Backend For Frontend (BFF) for Mobile
Understand the Backend for Frontend (BFF) pattern and its role in creating high-performance, experience-driven mobile applications.
Modern mobile applications demand speed, efficiency, and responsiveness, but back-end APIs often stand in the way. A common architectural bottleneck arises from the use of one-size-fits-all APIs: general-purpose interfaces designed to serve various clients like web applications, mobile apps, and third-party systems. While this approach promotes reusability and uniformity, it introduces significant friction for mobile clients because it overfetches data, embeds client-specific logic, and becomes brittle to change. Mobile devices, due to
The disconnect between client-specific needs and back-end capabilities has become one of the most recurring friction points in mobile architecture. What begins as a question of optimization often turns into a deeper conversation about architectural boundaries, ownership, and scalability.
This lesson introduces the Backend for Frontend (BFF) pattern as a deliberate architectural response: a thin, purpose-built layer that customizes and orchestrates services for each client’s unique needs.
By the end, we should be able to:
Articulate the shortcomings of one-size-fits-all backends when serving diverse clients.
Understand the BFF pattern and its core responsibilities.
Identify the benefits of client-specific orchestration, including performance gains and maintainability.
Outline how a BFF layer fits within a broader microservices or API gateway ecosystem.
Understanding the problem
Let’s try to understand the problem of one-size-fits-all with a scenario.
ShopEase, a rapidly expanding e-commerce company, began its journey with a web-first application and a back-end architecture optimized accordingly. When the product team introduced mobile apps to reach a broader audience, they reused the same back-end services, assuming consistency would reduce duplication and accelerate development.
Initially, this approach appeared pragmatic. But overtime, the limitations became visible.
Mobile users, especially those on unreliable networks, experienced slow load times and high data usage. The architectural misalignment between the shared backend, and the mobile client at ShopEase reveals itself through a range of recurring, systemic issues.
Over-fetching and under-fetching: ShopEase’s product listing APIs return complete metadata used by the desktop site: images, language variants, offers, and user reviews, much of which is unnecessary for mobile. This leads to slower performance and increased data usage. Conversely, mobile-specific needs like quick previews lack dedicated support, forcing inefficient workarounds such as making other API calls.
Payload inefficiency: Beyond simply receiving too much data, mobile clients often suffer from poorly structured payloads, deeply nested fields, verbose naming, or redundant objects, making parsing and rendering expensive. Even small screens must process complex responses, leading to wasted CPU cycles, increased battery consumption, and sluggish UI performance.
Leaked client logic in shared layers: To make shared endpoints work across clients, ShopEase’s backend gradually absorbs conditional logic: flags for mobile vs. web, optional fields that vary by device, and branching behaviors that depend on ...