Frontend API Gateway: GraphQL Federation and Schema Stitching

In the world of modern web application development, managing data from multiple sources can be a significant challenge. As applications grow in complexity and embrace microservices architectures, the need for a unified and efficient way to access data becomes paramount. A Frontend API Gateway acts as a central point of entry for client applications, aggregating data from various backend services and providing a streamlined experience for developers and end-users alike. This blog post explores two powerful techniques for building a Frontend API Gateway: GraphQL Federation and Schema Stitching.

What is a Frontend API Gateway?

A Frontend API Gateway is an architectural pattern where a dedicated server acts as an intermediary between frontend clients (e.g., web browsers, mobile apps) and multiple backend services. It simplifies data fetching by:

• Aggregating data: Combining data from multiple sources into a single response.
• Transforming data: Adapting data formats to suit the needs of the frontend.
• Abstracting complexity: Hiding the intricacies of backend services from the client.
• Enforcing security: Implementing authentication and authorization policies.
• Optimizing performance: Caching frequently accessed data and reducing network requests.

Essentially, it implements the Backend for Frontend (BFF) pattern at scale and empowers front-end teams to take more control of the APIs they consume. In larger organisations, having the front-end manage and curate its own APIs can lead to faster delivery and reduced dependency on backend teams.

Why Use GraphQL for a Frontend API Gateway?

GraphQL is a query language for APIs and a runtime for fulfilling those queries with your existing data. It offers several advantages over traditional REST APIs, making it well-suited for building Frontend API Gateways:

• Efficient data fetching: Clients request only the data they need, reducing over-fetching and improving performance.
• Strong typing: GraphQL schemas define the structure of the data, enabling better tooling and validation.
• Introspection: Clients can discover the available data and operations through schema introspection.
• Real-time capabilities: GraphQL subscriptions enable real-time data updates.

By leveraging GraphQL, a Frontend API Gateway can provide a flexible, efficient, and developer-friendly interface for accessing data from multiple backend services. This contrasts sharply with traditional approaches using multiple REST endpoints, each needing to be queried individually and often returning more data than required.

GraphQL Federation: A Distributed Approach

What is GraphQL Federation?

GraphQL Federation is a powerful technique for building a distributed GraphQL API by composing multiple GraphQL services (called "subgraphs") into a single, unified schema. Each subgraph is responsible for a specific domain or data source, and the Federation gateway orchestrates queries across these subgraphs.

The core concept revolves around a supergraph, a single, unified GraphQL schema that represents the entire API. This supergraph is built by composing smaller GraphQL schemas, called subgraphs, each representing a specific microservice or data source. The Federation gateway is responsible for routing incoming GraphQL queries to the appropriate subgraphs and combining the results into a single response.

How GraphQL Federation Works

1. Subgraph Definition: Each microservice exposes a GraphQL API (a subgraph) that defines its own data and operations. These schemas include directives that tell the Federation gateway how to resolve types and fields. Key directives include `@key`, `@external`, and `@requires`.
2. Supergraph Composition: The Federation gateway (e.g., Apollo Gateway) retrieves the schemas from each subgraph and composes them into a single, unified schema (the supergraph). This process involves resolving type and field conflicts and establishing relationships between types across different subgraphs.
3. Query Planning and Execution: When a client sends a GraphQL query to the gateway, the gateway analyzes the query and determines which subgraphs need to be queried to fulfill the request. It then distributes the query to the appropriate subgraphs, collects the results, and combines them into a single response, which is returned to the client.

Example: E-commerce Platform with GraphQL Federation

Consider an e-commerce platform with separate microservices for products, customers, and orders.

• Products Subgraph: Manages product information (name, description, price, etc.).
• Customers Subgraph: Manages customer data (name, address, email, etc.).
• Orders Subgraph: Manages order information (order ID, customer ID, product IDs, total amount, etc.).

Each subgraph exposes a GraphQL API, and the Federation gateway composes these APIs into a single supergraph. A client can then query the supergraph to retrieve information about products, customers, and orders in a single request.

For example, a query to retrieve a customer's name and their order history could look like this:

query GetCustomerAndOrders($customerId: ID!) {
  customer(id: $customerId) {
    id
    name
    orders {
      id
      orderDate
      totalAmount
    }
  }
}

The Federation gateway would route this query to the Customers and Orders subgraphs, retrieve the necessary data, and combine it into a single response.

Benefits of GraphQL Federation

• Simplified data access: Clients interact with a single GraphQL endpoint, regardless of the underlying data sources.
• Improved performance: Data fetching is optimized by retrieving only the necessary data from each subgraph.
• Increased scalability: Each subgraph can be scaled independently, allowing for better resource utilization.
• Decentralized development: Teams can develop and deploy subgraphs independently, promoting agility and innovation.
• Schema governance: The Federation gateway enforces schema consistency and compatibility across subgraphs.

