LinkedIn Infrastructure Interview: Caching Strategies

Overview

This question asks you to compare and justify caching strategies — specifically write-through vs write-back — in the context of infrastructure and backend systems. You'll be expected to explain how each strategy handles writes, how they affect consistency, durability, latency, and throughput, and when one is preferable to the other in real-world services.

What you'll be asked (flow)

You will typically start by describing the write paths for write-through and write-back caches. Next, you’ll discuss trade-offs (latency vs durability vs complexity). Interviewers often follow with concurrency and coherence scenarios: multi-threaded access, distributed caches, replication, and failure recovery. Finally, you may be asked to pick a strategy for a given workload and justify it with metrics or failure modes.

Skills and signals you should demonstrate

You should show clear knowledge of cache write policies (write-through, write-back, write-allocate/no-write-allocate), cache coherence basics (e.g., invalidation, update propagation), and how these interact with durability and fault tolerance. Quantify trade-offs with latency/throughput estimates, mention recovery mechanisms (e.g., write logs, checkpoints), and discuss testing approaches (consistency tests, crash/recovery scenarios). Use concrete examples (read-heavy vs write-heavy, critical user data vs transient data) to justify decisions.

Prepare by sketching write paths, enumerating failure cases, and practicing concise trade-off-driven recommendations. Include follow-ups like distributed coherence, crash recovery for write-back, and eviction/flush strategies in your prep.