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System Design interview questions

1311 System Design questions from 230 companies, with hints, runnable code and solution walkthroughs.

Questions1311

60 easy819 medium432 hard

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System Design interview questions by the numbers

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Katkat has 1,311 System Design interview questions from 230 companies; the most come from OpenAI (8%), Meta (5%) and Amazon (4%). By difficulty: 5% easy, 62% medium and 33% hard. The most common round is Onsite (55%). Frequent concepts include System Design, Distributed Systems, Scalability and Caching.

Companies (230)

Difficulty

  • Easy5% · 60
  • Medium62% · 819
  • Hard33% · 432

Interview rounds

  • Onsite55% · 721
  • Technical Screen39% · 517
  • Online Assessment3% · 38
  • Other2% · 21
  • HR Screen1% · 13

Roles

  • Software Engineer91% · 1189
  • Machine Learning Engineer2% · 31
  • Data Engineer2% · 26
  • Backend Engineer2% · 25
  • Frontend Engineer1% · 19

Frequent concepts

  • System Design31% · 400
  • Distributed Systems24% · 316
  • Scalability15% · 196
  • Caching7% · 95
  • Concurrency7% · 91
  • system-design6% · 83

Showing 661–690 of 1311 results

  • This question evaluates system-design and transactional engineering skills for financial services, including API design, data modeling, correctness under holds and transfer expirations, idempotency, merge semantics, and complexity reasoning.

    MetaSoftware EngineerSystem DesignHR Screen
  • This question evaluates a candidate's ability to design and implement an in-memory banking API, focusing on data modeling, API semantics, invariants (such as monotonic timestamps and non-negative balances), idempotency, and basic concurrency control.

    MetaSoftware EngineerSystem DesignOnline Assessment
  • This question evaluates understanding of designing scalable, reliable content-processing systems that handle high-throughput ingestion, ML-based classification and rule evaluation, priority/backpressure mechanisms, storage and API design, experimentation hooks, and operational concerns like observability and cost.

    MetaSoftware EngineerSystem DesignOnsite
  • This problem tests your ability to design a scalable backend for a fitness tracking application, focusing on high-frequency sensor data ingestion, geospatial route storage, and efficient retrieval of historical user activities.

    MetaSoftware EngineerSystem DesignOnline Assessment
  • This question tests the ability to design a high-scale search platform that aggregates volatile data from heterogeneous third-party providers while maintaining low latency and high availability.

    MetaSoftware EngineerSystem DesignOnsite
  • This question tests the ability to design a high-throughput, low-latency leaderboard system, focusing on data structures for ranking, storage trade-offs, and scalability under heavy write and read loads.

    MetaSoftware EngineerSystem DesignOnsite
  • This question evaluates a candidate's ability to design scalable, fault-tolerant distributed systems for web-scale data acquisition, covering competencies such as crawler architecture, URL frontier management, deduplication, per-domain rate limiting and robots.

    MetaSoftware EngineerSystem DesignOnsite
  • This problem tests your ability to design a high-throughput, real-time messaging system capable of handling sudden spikes in concurrent viewers and maintaining low latency for chat delivery.

    MetaSoftware EngineerSystem DesignOnsite
  • This question evaluates a candidate's ability to design scalable, reliable ingestion and processing pipelines, time-series price storage and querying, deduplication across users, and notification/alert mechanisms for a large-scale price-tracking service.

    MetaSoftware EngineerSystem DesignOnsite
  • This interview question evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer for Design a mini banking system states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

    MetaSoftware EngineerSystem DesignTechnical Screen
  • This question evaluates a candidate's ability to design access control and visibility mechanisms for social posts, covering privacy models, efficient read-time enforcement, data modeling, caching strategies, and handling dynamic friendship and privacy updates.

    MetaSoftware EngineerSystem DesignOnsite
  • This question evaluates system-design competencies such as scalable architecture, data modeling for time-series price history, external data ingestion and integration, alerting and monitoring, and trade-off reasoning for large-scale services.

    MetaSoftware EngineerSystem DesignOnsite
  • This question evaluates system design competencies for building a large-scale notifications platform—covering architecture, APIs, data modeling, event pipelines, delivery semantics (retries, deduplication, idempotency), targeting/segmentation, localization, monitoring, and legal compliance such as GDPR/CCPA.

    MetaSoftware EngineerSystem DesignOnsite
  • This problem tests your ability to design a multi-stage recommendation pipeline that balances low-latency retrieval with high-precision ranking at scale.

    MetaSoftware EngineerSystem DesignTechnical Screen
  • This question evaluates a candidate's ability in scalable real-time system design, covering competencies such as stream processing, event aggregation, time-windowed metrics, handling late and out-of-order events, and designing for very high write throughput.

