Distributed Cache Design Interview
Ace your principal software engineer distributed cache design interview with our AI-powered real-time coach. Get instant guidance on cache coherence, eviction policies, distributed systems architecture, and high-performance caching strategies.
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Interviewer [00:00:05]: Design a distributed cache system that can handle 100,000 requests per second with sub-10ms latency and 99.99% availability.
You [00:00:15]: I'd like to start by clarifying the requirements and constraints. What's the expected data size per cache entry? What's the total data volume we need to cache? And what consistency model is required?
Interviewer [00:00:28]: Good questions. Let's say the average cache entry is 10KB, with a total cache size of 1TB. We need strong consistency within regions but can accept eventual consistency across regions. The cache should also handle node failures gracefully.
AI Suggestion:
- Architecture Components:
- Propose a distributed hash table with consistent hashing for node management
- Suggest a multi-tier architecture: in-memory layer (Redis/Memcached) with SSD backup
- Recommend regional clusters with cross-region replication
- Consistency & Replication:
- Explain quorum-based writes (W + R > N) for regional strong consistency
- Discuss vector clocks or logical timestamps for conflict resolution
- Suggest asynchronous replication across regions with conflict detection
- Performance Optimization:
- Mention partitioning strategy with virtual nodes to distribute load
- Discuss read-through/write-through vs. read-aside/write-aside patterns
- Suggest bloom filters to reduce cache misses
- Failure Handling:
- Explain gossip protocol for failure detection
- Discuss anti-entropy mechanisms for replica synchronization
- Mention sloppy quorum and hinted handoff for availability during partitions
- Eviction Policies:
- Suggest segmented LRU with frequency/recency balance
- Discuss TTL implementation with background expiration
🏗️ Distributed Cache Architecture
Get expert guidance on designing scalable distributed cache architectures, including sharding strategies, replication models, and consistency mechanisms tailored to your specific interview scenario.
⚡ Cache Coherence Strategies
Receive instant recommendations on cache coherence protocols, invalidation strategies, and consistency models with detailed explanations of trade-offs between performance and consistency.
🔄 Eviction Policy Design
Access real-time guidance on designing optimal cache eviction policies, including LRU, LFU, FIFO, and advanced algorithms like W-TinyLFU, with implementation considerations for distributed environments.
🔍 Failure Handling & Resilience
Get instant suggestions for handling node failures, network partitions, and split-brain scenarios in distributed cache systems, including sloppy quorums, hinted handoff, and anti-entropy mechanisms.
🔒 Consistency & Replication Models
Receive guidance on implementing various consistency models (strong, eventual, causal) and replication strategies (synchronous, asynchronous) with practical examples and trade-off analysis.
📈 Performance Optimization Techniques
Access expert advice on optimizing distributed cache performance, including read/write patterns, bloom filters, cache warming strategies, and techniques to minimize cache misses and latency.
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