--- title: "System Design Interview Questions (2026): By Level, With Model Answers" url: https://weworkworldwide.com/system-design-interview-questions/ description: "System design interview questions for mid and senior engineers — scaling, caching, databases, consistency and reliability — with model answers and red flags." date: 2026-07-04T15:29:04+00:00 source: https://weworkworldwide.com/llms.txt --- # System Design Interview Questions (2026): By Level, With Model Answers How to use this System design separates engineers who can build a feature from those who can build a system. These questions probe how someone reasons about scale, tradeoffs and failure. Hiring a System Design developer is easy. Telling a real one from a convincing résumé is the hard part — and it’s most of what we do. These are grouped by level, because the same question that stretches a junior is a warm-up for a senior. ## Junior System Design interview questions 0–2 years Foundational building blocks. ### What is the difference between horizontal and vertical scaling? What a strong answer covers Vertical scaling adds power to one machine; horizontal scaling adds more machines behind a load balancer, which scales further but needs statelessness. Red flag Only knows “buy a bigger server.” ### What does a load balancer do? What a strong answer covers Distributes traffic across servers, enabling scale and redundancy, with health checks routing away from unhealthy instances. Red flag Thinks a load balancer stores state. ### What is caching and where do you apply it? What a strong answer covers Storing frequently-read data closer to the consumer (browser, CDN, app, database) to cut latency and load; the hard part is invalidation. Red flag Caches everything with no expiry strategy. ### What is a database index, at a systems level? What a strong answer covers A structure that trades write cost and storage for faster reads, essential once tables grow. Red flag Thinks scaling reads is only about bigger hardware. ### What is the difference between SQL and NoSQL? What a strong answer covers Relational databases give structure, joins and transactions; NoSQL trades some of those for flexible schemas and horizontal scale. Choose by access pattern. Red flag Believes one is universally better. ### What is an API and how do services talk? What a strong answer covers A contract for requests/responses, commonly over HTTP/REST or gRPC, decoupling producers and consumers. Red flag No notion of contracts or versioning. ### What is latency vs throughput? What a strong answer covers Latency is the time for one request; throughput is requests handled per unit time. They can be optimised independently and sometimes traded off. Red flag Uses the terms interchangeably. ### What is a stateless service and why does it matter? What a strong answer covers One that keeps no client state between requests, so any instance can serve any request — the basis for horizontal scaling. Red flag Stores session state in process memory. ## Mid-level System Design interview questions 2–5 years Data, queues and consistency. ### How would you design a URL shortener? What a strong answer covers Generate a short unique key, store the mapping, redirect on lookup; discuss key generation, storage choice, caching hot links and read/write ratios. Red flag Jumps to code without discussing scale or key collisions. ### When do you introduce a message queue? What a strong answer covers To decouple producers from consumers, smooth spikes, and process work asynchronously and reliably with retries. Red flag Does slow work synchronously in the request path. ### What is the difference between strong and eventual consistency? What a strong answer covers Strong consistency guarantees every read sees the latest write; eventual consistency allows temporary divergence for availability and scale. Red flag Assumes every system must be strongly consistent. ### How do you scale reads on a database? What a strong answer covers Read replicas, caching, and denormalised read models, accepting replication lag and its consistency implications. Red flag Points all reads at the primary and wonders why it’s slow. ### What is idempotency and why does it matter? What a strong answer covers An operation that has the same effect if applied multiple times, essential for safe retries in distributed systems (e.g. payment requests). Red flag Retries non-idempotent operations and double-charges. ### How do you handle a service that depends on a slow downstream? What a strong answer covers Timeouts, retries with backoff, circuit breakers, caching and graceful degradation so one slow dependency doesn’t cascade. Red flag Lets a slow dependency block threads until everything falls over. ### What is sharding and what does it cost? What a strong answer covers Splitting data across nodes by a key to scale writes and storage; the cost is cross-shard queries, rebalancing and hotspots. Red flag Shards on a key that creates hotspots. ### How do you design an API for pagination of large results? What a strong answer covers Cursor/keyset pagination for stability and performance over large offsets, rather than `OFFSET` deep into a dataset. Red flag Uses large `OFFSET` values that scan and skip millions of rows. ## Senior System Design interview questions 5+ years Tradeoffs, reliability and scale. ### Walk me through designing a news feed / timeline. What a strong answer covers Discuss fan-out on write vs read, caching, ranking, storage, and the tradeoffs for celebrity accounts and hot partitions. Red flag Gives one design with no tradeoff discussion. ### How do you explain the CAP theorem in practice? What a strong answer covers Under a network partition you must choose availability or consistency; in normal operation you tune latency vs consistency. They apply it to real choices. Red flag Recites CAP but can’t apply it to a decision. ### How do you design for high availability? What a strong answer covers Redundancy across zones, no single points of failure, health checks and failover, graceful degradation, and tested recovery. Red flag Assumes a single region and instance is fine. ### How do you approach observability? What a strong answer covers Metrics, structured logs and distributed tracing tied to SLOs, so you can detect, locate and diagnose problems quickly. Red flag Relies on users to report outages. ### How do you handle a hot partition or celebrity problem? What a strong answer covers Special-case heavy keys, add caching, split or replicate the hotspot, and consider a different fan-out strategy for them. Red flag Ignores skew and lets one key overwhelm a shard. ### How do you make a distributed operation reliable? What a strong answer covers Idempotency keys, retries with backoff, outbox/saga patterns for consistency across services, and dead-letter queues. Red flag Assumes network calls always succeed. ### How do you decide between monolith and microservices? What a strong answer covers By team size, deployment needs and domain boundaries; microservices add operational complexity that only pays off at scale and organisational need. Red flag Reaches for microservices reflexively on day one. ### How do you estimate capacity for a new system? What a strong answer covers Back-of-the-envelope from expected QPS, data size, read/write ratio and growth, then validate with load testing. Red flag Provisions by guesswork with no numbers. **Skip the screening entirely.**We vet System Design engineers so you don’t have to — embed one in your team, or have us build it. 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