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Storage Systems: Databases, Caches, and Data Structures
System & ML-System Design

Storage Layer: Caching Strategies, Bloom Filters, and Skip Lists

TechnicalMedium~30 minDesigned by experts

About this interview

A technical interview on Storage Systems: Databases, Caches, and Data Structures, pitched at the medium level. A voice AI interviewer leads the conversation, adapts its questions to your answers, keeps you on topic, and afterward gives you honest, specific feedback on where you were strong and where to improve. Expect roughly 30 minutes.

What you'll be assessed on

Design a caching layer covering cache-aside vs. write-through vs. write-behind strategies and eviction policies
Explain thundering herd, cache stampede, and hotspot problems and their mitigations
Describe Bloom filters as probabilistic data structures and their use in storage engines and CDNs
Explain skip lists and their role as an alternative to balanced trees in concurrent data structures

Topics covered

Caching fundamentalsCache read patternsCache-aside vs read-throughCache write patternsEviction policiesCache consistencyThundering herdThundering herd mitigationsCache stampedeCache hotspotsCache operationsCache design decisionsCache placementBloom filter fundamentals

A few sample questions

Just examples to set expectations - the real interview has many more and adapts to your responses.

In plain terms, why do we add a cache in front of a database at all? What fundamental tradeoff does it exploit?
What are three practical techniques to prevent or reduce the thundering herd problem? Explain how each one works.
Describe a scenario in a content delivery network where a Bloom filter would be valuable. What query is being answered and what is the benefit over a full index lookup?

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