Tools for GraphQL Federation

• Apollo Federation: A popular open-source implementation of GraphQL Federation, providing a gateway, a schema registry, and tooling for building and managing federated GraphQL APIs. Apollo Federation is known for its scalability and robust error handling.
• GraphQL Hive: This tool offers schema registry and governance for GraphQL federated services, providing features like change detection, usage analysis, and schema checks. It enhances visibility and control over the supergraph.

Schema Stitching: An Alternative Approach

What is Schema Stitching?

Schema Stitching is another technique for combining multiple GraphQL schemas into a single, unified schema. Unlike Federation, Schema Stitching typically involves a more manual process of defining how types and fields from different schemas are connected. While Federation is considered a more modern and robust solution, Schema Stitching can be a viable option for simpler use cases or when migrating from existing GraphQL APIs.

How Schema Stitching Works

1. Schema Definition: Each microservice exposes a GraphQL API with its own schema.
2. Stitching Logic: A stitching layer (often implemented using libraries like GraphQL Tools) defines how types and fields from different schemas are connected. This involves writing resolver functions that fetch data from the underlying services and map it to the unified schema.
3. Unified Schema: The stitching layer combines the individual schemas into a single, unified schema that is exposed to the client.

Example: Stitching Products and Reviews

Imagine two separate GraphQL services: one for products and another for reviews.

• Products Service: Provides information about products (ID, name, description, price).
• Reviews Service: Provides reviews for products (ID, product ID, rating, comment).

Using Schema Stitching, you can create a unified schema that allows clients to retrieve product information and reviews in a single query.

You would define a resolver function in the stitching layer that fetches reviews for a given product ID from the Reviews Service and adds them to the Product type in the unified schema.

// Example (Conceptual): Stitching logic using GraphQL Tools
const { stitchSchemas } = require('@graphql-tools/stitch');

const productsSchema = ... // Define your products schema
const reviewsSchema = ... // Define your reviews schema

const stitchedSchema = stitchSchemas({
  subschemas: [
    {
      schema: productsSchema,
    },
    {
      schema: reviewsSchema,
      transforms: [
        {
          transformSchema: (schema) => schema,
          transformRequest: (originalRequest) => {
            return originalRequest;
          },
          transformResult: (originalResult) => {
            return originalResult;
          }
        }
      ],
    },
  ],
  typeDefs: `
    extend type Product {
      reviews: [Review]
    }
  `,
  resolvers: {
    Product: {
      reviews: {
        resolve: (product, args, context, info) => {
          // Fetch reviews for the product from the Reviews Service
          return fetchReviewsForProduct(product.id);
        },
      },
    },
  },
});

This example demonstrates the core concept of stitching schemas together. Note the need for custom resolvers to fetch the `reviews` field. This additional overhead of coding resolvers for each relationship can make the development process slower than using Federation.

Benefits of Schema Stitching

• Unified API: Clients access a single GraphQL endpoint, simplifying data access.
• Incremental adoption: Schema Stitching can be implemented incrementally, allowing you to gradually migrate to a unified API.
• Flexibility: Schema Stitching provides more control over how schemas are combined, allowing you to customize the stitching logic to meet specific needs.

Drawbacks of Schema Stitching

• Manual configuration: Schema Stitching requires manual configuration of the stitching logic, which can be complex and time-consuming.
• Performance overhead: Resolver functions can introduce performance overhead, especially if they involve complex data transformations.
• Limited scalability: Schema Stitching can be more difficult to scale than Federation, as the stitching logic is typically centralized.
• Schema ownership: Can lead to ambiguity around schema ownership, particularly if different teams manage the stitched services.

Tools for Schema Stitching

• GraphQL Tools: A popular library for building and manipulating GraphQL schemas, including support for Schema Stitching.
• GraphQL Mesh: GraphQL Mesh allows you to use GraphQL query language to access data from various sources like REST APIs, databases and gRPC. It can stitch these APIs into unified GraphQL schema.

GraphQL Federation vs. Schema Stitching: A Comparison

Both GraphQL Federation and Schema Stitching offer ways to combine multiple GraphQL schemas into a single API, but they differ in their approach and capabilities.

Feature	GraphQL Federation	Schema Stitching
Approach	Distributed, automated composition	Centralized, manual configuration
Complexity	Lower complexity for maintaining and scaling	Higher complexity due to manual resolver logic
Scalability	Designed for large-scale, distributed systems	Less scalable, typically used for smaller applications
Schema governance	Built-in schema governance and validation	Requires manual schema management and coordination
Tooling	Strong ecosystem of tools and libraries (e.g., Apollo Federation)	Requires more custom tooling and configuration
Use Cases	Microservices architectures, large-scale APIs, decentralized development	Smaller applications, incremental migration, specific customization requirements

When to Use GraphQL Federation: Choose Federation when you have a complex microservices architecture, need to scale your API, and want to empower independent teams to manage their own subgraphs. It also simplifies schema management and governance.

