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
46 practiced
What is cache warming (preloading) and why would a backend service use it? Describe practical strategies to warm caches during deployment or scale-up events: background prefetch workers, replaying recent traffic, precomputing popular keys, and selectively priming edges. Discuss trade-offs including additional load and potential stale priming.
HardTechnical
51 practiced
Your backend spends 40% of CPU time serializing and deserializing JSON objects stored in Redis. Propose and justify a set of optimizations such as switching to a binary encoding (protobuf/msgpack), compressing payloads, storing frequently accessed fields separately, lazy deserialization, or leveraging field-level access patterns. Include migration and compatibility concerns.
HardTechnical
44 practiced
Your Redis nodes are showing high memory fragmentation and periodic latency spikes under heavy write load. Outline a detailed diagnostic and remediation plan: which Redis INFO and system metrics to check, how allocator settings like jemalloc affect fragmentation, strategies such as reworking key/value sizes, enabling lazyfree or defrag, tuning AOF/RDB settings, and application-level batching to reduce churn.
MediumTechnical
43 practiced
You're observing high tail latency for a read-heavy microservice. Outline a step-by-step plan to introduce application-level caching (for example Redis) to reduce latency: include diagnosis steps, where to place the cache (co-located vs remote), cache key formation, partitioning/sharding strategy, cache warming approach, monitoring to add, and rollback criteria.
MediumTechnical
52 practiced
How would you cache database query results that depend on multiple tables and user-specified filters (for example search with facets)? Discuss key generation strategies, cache fragmentation problems, invalidation approaches when underlying rows change (versioned keys, tags, or change-data-capture), and alternatives such as materialized views or a search index.
Unlock Full Question Bank
Get access to hundreds of Caching Strategies and In Memory Storage interview questions and detailed answers.
Sign in to ContinueJoin thousands of developers preparing for their dream job.