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Google system design interview questions
60 questions on this site are reported in Google software engineer interviews. Each has a full reference design (requirements, back-of-envelope numbers, components, user flows and deep dives with interviewer follow-ups). Each one can be walked through turn by turn and then sat as a mock. Patterns covered: key-generation, caching, cdn, analytics, real-time, websockets, fan-out, chat, transcoding, adaptive-bitrate, pipelines, storage, geospatial, routing, graphs, crdt, operational-transform, conflict-resolution, gpu-batching, streaming, scheduling, kv-cache, tool-calling, context-management, rate-limiting, prompt-caching, consistent-hashing, eviction, replication, hot-keys, frontier, politeness, dedupe, distributed-queues, algorithms, counters, redis, edge, chunking, sync, object-storage, tries, ranking, search, stream-processing, windowing, exactly-once, olap, leases, idempotency, queues, fault-tolerance, order-book, determinism, event-sourcing, low-latency, fairness, media-pipeline, ttl, persistent-connections, store-and-forward, end-to-end-encryption, delivery-receipts, push, proactive-caching, steering, resilience, geospatial-index, change-data-capture, aggregation, quorum-replication, gossip, lsm-tree, id-generation, clocks, bit-layout, k-sortable, sandboxing, job-queue, untrusted-code, contests, autoscaling, time-series, compression, cardinality, downsampling, alerting, geo-sharding, recommendations, bloom-filters, match-detection, write-heavy, comment-trees, voting, listings, contention, compare-and-set, durable-timers, bidding, broadcast, pub-sub, sse, sampling, moderation, heavy-hitters, count-min-sketch, sliding-windows, webrtc, sfu, real-time-media, congestion-control, multi-region, inverted-index, scatter-gather, tail-latency, prefetching, licensing, offline, counting, playlists, smtp-ingress, spam-filtering, per-user-sharding, peer-to-peer, bandwidth, integrity, stragglers, vector-search, feature-store, consensus, fencing-tokens, leader-election, watches, erasure-coding, range-partitioning, durability, strong-consistency, recurrence, time-zones, interval-search, deployment, canary, reconciliation, rollback, blast-radius, log-aggregation, tiered-storage, backpressure, multi-tenancy, live-video, request-coalescing, adaptive-scheduling, change-detection, range-queries, async-pipeline, spatial-matching, leaderboards, privacy, multiplayer, last-writer-wins, fractional-indexing, checkpoints, load-balancing, networking, health-checks, control-plane, rag, hybrid-search, permissions, anycast, tiered-cache, cache-invalidation, api-gateway, authentication, quotas, auctions, budget-pacing, git, quorum, content-addressing, thundering-herd, ledger, sharding, fraud, fintech, short-video, prefetch, session-ranking, exploration, clustering, ingestion, edge-caching, deduplication, latency-budget, cancellation, prefix-caching, context-assembly, code-completion, expiry, abuse, random-walks, visual-search, image-serving, ann-indexes, quantisation, segments, perceptual-hashing, review-queues, policy-engine, audit-log, saga, external-inventory, bin-packing, failure-detection.
Run an AI mock Google interview →One of these questions, run as a live round in that style, with a debrief at the end.
Attribution comes from public interview guides and candidate reports, not from Google. It indicates where a question has been asked, nothing more.
Google questions
hard
Design Slack
Real-time team messaging: channels, DMs, presence, history and search for millions of concurrent users.
hard
Design YouTube
Upload, transcode, and stream video to a billion viewers: a processing pipeline on one side, a CDN problem on the other.
hard
Design Google Maps
Map tiles, place search, turn-by-turn routing with live traffic, and ETAs for a billion users.
hard
Design Google Docs
Real-time collaborative editing: many cursors in one document, every keystroke converging to the same text, offline edits merged on reconnect.
hard
Design an LLM Inference Service
Serve a large language model behind an API: queue the requests, batch them onto scarce GPUs, stream tokens back, and keep every accelerator busy without blowing the latency budget.
hard
Design ChatGPT
An AI chat assistant for 100 M weekly users whose streamed answers survive dropped connections, call tools mid-answer, and share scarce GPUs across tiers.
