Caching Strategies and In Memory Storage Questions
Understanding caching mechanisms (HTTP caching, application-level caching with Redis/Memcached). Cache invalidation strategies, TTL, and when to cache. Performance implications.
EasyTechnical
81 practiced
When should you NOT cache data in a backend system? Provide concrete scenarios such as highly dynamic authorization checks, real-time financial ticks, small-cardinality datasets that would consume more memory than they save, or sensitive personal data that cannot be stored in ephemeral caches. For each scenario suggest safer alternatives.
HardSystem Design
83 practiced
Design a global distributed caching architecture for a personalized social feed service handling millions of QPS. Address cache placement choices (edge/CDN, regional caches, per-user caches), personalization approaches (precompute fan-out-on-write vs fan-out-on-read), invalidation when new posts or interactions arrive, cache warming, partitioning of user shards, and cost versus latency trade-offs for different regions.
HardSystem Design
89 practiced
Design cross-region caching with Redis to provide low-latency reads worldwide while respecting data sovereignty constraints and acceptable consistency. Compare active-active and active-passive approaches, replication lag consequences, conflict resolution strategies (CRDTs vs LWW), and operational cost and complexity considerations. Recommend a solution for read-mostly user profile data.
MediumTechnical
44 practiced
You need to choose a session store for a globally distributed web app: local in-memory per-process cache, Memcached, or Redis. Compare them across latency, shared access across instances, failover and replication, secure handling of session data, and operational complexity. Recommend the best approach for scalable sessions and justify your choice.
MediumSystem Design
50 practiced
Design a caching layer for product detail pages in an e-commerce application serving 10,000 requests per second. Describe cache placement across CDN, edge, application cache, and DB; cache key design including variants (currency, locale, logged-in state); invalidation strategy when product details or inventory change; choosing TTLs; and fallback behavior for cache misses.
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