Design: Design a Ticket Booking System (Ticketmaster)

Endpoints

Add the operations your service exposes. Method, path, and status codes make your API much easier to review.

Start with a template

Applies to all endpoints

Policies that aren't specific to a single endpoint — auth, rate limits, versioning, and other notes.

Authentication

Rate limiting

Versioning

Notes (idempotency, redirect choice, error shape, anything else)

Diagram

Draw the components and how traffic flows between them. Notes below the canvas are optional — the Walkthrough panel is the primary place to narrate flows.

Draw the architecture so the components and connections tell the core story; flow narration in Notes is optional but recommended.

Components

Click palette â†’ add

Drag edge dot â†’ connect

Double-click node/edge â†’ rename

Shift+drag or box-select â†’ multi

Click any component on the left to add it here.

Drag the edge of a node to connect it to another.

Double-click any arrow to label it.

Notes (optional) — flow narration, trade-offs, chosen alternatives0 elements on canvas

Request walkthrough

Trace each core requirement as an ordered sequence of hops through your diagram. Use component names from your canvas for the From / To columns.

1

Users can browse events and view available seats on a venue map.

FromToAction / payload

1.

2.

2

Users can select 1-6 seats and proceed to checkout.

FromToAction / payload

1.

2.

3

Selected seats are temporarily held (locked) for the user during checkout (e.g. 10 minutes).

FromToAction / payload

1.

2.

4

After successful payment, seats are confirmed and a booking is created.

FromToAction / payload

1.

2.

5

No seat can be sold to two different users (no double-booking).

FromToAction / payload

1.

2.

Storage schema

For each entity, declare how it's stored. Sharding key is the interesting one — pick the access pattern it optimises for.

Event

A concert, sports match, or show at a specific venue, date, and time.

In-memory / derived

Storage type

Primary key

Sharding / partition key

Critical fields

Notes (indexes, TTL, access pattern)

Seat

A specific seat in a venue with section, row, number. States: available → held → booked.

In-memory / derived

Storage type

Primary key

Sharding / partition key

Critical fields

Notes (indexes, TTL, access pattern)

Hold

A temporary lock on 1-6 seats for a user, with a TTL (e.g. 10 min). Expires if payment is not completed.

In-memory / derived

Storage type

Primary key

Sharding / partition key

Critical fields

Notes (indexes, TTL, access pattern)

Booking

A confirmed reservation: user + seats + payment reference. Immutable after creation.

In-memory / derived

Storage type

Primary key

Sharding / partition key

Critical fields

Notes (indexes, TTL, access pattern)

Component choices

Pick one per row and give a one-line reason. These are the concrete technology decisions your diagram implies.

Load Balancer

How traffic is distributed to your app servers.

Cache

Where hot reads are served from.

Database

Primary durable store for entities.

Queue / Stream

Async work buffer for writes/fan-out.

Your diagram

No components drawn yet — edit the diagram before answering.

Iterate on your design — don't start over.

Each scenario below probes a specific weakness in a typical HLD. Reference components from your diagram by name, describe what breaks and at what load, then name the minimum change that fixes it. Strong answers identify the precise failure mode — not just "scale it up".

1

A scalper bot holds 500 seats across 50 browser sessions, waits 9 minutes, then buys them all. How do you prevent this?

Probes: abuse rate limiting

Your answer

Design a Ticket Booking System (Ticketmaster)

API & core entities

Endpoints

Applies to all endpoints

High-level design

Deep dives