hard
Design a Distributed Cache
A Redis-like cache as a service: hundreds of nodes, terabytes of memory, sub-millisecond gets, and a cluster that survives losing a machine mid-request.
hard
Design a Web Crawler
Fetch billions of pages a month politely, discover new links, skip duplicates, and keep the copy fresh without getting the crawler banned.
medium
Design a Rate Limiter
A distributed service that decides, in under a millisecond, whether a request from a client is allowed under its quota.
hard
Design Dropbox
Keep a folder identical on every device: upload huge files in resumable chunks, push only what changed, and reconcile two machines that both edited the same file offline.
medium
Design Search Autocomplete
Suggest the top ten completions after every keystroke, in under fifty milliseconds, from what the world searched for in the last hour, without suggesting anything that gets you in the newspaper.
hard
Design an Ad Click Aggregator
Count a million ad clicks a second, show advertisers a dashboard that is seconds behind, stop a campaign the moment its budget runs out, and be exactly right when the invoice is cut.
medium
Design a Distributed Job Scheduler
Run millions of cron jobs and one-off tasks on time across a fleet, exactly once each, and keep going when a worker dies halfway through one.
hard
Design a Stock Exchange
Match buy and sell orders in microseconds, in a strict and provable order, never lose a fill, and stay correct when the matching engine dies mid-trade.
hard
Design Instagram
Upload photos, publish posts and stories, and load a feed of them for 500 M daily users, with every image served from a CDN in milliseconds.
hard
Design WhatsApp
Deliver 50 billion end-to-end encrypted messages a day to phones that are often offline, with sent, delivered and read ticks, and a server that cannot read any of it.
hard
Design Netflix
Stream a fixed catalog to 40 M people at once, 200 Tbps at peak, starting in under two seconds, from cache servers placed inside the viewers’ own internet providers.
medium
Design Yelp
Find the best places near you, filtered by what is open now, from 200 M businesses, in under 200 ms, and keep ratings honest as reviews arrive.
hard
Design a Distributed Key-Value Store
A Dynamo-style store that keeps 10 billion keys on dozens of machines, survives node and rack failures, and lets each caller trade consistency for latency with N, R and W.
medium
Design a Unique ID Generator
Hand out a million 64-bit ids a second across many hosts and regions, never twice, roughly in time order, with no central bottleneck and no trust in the wall clock.
hard
Design LeetCode
Run untrusted code from strangers against hidden tests in a dozen languages, return a fair verdict in seconds, and survive 50,000 people submitting in the last minutes of a contest.
hard
Design a Metrics and Monitoring System
Ingest 10 million samples a second from 100,000 hosts, keep them queryable for a year at shrinking resolution, draw dashboards in under a second, and page the right person within a minute.
medium
Design Tinder
Show each person a deck of nearby profiles that fit both people’s preferences, never repeat one, take 2 billion swipes a day, and announce a match the instant two people like each other.
medium
Design Reddit
Serve communities of posts with deeply nested comment threads, take tens of thousands of votes a second, rank by hot and best, and keep a 50,000-comment thread fast while it is still growing.
hard
Design an Online Auction
Run 50 million live eBay-style auctions: order every bid strictly per auction, push the price to watchers live, and close each auction exactly once.
hard
Design Live Comments
Comments and reactions on live video that reach viewers within two seconds, at 50 M concurrent viewers and 5 M on one stream.
hard
Design a Top-K Heavy Hitters Service
Rank the top 1,000 videos by views over the last minute, hour, day and all time, from a million views a second.
hard
Design Zoom
Real-time audio, video and screen share for 2 to 1,000 people per meeting, 300 M participants a day, under 150 ms mouth to ear.
hard
Design Google Search
Search 50 billion pages at 100 k queries a second: the ten best results with snippets in under 200 ms, and news within minutes.
hard
Design Spotify
Stream 100 M tracks to 600 M listeners with sound in 200 ms, offline downloads, regional licensing, and every play counted for royalties.
