IntermediateSystem-Design
30 min
Design a Distributed Caching Layer
CachingConsistencyNetworkingReliability
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Interview Question
Design a distributed cache that supports eviction policies, consistency across nodes, replication, and client-side failover.
Key Points to Cover
- Eviction policies (LRU, LFU, TTL) and hot key protection
- Replication: async vs sync; consistency models
- Sharding strategies (consistent hashing, rendezvous)
- Client failover and discovery mechanisms
- Observability and cache hit/miss metrics
Evaluation Rubric
Clear eviction and hot key plan25% weight
Replication & consistency trade-offs25% weight
Scalable sharding strategy25% weight
Operational visibility & failover25% weight
Hints
- 💡Think about cache stampede protection strategies.
Common Pitfalls to Avoid
- ⚠️**Over-reliance on Synchronous Replication:** This can cripple performance and availability in large distributed systems by making writes a bottleneck.
- ⚠️**Underestimating Replication Lag and Conflict Resolution:** Assuming async replication always works without sophisticated conflict resolution can lead to data inconsistency.
- ⚠️**Inefficient Eviction Policies:** Poorly chosen or implemented eviction policies (e.g., LFU without proper tuning) can lead to frequent evictions of valuable data.
- ⚠️**Static Sharding or Complex Rebalancing:** Not using consistent hashing or similar dynamic sharding methods can lead to massive data migrations and downtime when the cluster scales.
- ⚠️**Client-Side Complexity:** Making client logic too complex for failover and topology management can lead to unreliability and difficulty in debugging.
Potential Follow-up Questions
- ❓How would you implement read-through vs write-through?
- ❓How to handle cold start issues?
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