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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
81 practiced
As a backend engineer you must configure HTTP caching for different asset types. Provide practical Cache-Control and header recommendations for three classes: (1) static assets that rarely change (images, JS/CSS), (2) semi-dynamic product pages that can tolerate short staleness, and (3) personalized pages that must not be cached publicly. Show header examples (Cache-Control, ETag, Vary) and explain the rationale for each.
HardTechnical
71 practiced
You rolled out a caching change to production. Describe a comprehensive instrumentation and analysis plan to prove its end-to-end impact on user latency, backend load, error rates, and cost. Include how you'd use distributed tracing spans, enriched logs, before/after baselines, sampling strategies, statistical tests, dashboards, and how to present results to product and SRE stakeholders.
MediumSystem Design
85 practiced
Design a multi-level caching strategy for an e-commerce product detail page serving 50k RPS globally, with 1M SKUs. Specify what to cache at each layer (browser, CDN, edge, app memory, distributed Redis), cache key design, invalidation approach for price and inventory changes, and how to maximize hit rate while meeting freshness requirements for price/availability.
HardSystem Design
74 practiced
Design a migration plan to move a single-node Redis cache to a Redis Cluster (multi-node with slots and replication) with minimal downtime. Include steps for data synchronization, client routing changes, resharding keys, fallback/rollback approaches, and verification that no keys were lost and client traffic is routed correctly.
HardTechnical
85 practiced
You are building an online ticketing reservation system where seat reservations must be strongly consistent. Discuss why naive caching is dangerous here and propose a caching-safe architecture (for example: cache-aside with immediate invalidation, authoritative origin locking, conditional updates, or combining cache reads with origin verification). Analyze performance vs correctness trade-offs and mitigation strategies.

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