hard
Design a Payment System
Accept card payments for an e-commerce platform, move money correctly exactly once, and be able to prove it.
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Uber system design interview questions
28 questions on this site are reported in Uber 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: consistency, idempotency, ledger, fintech, geospatial, routing, graphs, cdn, matching, streaming, marketplace, fan-out, multi-channel, rate-limiting, priority-queues, consistent-hashing, eviction, replication, hot-keys, algorithms, counters, redis, edge, inventory, reservations, locking, queueing, thundering-herd, scheduling, leases, queues, fault-tolerance, persistent-connections, store-and-forward, end-to-end-encryption, delivery-receipts, push, geospatial-index, search, ranking, change-data-capture, aggregation, id-generation, clocks, bit-layout, k-sortable, availability-search, double-booking, holds, calendar-sync, append-only-log, partitioning, consumer-groups, exactly-once, time-series, compression, cardinality, downsampling, alerting, state-machine, dispatch, eta-prediction, location-tracking, workflow-orchestration, event-sourcing, durable-timers, sharding, dag-scheduling, backfills, row-locking, consensus, fencing-tokens, leader-election, watches, deployment, canary, reconciliation, rollback, blast-radius, log-aggregation, inverted-index, tiered-storage, backpressure, multi-tenancy, async-pipeline, spatial-matching, leaderboards, privacy, load-balancing, networking, health-checks, control-plane, api-gateway, authentication, quotas, experimentation, hashing, statistics, stream-processing, analytics, real-time, pub-sub, fraud, feature-store, low-latency, exploration, caching, saga, external-inventory, bin-packing, failure-detection.
Run an AI mock Uber 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 Uber. It indicates where a question has been asked, nothing more.
Uber questions
hard
Design Google Maps
Map tiles, place search, turn-by-turn routing with live traffic, and ETAs for a billion users.
hard
Design Uber
Match riders with nearby drivers in seconds, track trips live, and price them, for millions of concurrent users worldwide.
medium
Design a Notification System
Deliver push, email, SMS and in-app notifications to hundreds of millions of users: the right channel, once, on time, and never at 3 a.m.
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.
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 Ticketmaster
Sell 60 000 seats in ten minutes to a million people at once: hold a seat while someone pays, never sell it twice, and keep the site up when demand is a hundred times supply.
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 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.
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.
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 Airbnb
Search 7 M listings by place, dates and price, book a stay without ever selling the same night twice, and keep calendars in sync with hosts’ other platforms.
hard
Design a Distributed Message Queue
A Kafka-style log that ingests a million messages a second, keeps them in order per key, replicates them so no acknowledged message is lost, and lets many consumer groups read at their own pace.
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.
hard
Design DoorDash
Take a food order, get a restaurant to cook it and a courier to arrive just as it is ready, and keep three parties in sync across millions of orders a day.
hard
Design AWS Step Functions
A managed workflow engine that runs 200 M state-machine executions a day, some lasting a year, applying every transition exactly once.
hard
Design Apache Airflow
Schedule and run twenty thousand data pipelines as dependency graphs, each run tied to a slice of time, so a failed night can be retried or a year backfilled safely.
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 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 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 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 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 A/B Testing Platform
Run 500 experiments at once on 300 M users: sticky variants in microseconds, exposure logging, and confidence intervals teams can trust.
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.
hard
Design a Fraud Detection System
Allow, block or challenge 10,000 card payments a second in under 100 ms, then learn from chargebacks that arrive months later.
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 Uber round looks like
45–60 minutes, usually a real-time, geospatial or marketplace problem close to what the company runs.
What it is reported to weigh
- Real-time data flow and the freshness the product needs
- Geospatial indexing and matching under load
- Consistency where money and commitments are involved
- Degradation during surges and outages
The common mistake
Hand-waving the matching or pricing logic. That is the part they want opened up.
From public interview guides and candidate reports, and Uber’s own interview guidance where it publishes any. Not endorsed by Uber. Formats change; treat it as a prior, not a promise.
How to prepare for the Uber 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 Uber interviews under different names.
