Design flight-price search service

Quick Overview

Design flight-price search service evaluates requirements, scale assumptions, API/data design, architecture, trade-offs, failure modes, and rollout in a realistic interview setting. A strong answer states assumptions, handles edge cases, explains trade-offs, and shows how to validate the result clearly.

Design flight-price search service

System Design: Cheapest Flight Search Across Multiple Providers

Context

Design a backend system that searches multiple flight providers (airlines, OTAs, GDS/aggregators) to return the cheapest flight tickets for users. The system must handle a high volume of queries, volatile prices, and frequent updates while remaining scalable and cost-efficient.

Requirements

Inputs: origin, destination, departure date(s), return date(s), cabin class, number of stops.
Date flexibility: exact dates or flexible windows (e.g., ±3 days) and calendar view.
Core outputs: list of itineraries/offers sorted by price with filters, plus a fast “cheapest per day” calendar.
System concerns to describe:
1. High-level architecture: ingestion from providers, normalization, deduplication, search index.
2. APIs: search, quote/validate (re-price), and ancillary endpoints.
3. Caching strategy.
4. Data freshness and update propagation.
5. Rate limiting, retries, and resilience patterns.
6. Consistency vs availability trade-offs.
7. Scalability and cost-control strategies.
8. Schemas and indexes that enable fast queries and rapid price updates.

Clarifying Questions to Ask Guidance

Clarify users, core use cases, read/write patterns, scale, latency, availability, and data retention.
State explicit assumptions before making sizing or architecture decisions.
Prioritize the functional path first, then address reliability, security, observability, and rollout.

What a Strong Answer Covers Guidance

A scoped requirements summary with concrete non-goals and success metrics.
API, data model, architecture, consistency, capacity, and operations.
Reasoned trade-offs among simple and scalable designs, including bottlenecks and failure modes.
A validation, monitoring, migration, and launch plan appropriate for the risk level.

Follow-up Questions Guidance

What breaks first at 10x traffic or data volume?
How would you degrade gracefully during dependency failures?
What metrics and alerts would prove the design is healthy after launch?

Design flight-price search service

Quick Overview

Design flight-price search service

Design flight-price search service

System Design: Cheapest Flight Search Across Multiple Providers

Context

Requirements

Clarifying Questions to Ask Guidance

What a Strong Answer Covers Guidance

Follow-up Questions Guidance

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