I started with the basic TTL-based eviction and a hash map structure, which felt right, but then they pushed on consistency across distributed nodes and I kind of fumbled.
Start by clarifying requirements and scale, then design a multi-tier cache (in-memory, local disk, distributed) with TTL-based expiration and eviction policies. Focus on trade-offs between consistency, latency, and hit rate, and discuss how to handle cache invalidation and negative caching.
Pro tip: Emphasize that DNS caching is not just about storing records but also about respecting TTLs and handling negative responses; mention that Meta's scale requires a distributed cache with consistent hashing and proactive refreshing to avoid thundering herds.
Ask about expected QPS, latency targets, cache size, consistency requirements, and whether it's for a recursive resolver or a client-side cache. This sets the stage for design decisions.
Propose a multi-level cache: in-memory (e.g., LRU) for hot records, local disk for larger capacity, and a distributed cache (e.g., Redis) for sharing across nodes. Discuss how queries flow through these layers.
Define TTL-based expiration, eviction policies (LRU, LFU), and how to handle negative caching (NXDOMAIN). Explain how to respect TTLs from authoritative servers and avoid stale data.
Discuss strategies for cache invalidation (e.g., TTL expiry, active purging) and trade-offs between consistency and availability. Mention how to handle updates when records change.
Address scaling via sharding/consistent hashing, replication for fault tolerance, and monitoring hit rates. Discuss how to prevent cache stampedes and handle failures gracefully.
AI-generated suggestions, not part of the candidate's original notes. May be inaccurate — verify before relying on them.