hard
Design Gmail
Receive, filter, store and search email for 1.5 billion users: 200 billion inbound messages a day, mostly spam, kept for 20 years.
hard
Design a Large File Distribution System
Get a 200 GB checkpoint from one origin onto 10,000 machines in five data centres within minutes, under capped links, verifying every byte.
hard
Design a Recommendation System
The “recommended for you” video home feed: 50 personalised videos picked from billions for 500 M daily users in under 200 ms.
hard
Design a Distributed Lock Service
A Chubby-style lock service for 50 k processes: leases, leader election, fencing tokens and watched config, never letting two holders act at once.
hard
Design an Object Storage Service
An S3-like store for objects from bytes to terabytes, with eleven nines of durability and strong read-after-write consistency at exabyte scale.
hard
Design Google Calendar
Recurring events, invitations, free/busy and reminders for 500 million users, correct in every time zone and synced to every device within seconds.
hard
Design a Code Deployment System
Build each merge once into a signed artifact, roll it out in stages to 50,000 hosts in 10 regions, and roll back automatically on regression.
hard
Design a Distributed Logging System
Collect 10 million log lines a second from 100,000 hosts, make them searchable within seconds, stream them live, and keep a year affordably.
hard
Design Twitch
Ingest 100 k live broadcasts, transcode them in real time, and deliver each about three seconds behind live, to three viewers or 500 k.
hard
Design a Price Tracker
Track 500 M products' price history and alert 50 M users when a price drops below their target, in time to buy.
hard
Design Strava
Record runs and rides offline, process each upload into a map, stats and segment efforts, and rank them for 100 M athletes.
hard
Design Figma
500 k design files open at once, some with 200 people: objects converge live, cursors stream, and 300 MB files open in seconds.
hard
Design a Load Balancer
Spread 5 M requests a second over 50 k backends, terminate TLS, route by host and path, survive losing any balancer or data centre.
hard
Design a RAG System
An assistant that answers employees’ questions from their company’s documents, with citations, only from what each user may open, minutes after edits.
hard
Design a CDN
A multi-tenant CDN for 30 M customer domains: 300 PoPs, 50 M requests a second served mostly from cache, and global purges in seconds.
hard
Design an API Gateway
One front door for public and partner APIs: authenticate, limit and route 1 M requests a second to 300 services, adding under 10 ms.
hard
Design an Ad Serving System
Pick the best of 10 M active ads for 5 M requests a second in under 100 ms, within every campaign’s targeting, budget and frequency caps.
hard
Design GitHub
Host 400 M git repositories on replicated file servers, serve 100 k fetches a second, and run pull requests, forks and webhooks on top.
hard
Design Venmo
80 M users paying friends instantly: 15 M transfers a day on a sharded double-entry ledger, funded and cashed out over slow bank rails.
hard
Design TikTok
A full-screen feed of short videos for 1 B daily users, where the next clip starts instantly and every swipe reshapes what comes next.
hard
Design Google News
Collect 2 M articles a day from 50,000 publishers, group them into stories, rank them per edition, and serve 300 M daily readers.
hard
Design GitHub Copilot
Inline AI code suggestions for 10 M developers, shown within 300 ms of a pause in typing, when most requests are never used.
hard
Design Nearby Friends
Show each user which friends are within 5 miles, refreshed every 30 s, for 10 M concurrent users, without leaking anyone’s location.
medium
Design Pastebin
Store and serve 10 M text pastes a day behind unguessable links: expiry that is never late, burn after reading, and abuse takedown.
hard
Design Pinterest
Save images to boards, browse a personalised grid and search by picture: 100 M daily users, 5 B distinct images behind 100 B saves.
hard
Design a Vector Database
A managed vector database: 10,000 tenants, 20 B vectors, filtered top-k in under 50 ms at 0.95 recall, and writes searchable in seconds.
hard
Design a Content Moderation System
Catch spam, nudity, hate and illegal media in 4 billion daily posts and comments before they spread, with 15,000 reviewers for the hard cases.
hard
Design a Flight Booking System
Answer 50 M searches a day from 20 slow, metered suppliers through a fare cache, then book seats you do not own, exactly once.
hard
Design a Container Orchestrator
Place 300,000 containers on 10,000 machines from declared desired state, keep them running through failures, and give every service a stable address.
