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.
MediumTechnical
0 practiced
Describe reliable testing strategies for cache behavior: how to write unit tests, integration tests against a real Redis instance, deterministic TTL/time control in tests, mocking approaches, and how to avoid flakiness caused by eviction, background persistence, or network variability in CI pipelines.
HardSystem Design
0 practiced
You must migrate a single-node Redis cache to a Redis Cluster across 6 nodes with minimal downtime and consistent cache access. Sketch a migration plan covering client changes, key rehashing or proxying, data migration steps, how to warm caches, and strategies to avoid spikes or cache inconsistency during cutover.
MediumTechnical
0 practiced
Implement a thread-safe memoization decorator in Python that caches function results with a TTL per key. Explain how you handle race conditions when multiple callers compute the same expired value, and provide example usage demonstrating caching and expiry behavior.
EasyTechnical
0 practiced
Explain TTL (time-to-live) for cache entries: how TTL is applied in Redis and Memcached, how TTL interacts with eviction policies, guidelines for choosing TTL values across data types (sessions, product catalog, computed results), and common pitfalls such as cache avalanches and serving stale data when TTLs are too long or too short.
HardTechnical
0 practiced
JVM-based services using large in-process caches (like Caffeine) sometimes experience GC pauses affecting latency SLOs. Explain how cache size and object churn influence GC, what JVM and GC settings you would tune, and alternative strategies like off-heap caches or serialization to reduce GC pressure. Give concrete tuning suggestions.
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