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Design a food delivery system
Design a food delivery platform, similar to common restaurant delivery applications. The platform should support core user stories for customers, restaurants, and delivery partners.
Core User Stories
- Customers: Browse restaurants and menus, place orders, make payments, and track deliveries.
- Restaurants: Receive orders, confirm and prepare them, and update order statuses.
- Delivery Partners (Couriers): Receive delivery assignments, navigate to pickup and dropoff locations, and update delivery statuses.
Functional Requirements
- Restaurant Discovery: Basic search and filtering by location and cuisine.
- Menu Retrieval: Ability to fetch restaurant menus.
- Order Placement and Payment: Functionality for customers to place orders and complete payments.
- Order Lifecycle Management: Support for the following order states:
CREATED,CONFIRMED,PREPARING,READY_FOR_PICKUP,PICKED_UP,DELIVERED. Include paths for cancellations and refunds. - Real-time Tracking: Near real-time order status updates for customers.
Non-Functional Requirements
- High Availability: Ensure the platform is highly available, especially for order placement.
- Idempotency: Order creation and payment operations must be idempotent.
- Low Latency: Dispatch of orders to couriers should have low latency.
- Scalability: Support for peak traffic loads, such as lunch and dinner rushes.
Potential Follow-up Questions
- How would you design the dispatch and matching system between orders and available couriers?
- How would you model and deliver real-time order status updates to users?
- How would you scale the search functionality and read-heavy traffic for restaurants and menus?
- Optimization: Consider a scenario where couriers have limited capacity and time. How would you design a system to select a subset of candidate orders to batch and assign to couriers to maximize value under these constraints? (This may resemble a knapsack-style optimization problem.)
AI interview prep
Core dilemma
Balancing real-time delivery logistics and state management with scalable, highly available order processing and discovery services.
Mid-level signals3
Senior signals4
Red flags4
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 a food delivery system
Design a food delivery platform, similar to common restaurant delivery applications. The platform should support core user stories for customers, restaurants, and delivery partners.
Core User Stories
- Customers: Browse restaurants and menus, place orders, make payments, and track deliveries.
- Restaurants: Receive orders, confirm and prepare them, and update order statuses.
- Delivery Partners (Couriers): Receive delivery assignments, navigate to pickup and dropoff locations, and update delivery statuses.
Functional Requirements
- Restaurant Discovery: Basic search and filtering by location and cuisine.
- Menu Retrieval: Ability to fetch restaurant menus.
- Order Placement and Payment: Functionality for customers to place orders and complete payments.
- Order Lifecycle Management: Support for the following order states:
CREATED,CONFIRMED,PREPARING,READY_FOR_PICKUP,PICKED_UP,DELIVERED. Include paths for cancellations and refunds. - Real-time Tracking: Near real-time order status updates for customers.
Non-Functional Requirements
- High Availability: Ensure the platform is highly available, especially for order placement.
- Idempotency: Order creation and payment operations must be idempotent.
- Low Latency: Dispatch of orders to couriers should have low latency.
- Scalability: Support for peak traffic loads, such as lunch and dinner rushes.
Potential Follow-up Questions
- How would you design the dispatch and matching system between orders and available couriers?
- How would you model and deliver real-time order status updates to users?
- How would you scale the search functionality and read-heavy traffic for restaurants and menus?
- Optimization: Consider a scenario where couriers have limited capacity and time. How would you design a system to select a subset of candidate orders to batch and assign to couriers to maximize value under these constraints? (This may resemble a knapsack-style optimization problem.)