System Design Interview Prep

System design interview questions are the differentiator for senior and staff Java backend roles — capacity estimation, the building blocks (load balancers, caches, queues, databases, CDNs), data partitioning, replication and consistency, rate limiting, idempotency at scale, designing for high availability, and the trade-offs that show up in every system-design round (latency vs throughput, consistency vs availability). This page covers the fundamentals; for full case studies (URL shortener, Twitter feed, distributed cache) see the System Design Problems page.

Always answer in 5 steps — never skip a step.

1. 1
   Requirements (functional + non-functional + scale).
2. 2
   Capacity (QPS, storage, bandwidth).
3. 3
   API + data model.
4. 4
   High-level design (boxes + arrows).
5. 5
   Deep dive on the bottleneck the interviewer cares about.

Cite CAP + PACELC when consistency is on the line.

The interview surface for this module breaks into these focus areas:

• Caching at scale — drill the named patterns, the failure modes, and the recommended Java / framework idiom.
• Cap theorem — drill the named patterns, the failure modes, and the recommended Java / framework idiom.
• Capacity planning — drill the named patterns, the failure modes, and the recommended Java / framework idiom.
• Comparisons — drill the named patterns, the failure modes, and the recommended Java / framework idiom.
• Database design at scale — drill the named patterns, the failure modes, and the recommended Java / framework idiom.
• Design fundamentals — drill the named patterns, the failure modes, and the recommended Java / framework idiom.
• Event driven design — drill the named patterns, the failure modes, and the recommended Java / framework idiom.
• High availability — drill the named patterns, the failure modes, and the recommended Java / framework idiom.
• Load balancing — drill the named patterns, the failure modes, and the recommended Java / framework idiom.
• Microservices design — drill the named patterns, the failure modes, and the recommended Java / framework idiom.
• Scalability — drill the named patterns, the failure modes, and the recommended Java / framework idiom.
• Scenario-based — applied questions tying multiple topics together. Drill these last, after the fundamentals are sharp.

• Latency vs throughput — they trade against each other; cite p99 not avg.
• Sharding is a reorg, not an optimisation — earn it.
• Cache before sharding; read replicas before sharding.
• Idempotency at scale — keys + TTL + DB unique constraint.
• Back-of-envelope numbers — 1 GB/s ≈ 8 Gbps; 1 ms = 1 disk seek; 100 µs = 1 SSD read.

"At I'd start with a load balancer in front of stateless app servers, a primary DB with read replicas, Redis for hot reads, Kafka for async work. The bottleneck will be — the deep dive lives there."

System design problem walkthroughs — full end-to-end designs for the cases interviewers actually ask: URL shortener, distributed cache, rate limiter, news feed, ride-sharing dispatch, payment system, notification service, real-time chat. Each case follows the same structure: requirements, capacity estimation, API design, data model, high-level architecture, deep dives into the bottleneck components, and the trade-offs you would articulate to the interviewer. Pair this with the System Design Fundamentals page.

Each case has a canonical bottleneck — find it fast, deep-dive there.

• URL shortener — write throughput + key-gen.
• News feed — fan-out-on-write vs fan-out-on-read.
• Rate limiter — token bucket vs leaky bucket.
• Chat — long-poll / WebSocket / push gateway.
• Payments — idempotency keys, double-entry ledgers, exactly-once.
• Notifications — fan-out + per-user prefs + delivery semantics.

The interview surface for this module breaks into these focus areas:

• Chat system — drill the named patterns, the failure modes, and the recommended Java / framework idiom.
• Notification service — drill the named patterns, the failure modes, and the recommended Java / framework idiom.
• Payment system — drill the named patterns, the failure modes, and the recommended Java / framework idiom.
• Rate limiter — drill the named patterns, the failure modes, and the recommended Java / framework idiom.
• Search autocomplete — drill the named patterns, the failure modes, and the recommended Java / framework idiom.
• Social media feed — drill the named patterns, the failure modes, and the recommended Java / framework idiom.
• Url shortener — drill the named patterns, the failure modes, and the recommended Java / framework idiom.
• Scenario-based — applied questions tying multiple topics together. Drill these last, after the fundamentals are sharp.

• Fan-out write = cheap reads, expensive writes; fan-out read = opposite. Pick by read:write ratio.
• Exactly-once payment = idempotency key + DB-unique constraint, never trust delivery alone.
• Geo-distributed designs need consistency story — quorum read/write or Raft.
• Hot keys in URL shorteners — use base62 + counter sharding.
• WebSocket scale — sticky LB or central message bus.

"For the key constraint is . I'd pick for that reason, partition by for horizontal scale, and the bottleneck I'd deep-dive on is ."