Diving into the BFF Tool Pool
Tools for implementing the BFF (Backend for Frontend) pattern, optimizing app performance and reducing maintenance.
BFF (Backend for Frontend) is a design pattern used to design multiple backend services tailored to the specific needs of each frontend client. This approach helps to reduce the complexities and scaling issues in using a monolithic backend to serve multiple frontends.
For example, the mobile and web versions of the same application can have different data formats, performance requirements, and authentication methods. But, it is challenging to deliver these specific needs to specific frontend clients with a traditional monolithic backend. With the BFF pattern, developers can overcome such situations by providing each frontend with its own customized backend to deliver specific needs.
So, in this article, I will discuss how the BFF pattern works, its advantages, and the different tools we can use to implement the BFF pattern.
Introduction to BFF Pattern
The Backend-for-Frontend (BFF) pattern is a design pattern that involves creating a separate backend service for each frontend client. It creates a data transformation layer between a client and the API to prevent over-fetching and under-fetching data and eliminate the Chatty I/O development anti-pattern.
Let’s look at the diagram below to better grasp the BFF pattern concept.
In the figure above, you can see two examples of BFFs implemented for web and mobile. The request and response cycle of the BFF pattern is explained below:
- The client sends a request to the BFF.
- The BFF sends a request to the internal microservices and collects the required data to fulfil the client request.
- The BFF aggregates the data gathered.
- The BFF returns the required data to the client for its use.
The client directly interacts with the BFF to ensure that only the necessary data is sent to populate the frontend — nothing more or less. Furthermore, the BFF pattern creates a separation of concerns between the different frontend and backend teams and allows each team to work independently and optimize their specific areas of the application.
Benefits of BFF
- The BFF pattern enables businesses to rapidly scale and introduce new clients with different requirements without changing their backend. The BFF can cater to the needs of each client by providing only the data required without over-fetching or under-fetching.
- BFFs are not shared across clients, which helps balance the load and prevent overloading at a single entry point for all clients.
- With the BFF pattern, frontend and backend teams no longer need to depend on each other. They can work independently and utilize the BFF to integrate the two components, leading to more efficient development processes.
- The BFF pattern helps reduce the risk of potential data breaches and other security vulnerabilities by providing greater control over data exposure.
Tools for Implementing BFF
1. Component Driven Development (CDD) platforms
Component-driven development has become one of the most popular development methodologies for frontend since it enforces reusability, reduces development time and ensures consistency throughout the application.
You can adopt that same concept when building a BFF pattern with the help of component-driven architectures. For example, tools like Bit are a popular choice for building BFFs. These tools help developers to avoid duplication between BFFs and achieve no coupling by using packages for shared code.
Bit is an open-source platform that simplifies the process of building reusable components and sharing them among different projects and development teams. You can implement the BFF architecture using Bit and create modular components for your application. Bit enables you to define and organize components within your application, specifying how a component should be built, tested, and deployed to interact with a backend service.
Bit supports various application types, including component-driven frontend frameworks like React and Angular, complex microservice architectures, serverless functions, and native mobile apps. Its flexibility makes it popular for developers looking to implement the BFF architecture in their projects. Furthermore, the component-level versioning of Bit makes it easy to match specific component versions to relevant application versions.
You can read more on using Bit for BFF implementations here:
2. API Gateways
An API Gateway is a powerful tool that supports the BFF architecture. It is a central point for managing client API calls to the backend microservices. When a client makes an API request, the API Gateway routes the request to the appropriate backend and sends the response back to the client, creating a seamless network traffic flow. This added layer of abstraction also provides improved data security.
As the application grows, having multiple custom-made API Gateways for different client types, as suggested by the BFF architecture, can alleviate potential problems. AWS API Gateway, Microsoft Azure API Management, and Google Cloud Endpoints are a few popular API Gateways developers can use to implement the BFF pattern and achieve improved scalability, flexibility, and security for their applications.
AWS API gateway
AWS API Gateway is a software-as-a-service tool that creates a centralized entry point for microservice-based applications, making it easier for multiple external clients to access the API. By using API Gateway, businesses can regulate API calls through throttling and improve response time with caching.
It also provides an added layer of security by abstracting the backend microservices from the clients. Moreover, separate API gateways can be set up for different client types, such as a web API Gateway and a mobile API Gateway for the same application, to handle the unique requirements of each better. Overall, AWS API Gateway is an excellent tool for implementing the BFF architecture and providing a seamless experience for clients accessing the backend microservices.