    MetaSoftware EngineerSystem DesignTechnical Screen
  • A Meta software-engineer system-design onsite question: design a real-time messenger supporting 1:1 and group chats at 100M MAU with p99 send-to-receive latency under 150 ms. It covers APIs, message ordering and idempotency, delivery semantics, multi-device sync, WebSocket fanout, storage/search, E2EE, abuse controls, retention/GDPR, multi-region failover, and observability.

    MetaSoftware EngineerSystem DesignOnsite
  • This question evaluates competence in designing large-scale recommendation systems and ML engineering skills such as candidate generation, feature store design (offline/online and point-in-time correctness), real-time signal ingestion, ranking and re-ranking, online exploration, cold-start strategies, feedback-bias mitigation, experimentation, and operational reliability. It is commonly asked to assess the ability to make architecture-level trade-offs for scalability, latency and throughput targets, multi-objective optimization, data governance and outage fallback behavior; it falls under the System Design and Machine Learning domain and requires practical, architecture-level application with conceptual trade-off reasoning rather than low-level implementation detail.

    MetaMachine Learning EngineerSystem DesignOnsite
  • This problem tests your ability to design a distributed, high-concurrency ledger system that maintains strict consistency and atomicity for financial transactions.

    MetaSoftware EngineerSystem DesignTechnical Screen
  • This question evaluates understanding of large-scale system design and distributed systems concepts, including concurrency control, consistency models, real-time fanout, payment idempotency, and failure handling for high-concurrency ticketing with interactive seat maps.

    MetaSoftware EngineerSystem DesignOnsite
  • This question assesses the ability to architect a scalable, multi-modal machine learning pipeline for detecting policy-violating content (weapon advertisements) within a high-throughput ad-delivery system.

    MetaMachine Learning EngineerSystem DesignTechnical Screen
  • This problem tests your ability to design a high-throughput, fault-tolerant ingestion pipeline and an aggregation service for real-time analytics dashboarding.

    MetaSoftware EngineerSystem DesignOnsite
  • This question evaluates system design competencies including distributed systems, scalability and capacity planning, data modeling and storage strategies, API design, media processing and CDN integration, consistency models, operational reliability, observability, and estimation.

    MetaSoftware EngineerSystem DesignOnsite
  • This question evaluates skills in designing scalable, reliable distributed systems with emphasis on state management (shopping cart persistence), real-time telemetry (courier location updates), workflow orchestration (order lifecycle and dispatch), and operational concerns like scalability and reliability.

    MetaSoftware EngineerSystem DesignOnsite
  • A Meta software-engineer system-design screen: design the backend for an online game leaderboard supporting score recording, a global top-N board, a friends board, a player's rank and nearby players, and daily/weekly/seasonal/all-time windows at high write volume and low read latency. The model answer separates a durable score event log from an in-memory sorted ranking store, computes the friends board on read, and covers tie-breaking, caching, sharding, consistency trade-offs, anti-cheat, and rebuilds.

    MetaSoftware EngineerSystem DesignTechnical Screen
  • This problem tests your ability to design a high-scale, fault-tolerant distributed system capable of processing massive volumes of real-time ad click events while ensuring data consistency and accuracy.

    MetaSoftware EngineerSystem DesignOnsite
  • This question tests your ability to design a high-performance, in-memory distributed metadata store that supports hierarchical file structures, quota management, and efficient retrieval of top-k largest files.

    MetaSoftware EngineerSystem DesignOnline Assessment
  • A Meta software engineer onsite system design question: build an eBay-style online auction platform supporting proxy bidding, reserve prices, buy-it-now and soft close at 500k concurrent auctions and 5M watchers with p99 bid-to-UI latency under 200 ms. The answer covers APIs, data model, the proxy-bid pricing algorithm, single-writer-per-auction consistency, idempotent bid placement, real-time push trade-offs (polling vs long polling vs SSE vs WebSockets), sharding, finalization and recovery. It also covers anti-sniping, fraud, escrow payments, auditability and capacity estimation.

    MetaSoftware EngineerSystem DesignOnsite
  • This problem tests the ability to design a low-latency, stateful system for a turn-based game, focusing on synchronization, undo history management, and scalable real-time leaderboard updates.

    MetaSoftware EngineerSystem DesignOnsite
  • This problem tests the ability to architect a distributed, multi-tenant system for sandboxed execution of untrusted code, emphasizing security, scalability, and performance isolation.

    MetaSoftware EngineerSystem DesignOnsite
  • This question evaluates a candidate's ability to design scalable, secure distributed systems with emphasis on architecture, data modeling, service design, sandboxed code execution, and performance under high load for an online coding platform.

    MetaSoftware EngineerSystem DesignOnsite

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