When to Use Schema Stitching: Consider Schema Stitching when you have a simpler API, need more control over the stitching logic, or are migrating from existing GraphQL APIs. However, be aware of the potential complexities and scalability limitations.

Implementing Authentication and Authorization

Regardless of whether you choose GraphQL Federation or Schema Stitching, implementing authentication and authorization is crucial for securing your Frontend API Gateway. There are several approaches you can take:

• Gateway-level Authentication: The API Gateway handles authentication and authorization before routing requests to the backend services. This approach centralizes security logic and simplifies the backend services. Common methods include JWT (JSON Web Token) validation and OAuth 2.0.
• Service-level Authentication: Each backend service handles its own authentication and authorization. This approach provides more granular control over security but can be more complex to manage.
• Hybrid Approach: A combination of gateway-level and service-level authentication. The gateway handles initial authentication, and the backend services perform more granular authorization checks.

Example: JWT Authentication with Apollo Federation

With Apollo Federation, you can configure the gateway to validate JWT tokens included in the request headers. The gateway can then pass the user information extracted from the token to the subgraphs, which can use this information for authorization.

// Example (Conceptual): Apollo Gateway configuration with JWT validation
const { ApolloGateway } = require('@apollo/gateway');

const gateway = new ApolloGateway({
  serviceList: [
    // ... your subgraph configurations
  ],
  buildService: ({ name, url }) => {
    return new MyCustomService({
      name,  // Name of the subgraph
      url,   // URL of the subgraph
    });
  },
});

class MyCustomService extends RemoteGraphQLDataSource {
  willSendRequest({ request, context }) {
    // Get the user from the context
    const user = context.user;

    // Add the user's ID to the request headers
    if (user) {
      request.http.headers.set('user-id', user.id);
    }
  }
}

In this example, a custom service is created to modify the outgoing requests to include the user ID derived from the JWT. The downstream services can then use this ID for authorization checks.

Caching Strategies for Performance Optimization

Caching is essential for improving the performance of a Frontend API Gateway. By caching frequently accessed data, you can reduce the load on backend services and improve response times for clients. Here are some caching strategies:

• HTTP Caching: Leverage HTTP caching mechanisms (e.g., `Cache-Control` headers) to cache responses in the browser and intermediate proxies.
• In-Memory Caching: Use in-memory caches (e.g., Redis, Memcached) to cache frequently accessed data on the gateway.
• CDN Caching: Utilize Content Delivery Networks (CDNs) to cache static assets and API responses closer to the client.
• GraphQL Query Caching: Cache the results of GraphQL queries based on their query string and variables. This can be particularly effective for frequently executed queries. Apollo Server offers built-in support for query caching.

When implementing caching, consider cache invalidation strategies to ensure that clients receive up-to-date data. Common strategies include:

• Time-based Expiration: Set a fixed expiration time for cached data.
• Event-based Invalidation: Invalidate the cache when data changes in the backend services. This can be achieved using webhooks or message queues.

Monitoring and Observability

Monitoring and observability are critical for ensuring the health and performance of your Frontend API Gateway. Implement comprehensive monitoring to track key metrics such as:

• Request latency: The time it takes to process a request.
• Error rates: The percentage of requests that result in errors.
• Throughput: The number of requests processed per unit of time.
• Resource utilization: CPU, memory, and network usage of the gateway and backend services.

Use tracing to track requests as they flow through the system, identifying bottlenecks and performance issues. Logging provides valuable insights into the behavior of the gateway and backend services.

Tools for monitoring and observability include:

• Prometheus: An open-source monitoring and alerting system.
• Grafana: A data visualization and monitoring tool.
• Jaeger: An open-source distributed tracing system.
• Datadog: A monitoring and security platform for cloud applications.
• New Relic: A digital intelligence platform for monitoring and improving software performance.

By implementing robust monitoring and observability, you can proactively identify and resolve issues, ensuring the reliability and performance of your Frontend API Gateway.

Conclusion

A Frontend API Gateway built with GraphQL Federation or Schema Stitching can significantly simplify data access, improve performance, and enhance the developer experience in modern web applications. GraphQL Federation provides a powerful and scalable solution for composing distributed GraphQL APIs, while Schema Stitching offers a more flexible approach for combining existing schemas. By carefully considering the specific requirements of your application and the tradeoffs between these techniques, you can choose the best approach for building a robust and efficient Frontend API Gateway.

Remember to implement proper authentication and authorization, caching strategies, and monitoring and observability to ensure the security, performance, and reliability of your gateway. By embracing these best practices, you can unlock the full potential of GraphQL and build modern web applications that deliver exceptional user experiences.