Katkat

Topic

System Design interview questions

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

Questions1311

60 easy819 medium432 hard

Your progress0/1311

System Design interview questions by the numbers

Last updated

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 511–540 of 1311 results

  • Design a pipeline that turns a firehose of untrusted app reviews into LLM-written theme digests for internal product teams, with defenses against prompt injection, spam and personal data leakage.

    GoogleSoftware EngineerSystem DesignOnsite
  • Staff-level system design question on building a distributed in-memory cache shared by many backend services. It covers the client API, node memory layout and eviction, key placement and rebalancing, replication and failover, freshness against the database, hot keys, miss storms and cold starts.

    GoogleSoftware EngineerSystem DesignOther
  • Technical deep-dive question from a senior software engineer loop at Google: explain the architecture of a service you own and walk through its technical details. It tests whether a candidate can present purpose, scale and data flow clearly, then defend design choices, failure handling and trade-offs under probing.

    GoogleSoftware EngineerSystem DesignOther
  • Design a multiresolution map that turns over one hundred million points into cached heat maps and detailed pins without overwhelming the browser.

    GoogleFrontend EngineerSystem DesignOnsite
  • Design an ephemeral direct messaging system that reliably deletes messages after viewing across multiple devices, handles offline delivery, and balances user privacy with abuse reporting.

    GrammarlySoftware EngineerSystem DesignTechnical Screen
  • This question evaluates a candidate's ability in designing real-time collaborative systems, covering concurrency control (OT/CRDT trade-offs), low-latency messaging, data modeling, persistence, client-server synchronization, and fault tolerance for unreliable networks.

    GrammarlySoftware EngineerSystem DesignTechnical Screen
  • This question evaluates a candidate's competence in large-scale system design and distributed messaging, including API and data model design, read-once delivery semantics, consistency trade-offs, and operational concerns like scaling, partitioning, and failure handling.

    GrammarlySoftware EngineerSystem DesignOnsite
  • This question evaluates system design and distributed-systems competencies such as real-time collaboration, concurrent edit conflict resolution, data modeling for workbooks and sheets, session management, persistence and concrete API design.

    GrammarlySoftware EngineerSystem DesignOnsite
  • This question assesses the ability to design a distributed reservation system that handles high concurrency, prevents double-booking, and ensures data consistency.

    GrammarlySoftware EngineerSystem DesignTechnical Screen
  • This problem tests your ability to design a scalable scheduling system, specifically focusing on data modeling for temporal availability, handling conflicting shift assignments, and API design for concurrent updates.

    GustoSoftware EngineerSystem DesignTechnical Screen
  • This question assesses the ability to design a URL shortening service (like Bitly) focusing on scalability, distributed ID generation, and efficient data retrieval.

    HackerRankSoftware EngineerSystem DesignTechnical Screen
  • This question tests your ability to design a zero-downtime database migration strategy that handles heterogeneous database engines while maintaining strict data consistency across concurrent read and write operations.

    HadrianSoftware EngineerSystem DesignOnsite
  • This question tests your ability to design a scalable cloud file storage and collaboration platform, focusing on the architectural separation between metadata and blob storage, chunking, deduplication, and granular access control.

    HarveySoftware EngineerSystem DesignOnsite
  • Design drive-style file storage with metadata and blob separation, ACL checks, resumable chunk uploads, atomic publication, and version conflicts.

    HarveySoftware EngineerSystem DesignOnsite
  • Design persistent real-time chat with conversation ordering, idempotent sends, paginated history, optimistic state, delivery receipts, and reconnect catch-up.

    HarveyFrontend EngineerSystem DesignOther
  • This question evaluates competency in designing large-scale distributed file storage and collaboration systems, covering storage and metadata modeling, API design, synchronization and consistency models, resumable large-file handling, versioning, access control, scalability, availability, durability, and security.

    HarveySoftware EngineerSystem DesignTechnical Screen
  • Design an enterprise-grade Retrieval-Augmented Generation (RAG) system capable of answering complex natural language queries over millions of internal documents with high precision, low latency, and verifiable citations.

