss two-phase commit, distributed transactions, synchronous invalidation, change-data-capture with synchronous purge, and trade-offs in availability and latency.
MediumTechnical
0 practiced
Design sharding and partitioning strategy for a cache cluster that must store 10 TB of keys across 50 nodes. Explain consistent hashing, virtual nodes, rebalancing impact, and techniques to minimize cache churn when nodes are added or removed.
HardSystem Design
0 practiced
Design a caching strategy for a multi-tenant SaaS platform where tenants vary widely in traffic. Explain how to provide tenant isolation, enforce per-tenant quotas, implement fair eviction policies, and minimize noisy neighbor impact while keeping infrastructure cost efficient.
HardSystem Design
0 practiced
Design a write-behind (asynchronous flush) cache that guarantees no data loss and preserves ordering in the face of crashes. Discuss persistent write queues, at-least-once delivery, idempotency of writes, throttling/backpressure to the origin, and how to resume after a failure.
EasyTechnical
0 practiced
Define cache stampede and list common causes. Describe basic mitigation techniques such as request coalescing (singleflight), locking, early recompute, and probabilistic TTLs. Give a short example of how a singleflight pattern reduces DB overload.

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