In the past I’ve inherited, developed and maintained a microservice-based project and I would like to share some of the things I have learned with you.

The web frontend of this web application used ASP.NET MVC and ReactJS, the backend a mix of .NET Web APIs and Lambda APIs (we used AWS), about a dozen of them. It also used a few other 3rd party downstream services. There is also a mobile clients for both iOS and Android stores.

This project was developed by a small team, about from 2 to 4 fullstack developers working on it at a time. There were two client apps - a web application, which was actually a couple of web applications brought together by a proxy server front end. And a mobile application for both major platforms.

Anything but typical

In a typical client application, like in a mobile app or a typical SPA, one directly calls the microservice endpoints. However as the application evolves, more information and functionality gets squeezed into each page, and it is not unusual to have to do multiple calls to different microservices and compose the page from the data from all these.

Figure 1: Direct client to microservices

However, in this hybrid ASP.NET MVC/ReactJS app, the pattern used to compose the page is a bit different, so lets examine the situation.

Figure 2: Hybrid ASP.NET MVC/React App to microservice

In the course of initially loading a page the MVC App creates the Html skeleton including the bootstrap data that the page needs to achieve first paint as soon as possible. It also loads all the javascript, styling and images to make this possible. Now once the page is up in the client’s browser, React takes over and takes care its interactivity helped by the presence of a separate Web API in turn talking to all the services.

At first I was not quite clear why this separate Web API was required. Then after some research, I have stumbled upon the BFF Pattern as masterfully explained by Sam Newman in the post. Actually it was Phil Calcado who was one of the first (if not the first) who came up with this pattern.

The mobile application also followed a similar architecture - both the iOS and Android apps talked to the downstream services through a dedicated Web API in the middle.

Figure 3: Mobile App to microservice

BFF pattern is also known by many other names

  • Single Purpose API Gateway
  • Edge Layer
  • API Gateway Pattern
  • Single-purpose Edge Services
  • Proxy Server Gateway API

But they all point to the same BFF Pattern. Without having to repeat the articles in the previous section, let me say that BFF pattern is to simply have a backend API for each client, in which the development is owned by the client development team (shown in the blue shaded box in Figure 3).

Figure 3: API Gateway/BFF for each client application

Advantages of using the BFF Pattern

Using the BFF Pattern is more than just a data pass-through from data provider to the clients. These are the advantages for using this pattern:

  • it can serve as a gateway routing/proxy server: where the client talks to one API gateway, which routes the calls to multiple downstream services. This insulates the clients from changes when downstream services URL changes.

  • it can function as a request aggregator: reducing the chattiness of the client application. The client can send just one request to the API Gateway, which can send multiple requests to one or more downstream services. It can also gather all the responses and send them back to the client application. This can lead to performance improvements as running multiple requests from remote browser or mobile apps are more expensive than running them from each API Gateway.

  • it can contain code that handles cross-cutting concerns: such as authentication and authorization, logging, caching, retry policies, load balancing, etc. This can help in making the downstream services’ code much more simpler by not having to handle these concerns there.

  • it can promote consistent error handling: many service providers return errors a bit differently, so we can handle and translate error fault codes from different downstream services in a consistent manner so that the client application can be simpler.

  • enables development team’s autonomy and agility: BFFs enables and empowers development teams to be more in control of their projects. Instead of waiting for the “backend” team to deliver the updated API, and be at the mercy of their delay, control goes back to the client application team to be more on top of their delivery schedule.

  • enables better maintainability: because there is an inherent separation of concerns that this pattern promotes, this leads to better maintainability as parts of the system are insulated from certain changes.

Disadvantages of using the BFF Pattern

  • more moving parts: more moving parts means there is more things that we need to develop, build, deploy, and monitor. Put it simply there are more things that can go wrong.

  • moving the coupling around: whereas previously there was client application to downstream services coupling, the coupling has now moved to between the BFF and the downstream services. In the case of a mobile app client, or any client for that matter, maybe that is a compromise you are willing to take.

  • can introduce latency: in some instances, it may lead to more latency, however, a more chatty client most probably will have a longer response time.

  • more development by the client app team: because the BFF will typically be developed by the frontend team, this will mean more development and more time will be needed to develop the vertical solution

  • more possibility of code duplication: because following the BFF pattern, we tend to create an API for each user experience, the tendency is to duplicate code from one BFF to another, specially in the cases of similar or same functionality. However, in my opinion this is a compromise I am willing to take, in the interests of agility and autonomy.

Alternatives to the BFF Pattern

  • GraphQL: The BFF pattern started because of the generic service providers that cannot give what the client actually needs. This is the problem that GraphQL can solve. This enables a service provider to only return what a client needs. There is no concept of a generic API anymore, now we have an API that gives us exactly what we need. As awesome as this may sound, this may need more thought as it can mean either rewriting the downstream services to use GraphQL, or actually writing your BFF in GraphQL. You will have to assess this in your project as to what is possible.

  • Web Components or some other frontend UI composition technique/technology: maybe there are better technologies in the frontend space that although we still have to deal with multiple requests aggregation, would allow us to structure and manage our frontends similar to how we do our microservice backend. This compromise might help us manage our solution much better. More on micro frontend approach in a future post perhaps.

  • Don’t change: yes this is another option, but we will just have to be careful and manage the changes effectively. But, where’s the fun in that?


The arrival of microservices has contributed to software development challenges. Where previously apps talk to a general purpose API backend or service provider directly, this has proven to be problematic when changes need to be introduced both in the frontend, or at the backend.

I have listed down a few advantages in adopting this pattern. However among those, for me, I think promoting better maintainability and autonomy and agility are the most compelling reasons to use it.

We get better maintainability because we have narrowed the scope of the API, where you are not anymore trying to make everyone happy but just your own application client.

We get better autonomy and agility, because we have taken back control of the development of the backend service. And no longer are you at the mercy of the downstream service provider developers as both the frontend and the BFF are now developed by the same team.



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