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.
HardTechnical
0 practiced
Your service is write-heavy (10k writes/sec). Explain why naive caching might not help, and design a hybrid approach that supports write throughput while still benefiting reads: include a design using write-through or event-driven invalidation with queues (e.g., Kafka), idempotent consumers, and a pattern for ensuring eventual consistency without overwhelming the cache or origin.
MediumTechnical
0 practiced
Compare in-process caches (like Caffeine/Guava) vs remote/shared caches (Redis) for microservices. Discuss latency, consistency, memory duplication across instances, eviction complexity, failure modes, and operational trade-offs. Provide guidance for when to use local caches, remote caches, or a two-level strategy.
EasyTechnical
0 practiced
Explain common cache eviction policies (LRU, LFU, FIFO) with algorithmic intuition, typical implementations in caches, the memory/time trade-offs, and provide a short example workload where LFU outperforms LRU. Mention how approximations are used in systems like Redis.
HardTechnical
0 practiced
Design a robust system to prevent cache stampedes at scale combining methods like probabilistic early expiration, request coalescing (singleflight), distributed mutexes with timeouts, and proactive warming. Describe how the components interact, data structures needed, and performance implications under heavy traffic.
HardSystem Design
0 practiced
Design a globally distributed caching solution for a multi-region service requiring sub-5ms reads for local traffic and aims for eventual consistency on writes. Describe placement of caches (edge, region-local caches), replication strategies, write propagation, conflict handling, failover, and cost vs latency trade-offs.
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