A Comprehensive Guide to Structuring a Backend with BFFs: Using a Ride-Hailing Application as a Case Study

The Backend for Frontend (BFF) pattern is becoming increasingly popular in modern software architecture, especially for applications that serve multiple frontends, such as web, mobile, or even micro-frontends. In the case of a ride-hailing application where you must cater to different user groups — such as passengers and drivers — the BFF pattern can help streamline communication between frontends and backend services. By creating separate backends for each type of client (e.g., a BFF for passengers and a BFF for drivers), you can simplify the complexity for both backend and frontend teams, optimize performance, and deliver a more maintainable solution.

This comprehensive guide will walk you through how to structure a backend using BFFs, using a ride-hailing application as a case study. We will explore the benefits of BFFs, how to implement them, and the potential challenges you may encounter along the way.

What Is a Backend for Frontend (BFF)?

In modern software architecture, frontend applications often have specific data and performance needs that don’t always align with how backend microservices are structured. The BFF pattern addresses this challenge by creating a tailored backend layer specifically designed to meet the needs of different frontends.

Instead of having a single backend serve all frontend clients, the BFF pattern introduces a middle layer. This layer aggregates data from various backend services, transforms it if necessary, and delivers it to frontend applications in a format they can easily consume.

For a ride-hailing application, we have two distinct user groups:

• Passengers: Use the app to request rides, track drivers, and manage payments.
• Drivers: Use the app to accept ride requests, navigate to pickup/drop-off locations, and track earnings.

Both groups interact with the backend in different ways, which makes the BFF pattern ideal for simplifying backend communication.

Benefits of Using BFF in a Ride-Hailing Application

The BFF pattern offers several advantages, especially for a ride-hailing app, which has diverse frontend clients with specific needs.

1. Tailored Backend for Each User Group

The passenger and driver apps have different functionalities and data requirements. A single backend for both might result in complex, bloated APIs that try to serve too many different use cases. By using a BFF for each frontend, you can design APIs that are perfectly optimized for the passenger app and another for the driver app.

2. Improved Performance

Since the BFF serves as a middle layer between the frontend and backend services, it can aggregate data from multiple microservices in a single request. This reduces the number of API calls the frontend needs to make, improving performance, especially for mobile clients with limited bandwidth.

3. Simplified Frontend Development

With a BFF, frontend developers don’t need to understand the entire backend architecture. They only need to work with the BFF API, which simplifies development and testing.

4. Decoupling Frontend from Backend Complexity

By introducing a BFF, the frontend is decoupled from the complexity of backend microservices. Changes to backend services (e.g., splitting or merging microservices) won’t directly affect frontend development, as long as the BFF API remains stable.

Structuring the Backend for a Ride-Hailing Application

Now that we understand the value of the BFF pattern, let’s dive into how to structure the backend for a ride-hailing application that serves both passengers and drivers.

Step 1: Identify the Backend Services

For a ride-hailing app, you’ll likely have several microservices that handle different parts of the system, such as:

• Authentication Service: Handles login, registration, and user authentication.
• Ride Service: Manages ride requests, ride statuses, and ride history.
• Location Service: Tracks real-time locations of passengers and drivers.
• Payment Service: Handles transactions, refunds, and payment methods.
• Notification Service: Sends notifications for ride status updates or promotional offers.

These services operate independently, but the frontend needs to aggregate data from several services for each feature (e.g., the passenger app might need information from the ride, location, and notification services all at once).

Step 2: Create Separate BFFs for Passengers and Drivers

The next step is to create separate BFFs for the passenger and driver apps. Each BFF will act as the middle layer between the respective frontend and the backend services.

Passenger BFF: This backend will be optimized for passenger-specific actions, such as requesting rides, viewing nearby drivers, and tracking the status of an ongoing ride.

Driver BFF: This backend will handle driver-related actions, such as accepting ride requests, navigating to a passenger’s location, and viewing earnings.

By separating the BFFs, each can be tailored to meet the specific needs of the user group it serves, without unnecessary complexity.

Step 3: Design the APIs for Each BFF

For the BFF pattern to work effectively, you need to design APIs that are clean, simple, and focused on delivering what the frontend needs. Each BFF should offer endpoints that aggregate data from multiple services and transform it as needed.