What the Google round looks like
45 minutes, whiteboard or shared document, usually one open-ended design with the interviewer steering into depth. Now asked at more levels than it used to be.
What it is reported to weigh
- Scale: the numbers behind the design, and what changes at 10x
- Technical depth on whichever component the interviewer picks
- Data modelling and storage choices, defended against the access patterns
- Clear tradeoffs rather than a single asserted answer
The common mistake
Depth is sampled, not announced. Any component you name can become the next fifteen minutes, so do not put something on the board you cannot open up.
From public interview guides and candidate reports, and Google’s own interview guidance where it publishes any. Not endorsed by Google. Formats change; treat it as a prior, not a promise.
How to prepare for the Google system design interview
Large-company loops run 45 to 60 minutes, expect numbers, and spend most of the time on deep dives. Walk through a question to see how a strong candidate paces the hour, sit the same question as a mock until you can produce the requirements, the estimates and the design without looking, then read the interview framework guide for how to structure the hour. The other questions on the site teach patterns that show up in Google interviews under different names.
- Design a Payment Systemconsistency · idempotency · ledger
- Design a News Feedfan-out · ranking · caching
- Design a Matchmaking Systemqueues · scheduling · latency
- Design Ubergeospatial · matching · streaming
- Design a Notification Systemfan-out · multi-channel · idempotency
- Design Ticketmasterinventory · reservations · locking
- Design a Project-to-Contractor Matching Systemrecommendations · ranking · marketplace
- Design a Real-Time Leaderboardsorted-sets · ranking · sharding
- Design Airbnbavailability-search · inventory · double-booking
- Design a Distributed Message Queueappend-only-log · partitioning · replication
- Design DoorDashstate-machine · dispatch · eta-prediction
- Design AWS Step Functionsworkflow-orchestration · event-sourcing · durable-timers
- Design Apache Airflowworkflow-orchestration · dag-scheduling · backfills
- Design Zapierworkflow-orchestration · polling · webhooks
- Design Amazonshopping-cart · inventory · caching
- Design Post Searchsearch · real-time · privacy
- Design a Social Graphgraph · sharding · in-memory
- Design a Multiplayer Game Backendreal-time · udp · game-servers
- Design an A/B Testing Platformexperimentation · hashing · statistics
- Design a Fraud Detection Systemfraud · feature-store · stream-processing
- Design a Webhook Delivery Systemwebhooks · retries · isolation
- Design Robinhoodmarket-data · order-management · ledger
- Design Discordreal-time · fan-out · actors
Questions people ask about the Google system design interview
What system design questions does Google ask?
Questions reported in Google system design interviews include URL Shortener, Slack, YouTube, Google Maps, Google Docs, LLM Inference Service, ChatGPT and Distributed Cache, among 60 in total. Between them they test key generation, caching, cdn, analytics, real time and websockets. The reports come from public interview guides and candidate accounts, not from Google, so practise the patterns rather than memorising one list.
What is the Google system design interview like?
45 minutes, whiteboard or shared document, usually one open-ended design with the interviewer steering into depth. Now asked at more levels than it used to be.
What does Google look for in a system design interview?
Reports say the Google round weighs 4 things. 1. Scale: the numbers behind the design, and what changes at 10x. 2. Technical depth on whichever component the interviewer picks. 3. Data modelling and storage choices, defended against the access patterns. 4. Clear tradeoffs rather than a single asserted answer. Depth is sampled, not announced. Any component you name can become the next fifteen minutes, so do not put something on the board you cannot open up.
How do I prepare for the Google system design interview?
Practise the questions reported there out loud, under a 45-minute clock: requirements with numbers first, then estimates, a high-level design, and deep dives into the two or three hardest parts. Start with URL Shortener: watch a strong candidate answer it turn by turn, then sit it yourself. Then cover the patterns the round leans on (key generation, caching, cdn and analytics) with one more question each.