InterviewStack.io LogoInterviewStack.io

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.

HardSystem Design
0 practiced
Design a write-behind caching layer that buffers writes to the database to improve throughput while aiming for at-most-once or exactly-once semantics. Explain buffering strategies, durability guarantees, ordering constraints, crash recovery, and how you would handle duplicate or lost writes.
MediumTechnical
0 practiced
You must choose between Redis and Memcached for a cache layer storing objects up to 1 MB, with a mix of string and small JSON blobs, high concurrency, occasional big batch evictions, and cost sensitivity. Compare both choices covering memory management, eviction behavior, persistence, operational overhead, and security considerations.
HardTechnical
0 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.
HardTechnical
0 practiced
You led an incident where stale feature flags in cache caused 20% of users to see an outdated UI for 45 minutes. Draft a high-level incident postmortem: timeline, root cause analysis, immediate remediation, permanent fixes, monitoring changes, and team-level learnings that prevent recurrence.
EasyTechnical
0 practiced
Explain LRU, LFU, and FIFO eviction policies and how they behave under different workloads. Discuss CPU and memory overhead of each policy and which is preferable for workloads with strong temporal locality versus long-tail popularity.

Unlock Full Question Bank

Get access to hundreds of Caching Strategies and Patterns interview questions and detailed answers.

Sign in to Continue

Join thousands of developers preparing for their dream job.