Let’s look at some example API endpoints for the passenger and driver BFFs:

Passenger BFF APIs:

• POST /ride/request: Allows passengers to request a ride. This endpoint would gather data from the ride service, location service (for nearby drivers), and notification service (to send ride request updates).
• GET /ride/status: Returns the status of the passenger’s current ride, including the driver’s real-time location.
• POST /payment/charge: Processes payment for a completed ride. The BFF interacts with the payment service and ride service to finalize the transaction.

Driver BFF APIs:

• POST /ride/accept: Allows drivers to accept ride requests. This endpoint interacts with the ride and location services to update the ride’s status.
• GET /ride/details: Provides drivers with detailed information about an upcoming ride, such as the passenger’s location and destination.
• GET /earnings/summary: Returns a summary of the driver’s earnings, aggregating data from the payment service.

Step 4: Aggregate Data in the BFF Layer

One of the key responsibilities of the BFF is to aggregate data from multiple microservices into a single response that the frontend can easily consume. Instead of the frontend making separate calls to the ride service, location service, and payment service, the BFF can handle these interactions and return a single, cohesive response.

For example, the GET /ride/status API in the passenger BFF would need to fetch:

• The current status of the ride from the ride service (e.g., "driver on the way").
• The real-time location of the driver from the location service.
• Any updates or notifications related to the ride from the notification service.

The BFF would then aggregate this information into a single response that the frontend can display to the passenger.

Best Practices for Implementing BFFs

As you implement the BFF pattern, keep the following best practices in mind to ensure success:

1. Avoid Business Logic in the BFF

The BFF should focus on aggregating and transforming data, but avoid adding complex business logic. Business logic should remain in the backend services to keep the architecture clean and maintainable.

2. Handle Caching and Rate Limiting

Since the BFF will make multiple requests to backend services, it’s important to implement caching and rate limiting where appropriate. This ensures that the BFF doesn’t overwhelm backend services with frequent requests, especially for mobile apps that may have limited bandwidth.

3. Ensure Security

The BFF introduces an additional layer in your architecture, so it’s crucial to implement security measures, such as authentication, authorization, and input validation. The BFF should authenticate requests from the frontend before making calls to backend services.

4. Monitor and Log BFF Performance

Monitor the performance of your BFFs, including response times, error rates, and API usage. This will help you identify bottlenecks and ensure that the BFF is efficiently handling requests from the frontend.

Challenges of Using the BFF Pattern

While the BFF pattern offers many advantages, it’s not without challenges. Here are a few potential downsides to consider:

Increased Maintenance: You’ll need to maintain separate BFFs for each type of frontend, which can increase the complexity of your architecture. However, this is often outweighed by the benefits of clean, decoupled frontends.

Consistency Across BFFs: Ensuring that each BFF adheres to consistent API design principles and security protocols can be challenging, especially as your architecture grows.

Latency: The BFF introduces an extra layer between the frontend and backend, which could introduce latency if not optimized correctly. Caching and efficient aggregation strategies are essential to mitigate this.

Conclusion

The Backend for Frontend (BFF) pattern provides an excellent solution for structuring the backend of complex applications, such as a ride-hailing platform that serves both passengers and drivers. By implementing separate BFF layers for different frontends, companies can optimize performance, simplify frontend-backend communication, and enhance developer productivity.

For a ride-hailing app, this means passengers and drivers each have tailored backends, leading to faster, more efficient interactions with services like ride management, real-time location tracking, and payment processing. The BFF pattern also decouples frontend teams from the complexity of the underlying microservices, allowing them to focus on building intuitive user experiences.

While adopting the BFF pattern introduces additional architectural layers, the benefits of simplicity, maintainability, and flexibility far outweigh the downsides. By using well-structured BFFs, small IT companies can avoid overwhelming their teams with unnecessary complexity, focus on core deliverables, and deliver better products to their end users.

As we’ve shown in this guide, for businesses looking to provide multiple frontend experiences — whether for web, mobile, or multi-user platforms like ride-hailing apps — the BFF pattern is an invaluable strategy for achieving scalability and efficiency. By aligning backend responses with specific frontend needs, businesses can streamline development and provide faster, more reliable service to their users.

Ultimately, the BFF pattern provides a practical way to structure modern backend architectures in a world where both frontends and backends are becoming increasingly complex.