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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.

MediumTechnical
95 practiced
Design monitoring dashboards and an alerting strategy for a Redis cluster to detect deteriorating cache performance. Include the key metrics, derived ratios, alert thresholds, and example remediation steps that an on-call SRE should follow when alerts fire.
HardTechnical
80 practiced
Discuss cache security threats and mitigations in multi-tenant environments. Cover data leakage via shared memory, tenant isolation, ACLs, TLS in transit, authentication, encryption at rest, and operational controls to prevent eviction or poisoning attacks targeting the cache.
MediumSystem Design
120 practiced
Design a caching strategy for a read-heavy analytics endpoint that takes around 1 second of CPU per request. Clients tolerate 5% staleness up to 1 minute. Propose TTLs, background proactive refresh, cache-aside or read-through pattern, and how to handle cache misses and failures gracefully.
MediumTechnical
94 practiced
Describe a methodology for choosing TTLs across a caching hierarchy: browser, CDN, edge, and app-level cache. Given example content types user profile (strong consistency), feed items (eventual), and static assets, propose TTLs and invalidation techniques for each layer.
MediumTechnical
99 practiced
Design a cache key naming scheme that supports schema evolution, multi-tenancy, and versioned content. Explain how to include prefixes, version tokens, tenant identifiers and TTLs in keys and how to handle migrations when schema changes require key format updates.

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