    HarveySoftware EngineerSystem DesignOnsite
  • Design an enterprise-grade virtual data room (VDR) for secure legal document sharing, focusing on multi-tenant access control, instant permission revocation, dynamic watermarking, and tamper-evident audit logging.

    HarveySoftware EngineerSystem DesignOnsite
  • This question evaluates a candidate's competency in distributed systems and storage architecture, covering metadata schema design, concurrency control for atomic per-directory limits and renaming, transaction boundaries and idempotency, storage models for file bytes, large-file handling, consistency and failure modes, scalability and partitioning, observability, lifecycle management, and security. It is in the System Design domain and is commonly asked because it reveals how a candidate reasons about architectural trade-offs and practical implementation concerns; it tests both high-level conceptual design and hands-on practical application.

    HarveySoftware EngineerSystem DesignTechnical Screen
  • This question evaluates a candidate's competencies in secure backend system design, covering authentication and authorization, metadata and object storage architectures, integrity verification for chunked uploads, scalability, and operational reliability.

    HarveyBackend EngineerSystem DesignOnsite
  • A Harvey AI system design screen on determining whether two files are byte-identical while ignoring metadata, then scaling to deduplication. It covers hashing algorithm choice (SHA-256/BLAKE3 vs MD5/xxHash), multi-stage verification, collision and false-positive mitigation, streaming and parallel hashing, content-defined chunking, and persistent hash-index/service design.

    HarveySoftware EngineerSystem DesignTechnical Screen
  • Design a short-term rental search and booking system, balancing eventual consistency in search discovery with strict consistency during reservations and checkout.

    HeadwaySoftware EngineerSystem DesignTechnical Screen
  • Design the backend for an online store's shopping cart, with the focus on inventory consistency: when stock is reserved, how two shoppers racing for the last unit are resolved, and how abandoned holds are released. It tests data modeling, concurrency control, checkout failure handling and contention on popular items.

    HeadwaySoftware EngineerSystem DesignTechnical Screen
  • This question evaluates a candidate's competency in performance troubleshooting, capacity planning, and scalable system architecture, focusing on diagnosing overload causes and quantifying infrastructure needs.

    HeadwaySoftware EngineerSystem DesignTechnical Screen
  • This question evaluates a candidate's ability to design scalable, reliable backend architectures that integrate LLMs and multi-agent orchestration, covering distributed systems, streaming responses, conversation context management, tool integrations, observability, and secure handling of sensitive financial data.

    HebbiaSoftware EngineerSystem DesignOnsite
  • This question tests the ability to design a resilient client-server architecture for a collaborative editing application that must function reliably under network instability.

    HexSoftware EngineerSystem DesignOnsite
  • This problem tests the ability to design a high-availability, accessible, and modular UI/UX system under significant physical and connectivity constraints.

    HexSoftware EngineerSystem DesignOnsite
  • This question evaluates system design competencies including large-scale backend architecture, data modeling and indexing, database internals, concurrency control to prevent overselling, and high-throughput real-time streaming and metrics for live updates.

    Hot Agent StartupSoftware EngineerSystem DesignOnsite
  • A HubSpot software-engineer onsite system-design question: design a Netflix-like video streaming platform covering catalog browse by genre and curated rails (Recently Added, Top Ten), search, adaptive-bitrate playback across web, mobile and TV, cross-device resume, and an upload-to-streamable ingest pipeline. It evaluates service decomposition, data models and API contracts, transcoding and CMAF/multi-DRM packaging, CDN and caching strategy, session concurrency and consistency, multi-region failover, observability and A/B testing, graceful degradation, and cost control at millions of concurrent viewers. The worked solution sizes egress and heartbeat load, corrects the common concurrency, resume, and cache-TTL mistakes, and marks the MVP cut line.

    HubSpotSoftware EngineerSystem DesignOnsite
  • A HubSpot onsite system-design question: build a weather data platform that ingests hourly dumps for ~2,000 U.S. locations and serves the current temperature with an at-most-10-minute freshness SLA. It tests ingestion pipelines, idempotent retries and backfill, caching and invalidation, storage modeling, rate-limit handling, scaling, and observability on freshness SLOs.

    HubSpotSoftware EngineerSystem DesignOnsite

More topics