Design Flight Search & Booking Engine - System Design | WinJob

Problem Statement: Flight Search & Booking Platform

Design Google Flights / Kayak-class flight search & booking: GDS/NDC aggregation, itinerary merge, inventory holds, and ticket issuance. This section covers problem statement: flight search & booking platform in the understanding phase.

Operational detail

Quantify fan-out budgets, hold TTLs, and idempotency before naming SKUs. State AP for search caches and CP for booking/PNR rows with explicit stale-offer and double-booking stories.

Failure and edge cases

GDS timeout mid-merge, fare jump between select and pay, hold expired during checkout, airline 409 on last seat, and partial provider outage during holiday peak.

Interview checkpoints

javaOne Dark Pro

1 public record OfferHoldToken(String offerId, long inventoryVersion, Instant expiresAt) {}

pythonOne Dark Pro

1 def fan_out_budget_ms(provider_count: int, base: int = 2200) -> int:
2     return max(800, base - 40 * provider_count)

typescriptOne Dark Pro

1 export interface Itinerary { id: string; segments: Segment[]; priceCents: number; }
2 export function cheaperFirst(a: Itinerary, b: Itinerary): number { return a.priceCents - b.priceCents; }

Why interviewers care

Flight Search & Booking Engine interviews reward crisp scope, explicit trade-offs, and failure stories—not generic microservice diagrams.

Interview checkpoint

Name one failure story for Problem Statement: Flight Search & Booking Platform that proves you understand real outages, not happy-path diagrams.

Key Highlights

•500+ airline and GDS sources
•sub-3s ranked results under fan-out
•PNR after price-locked offer
•multi-leg graph combinatorics

1	def fan_out_budget_ms(provider_count: int, base: int = 2200) -> int:
2	return max(800, base - 40 * provider_count)

1	export interface Itinerary { id: string; segments: Segment[]; priceCents: number; }
2	export function cheaperFirst(a: Itinerary, b: Itinerary): number { return a.priceCents - b.priceCents; }