- Design a URL Shortenerkey-generation · caching · cdn
- Design Slackreal-time · websockets · fan-out
- Design a News Feedfan-out · ranking · caching
- Design YouTubetranscoding · cdn · adaptive-bitrate
- Design a Matchmaking Systemqueues · scheduling · latency
- Design Google Docscrdt · operational-transform · websockets
- Design an LLM Inference Servicegpu-batching · streaming · scheduling
- Design ChatGPTstreaming · tool-calling · context-management
- Design a Web Crawlerfrontier · politeness · dedupe
- Design Dropboxchunking · dedupe · sync
- Design Search Autocompletetries · ranking · caching
- Design an Ad Click Aggregatorstream-processing · windowing · exactly-once
- Design a Stock Exchangeorder-book · determinism · event-sourcing
- Design a Project-to-Contractor Matching Systemrecommendations · ranking · marketplace
- Design Instagrammedia-pipeline · object-storage · fan-out
- Design Netflixcdn · proactive-caching · adaptive-bitrate
- Design a Real-Time Leaderboardsorted-sets · ranking · sharding
- Design a Distributed Key-Value Storeconsistent-hashing · quorum-replication · conflict-resolution
- Design LeetCodesandboxing · job-queue · untrusted-code
- Design Tindergeo-sharding · recommendations · bloom-filters
- Design Redditcomment-trees · voting · ranking
- Design Zapierworkflow-orchestration · polling · webhooks
- Design an Online Auctioncontention · compare-and-set · durable-timers
- Design Live Commentsbroadcast · pub-sub · sse
- Design a Top-K Heavy Hitters Serviceheavy-hitters · count-min-sketch · sliding-windows
- Design Zoomwebrtc · sfu · real-time-media
- Design Google Searchinverted-index · scatter-gather · tail-latency
- Design Spotifyprefetching · licensing · offline
- Design Gmailsmtp-ingress · spam-filtering · per-user-sharding
- Design Amazonshopping-cart · inventory · caching
- Design a Large File Distribution Systempeer-to-peer · chunking · bandwidth
- Design a Recommendation Systemrecommendations · ranking · vector-search
- Design an Object Storage Serviceerasure-coding · range-partitioning · durability
- Design Google Calendarrecurrence · time-zones · fan-out
- Design Twitchlive-video · low-latency · transcoding
- Design a Price Trackeradaptive-scheduling · change-detection · time-series
- Design Post Searchsearch · real-time · privacy
- Design Figmamultiplayer · last-writer-wins · websockets
- Design a RAG Systemrag · vector-search · hybrid-search
- Design a CDNcdn · anycast · tiered-cache
- Design a Social Graphgraph · sharding · in-memory
- Design an Ad Serving Systemauctions · budget-pacing · ranking
- Design GitHubgit · replication · quorum
- Design Venmoledger · sharding · hot-keys
- Design a Multiplayer Game Backendreal-time · udp · game-servers
- Design TikTokshort-video · prefetch · session-ranking
- Design Google Newsclustering · ingestion · ranking
- Design GitHub Copilotlatency-budget · cancellation · prefix-caching
- Design Pastebinobject-storage · expiry · caching
- Design a Webhook Delivery Systemwebhooks · retries · isolation
- Design Pinterestrandom-walks · visual-search · deduplication
- Design a Vector Databasevector-search · ann-indexes · quantisation
- Design a Content Moderation Systemmoderation · perceptual-hashing · review-queues
- Design Robinhoodmarket-data · order-management · ledger
- Design Discordreal-time · fan-out · actors
Questions people ask about the Uber system design interview
What system design questions does Uber ask?
Questions reported in Uber system design interviews include Payment System, Google Maps, Uber, Notification System, Distributed Cache, Rate Limiter, Ticketmaster and Distributed Job Scheduler, among 28 in total. Between them they test consistency, idempotency, ledger, fintech, geospatial and routing. The reports come from public interview guides and candidate accounts, not from Uber, so practise the patterns rather than memorising one list.
What is the Uber system design interview like?
45–60 minutes, usually a real-time, geospatial or marketplace problem close to what the company runs.
What does Uber look for in a system design interview?
Reports say the Uber round weighs 4 things. 1. Real-time data flow and the freshness the product needs. 2. Geospatial indexing and matching under load. 3. Consistency where money and commitments are involved. 4. Degradation during surges and outages. Hand-waving the matching or pricing logic. That is the part they want opened up.
How do I prepare for the Uber 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 Payment System: watch a strong candidate answer it turn by turn, then sit it yourself. Then cover the patterns the round leans on (consistency, idempotency, ledger and fintech) with one more question each.