3. Serverless Platforms
With serverless platforms, developers can build and deploy BFF services as serverless functions. Using serverless platforms to implement BFF services includes several benefits:
- Automatically scales incoming traffic, ensuring the service is always available to clients.
- Cost-effective because cloud resources are allocated on demand, reducing the need for unnecessary infrastructure.
- The serverless nature of the infrastructure is fully managed, so developers do not need to worry about server management.
- Easy deployments.
- Easy integrations with other cloud services.
You can use AWS Lambda, Google Cloud Functions, or Microsoft Azure Functions to implement BFF services as serverless functions easily.
Google Cloud functions
Google Cloud Functions is a fully managed cloud service that allows developers to run event-driven code in response to cloud events or HTTP requests. Suppose you implement BFF services with Google Cloud Functions. In that case, you can create a function for each frontend client, and the functions will be responsible for catering the data from the backend API into the specific format required by the frontend client.
4. Service Mesh
A service mesh is a dedicated, configurable infrastructure layer for managing service-to-service communication between microservices. This approach is popular in distributed systems with hundreds or thousands of services since a service mesh can handle complex network communication and traffic management between services.
A Service Mesh is implemented using a series of network proxies that control communication between microservices. It provides essential functions such as traffic management, service discovery, load balancing, and high-level security.
Istio, Linkerd, and Amazon App Mesh are some of the most popular tools used to implement service meshes. They offer a range of features, including automatic load balancing, circuit breaking, rate limiting, and request routing.
Istio
Istio is a free and powerful tool for managing communication between microservices in a distributed system. It acts as a client to the microservices, allowing for uniform communication and providing infrastructure to manage their communication. Istio also offers a control plane for administrative purposes, allowing monitoring of the service mesh. This makes Istio a comprehensive solution for managing communication between microservices in the context of the BFF architecture.
Linkerd
Linkerd is a fast and easy-to-use service mesh for Kubernetes. It offers features like authorization policies, automatic proxy injection, a dashboard monitoring cluster metrics, service discovery and load balancing. Organizations can utilize these features to create a flexible and scalable BFF implementation that meets the requirements of multiple frontend clients.
5. Monitoring and logging tools
Monitoring and logging play a significant role when dealing with multiple microservices in a distributed environment. Monitoring helps detect failures and errors, while logging provides detailed information about the errors. Monitoring and logging are crucial in BFF architecture to improve system performance and quickly identify errors and failures.
Using a monitoring tool can reduce the time it takes to find the root cause of problems, and the application can be up and running again in no time. Monitoring tools also automate alerting, so the support team can respond to failures quickly. Different types of monitoring, such as network, application, web server, database, and cloud monitoring, can be applied based on your specific needs.
Some commonly used tools for monitoring and logging include Prometheus, Grafana, ELK Stack, and Datadog.
Prometheus
Prometheus is an open-source monitoring and alerting tool for cloud-native environments, including Kubernetes. It tracks time-series data, such as the number of API calls per second, and provides a way to visualize this data with graphs and dashboards. This helps to identify and respond to any issues in the system easily.
Datadog
Datadog is a cloud-based monitoring platform that offers a comprehensive solution for monitoring various aspects of your applications. It’s famous for its 400+ built-in integrations and ability to bring together three different types of monitoring under one roof: metrics, logs, and APM. Metrics involve collecting data, such as the number of API calls per second, and visualizing it in graphs and dashboards. Logs involve tracking log files and sending them to the Datadog agent. Finally, APM helps analyze traces across complex, distributed systems.
Conclusion
In conclusion, BFF is a crucial architectural pattern providing a seamless communication channel between frontend clients and backend services. The BFF pattern significantly enhances the user experience, accelerates software delivery, and optimizes performance by allowing different backend services to be developed for various frontend clients.
However, implementing the BFF pattern brings some practical challenges, like creating and managing multiple backend services, which will increase the complexity of the overall system. Hence, it is important to design the backend services as modular and flexible as possible.
You can use tools like Bit to implement the BFF pattern using independent components to avoid duplications and drastically reduce the system’s complexity. Furthermore, API Gateway services, service mesh, monitoring and logging tools offer advanced features and capabilities to support the BFF architecture. These tools ensure seamless communication between microservices, monitor and log system errors, and improve system performance.
Overall, the BFF pattern has proven to be a highly effective solution for building scalable, flexible, and efficient applications. Its adoption can significantly improve the performance of software systems.
Thank you for reading.
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