Design rental watchlist and notification system
System Design: Rental Listing Watchlist and Availability Notifications
Context
Design a feature for a vacation-rental marketplace where guests can "watch" a listing for a specific date range (check-in to check-out). If the listing becomes available for that exact range (per a defined matching policy), the system should notify the watcher. Hosts must also be able to view how many users are watching their listing.
Requirements
- APIs and Data Model: Define the necessary APIs and data models for Users, Listings, Reservations, Watchlist entries (including date ranges), and Notification preferences. Hosts need to view watch counts for their listings.
- Date-Range Representation and Matching Semantics: Address how date ranges are represented (e.g., inclusive/exclusive day bounds), consider time zones and Daylight Saving Time (DST), and define the matching policy (e.g., full overlap vs. partial overlap).
- Ingestion of Reservation Updates/Cancellations: Design a robust mechanism for ingesting reservation updates and cancellations. This should involve eventing, pub/sub patterns, and ensuring idempotency. Develop an efficient algorithm to find all affected watchers at scale, potentially leveraging per-listing calendars or interval indexes.
- Notification Pipeline: Implement a notification pipeline that handles deduplication, suppression, rate limiting, retries, and idempotency. It should also support multi-channel notification preferences.
- Storage, Sharding, and Caching: Propose appropriate strategies for data storage, sharding to handle scale, and caching to optimize performance.
- Consistency Model: Define the consistency model between reservation data and the watchlist system.
- Race Handling: Address potential race conditions between new bookings and the generation of availability notifications.
- Privacy, Abuse Controls, and Analytics: Implement controls for user privacy and prevention of abuse, especially concerning the host watch count feature. Provide analytics for host watch counts.
AI interview prep
Core dilemma
Balancing the real-time, high-volume processing of dynamic availability changes against the need for accurate, timely, and deduplicated notifications for potentially millions of watch requests, all while maintaining data consistency, system resilience, and managing operational costs at scale.
3 tradeoffs and 3 stress tests locked
Interview prep
Unlock the interviewer X-Ray rubric, tradeoff matrix, stress tests, clarifying questions, and key concepts.
Design rental watchlist and notification system
System Design: Rental Listing Watchlist and Availability Notifications
Context
Design a feature for a vacation-rental marketplace where guests can "watch" a listing for a specific date range (check-in to check-out). If the listing becomes available for that exact range (per a defined matching policy), the system should notify the watcher. Hosts must also be able to view how many users are watching their listing.
Requirements
- APIs and Data Model: Define the necessary APIs and data models for Users, Listings, Reservations, Watchlist entries (including date ranges), and Notification preferences. Hosts need to view watch counts for their listings.
- Date-Range Representation and Matching Semantics: Address how date ranges are represented (e.g., inclusive/exclusive day bounds), consider time zones and Daylight Saving Time (DST), and define the matching policy (e.g., full overlap vs. partial overlap).
- Ingestion of Reservation Updates/Cancellations: Design a robust mechanism for ingesting reservation updates and cancellations. This should involve eventing, pub/sub patterns, and ensuring idempotency. Develop an efficient algorithm to find all affected watchers at scale, potentially leveraging per-listing calendars or interval indexes.
- Notification Pipeline: Implement a notification pipeline that handles deduplication, suppression, rate limiting, retries, and idempotency. It should also support multi-channel notification preferences.
- Storage, Sharding, and Caching: Propose appropriate strategies for data storage, sharding to handle scale, and caching to optimize performance.
- Consistency Model: Define the consistency model between reservation data and the watchlist system.
- Race Handling: Address potential race conditions between new bookings and the generation of availability notifications.
- Privacy, Abuse Controls, and Analytics: Implement controls for user privacy and prevention of abuse, especially concerning the host watch count feature. Provide analytics for host watch counts.