System Design: Cheapest Flight Search Across Multiple Providers
Context
Design a backend system capable of searching across numerous flight providers, including airlines, Online Travel Agencies (OTAs), and Global Distribution Systems (GDS/aggregators), to identify and present the cheapest flight tickets to users. The system must be engineered to manage a high volume of user queries, accommodate highly volatile pricing, and process frequent data updates, all while maintaining high scalability and cost-efficiency.
Requirements
Inputs
The system must accept the following search parameters:
- Origin
- Destination
- Departure date(s)
- Return date(s)
- Cabin class
- Number of stops
Date Flexibility
The system should support:
- Exact date searches
- Flexible date windows (e.g., ±3 days around a specified date)
- A calendar view displaying "cheapest per day" options
Core Outputs
The primary outputs should include:
- A list of flight itineraries or offers, sorted by price, with various filtering options.
- A fast "cheapest per day" calendar view.
System Concerns to Address
The design discussion should explicitly cover the following architectural aspects:
- High-level Architecture: Detail the overall system structure, including components for data ingestion from providers, data normalization, deduplication logic, and the design of the search index.
- APIs: Define the necessary API endpoints, specifically for search, quoting/validation (re-pricing), and any ancillary services.
- Caching Strategy: Outline a comprehensive caching approach to optimize performance and reduce load.
- Data Freshness and Update Propagation: Describe mechanisms to ensure data freshness and efficiently propagate updates throughout the system.
- Rate Limiting, Retries, and Resilience Patterns: Explain how the system handles external provider rate limits, implements retry logic, and incorporates other resilience patterns.
- Consistency vs. Availability Trade-offs: Discuss the architectural decisions made regarding consistency and availability, and their implications.
- Scalability and Cost-Control Strategies: Detail strategies for scaling the system to meet demand and controlling operational costs.
- Schemas and Indexes: Propose database schemas and indexing strategies optimized for fast queries and rapid price updates.
AI interview prep
Core dilemma
Balancing the need for real-time, accurate, and comprehensive flight pricing data from a multitude of external, often unreliable, sources against the demands of ultra-low latency user queries, high throughput, and cost-efficiency. This involves managing massive, volatile datasets, external API dependencies, and complex indexing for diverse search patterns.
3 tradeoffs and 3 stress tests locked
Interview prep
Unlock the interviewer X-Ray rubric, tradeoff matrix, stress tests, clarifying questions, and key concepts.
System Design: Cheapest Flight Search Across Multiple Providers
Context
Design a backend system capable of searching across numerous flight providers, including airlines, Online Travel Agencies (OTAs), and Global Distribution Systems (GDS/aggregators), to identify and present the cheapest flight tickets to users. The system must be engineered to manage a high volume of user queries, accommodate highly volatile pricing, and process frequent data updates, all while maintaining high scalability and cost-efficiency.
Requirements
Inputs
The system must accept the following search parameters:
- Origin
- Destination
- Departure date(s)
- Return date(s)
- Cabin class
- Number of stops
Date Flexibility
The system should support:
- Exact date searches
- Flexible date windows (e.g., ±3 days around a specified date)
- A calendar view displaying "cheapest per day" options
Core Outputs
The primary outputs should include:
- A list of flight itineraries or offers, sorted by price, with various filtering options.
- A fast "cheapest per day" calendar view.
System Concerns to Address
The design discussion should explicitly cover the following architectural aspects:
- High-level Architecture: Detail the overall system structure, including components for data ingestion from providers, data normalization, deduplication logic, and the design of the search index.
- APIs: Define the necessary API endpoints, specifically for search, quoting/validation (re-pricing), and any ancillary services.
- Caching Strategy: Outline a comprehensive caching approach to optimize performance and reduce load.
- Data Freshness and Update Propagation: Describe mechanisms to ensure data freshness and efficiently propagate updates throughout the system.
- Rate Limiting, Retries, and Resilience Patterns: Explain how the system handles external provider rate limits, implements retry logic, and incorporates other resilience patterns.
- Consistency vs. Availability Trade-offs: Discuss the architectural decisions made regarding consistency and availability, and their implications.
- Scalability and Cost-Control Strategies: Detail strategies for scaling the system to meet demand and controlling operational costs.
- Schemas and Indexes: Propose database schemas and indexing strategies optimized for fast queries and rapid price updates.