I’ve been building distributed systems for years, and one challenge that keeps resurfacing is how to provide a unified API while allowing teams to work independently. That’s what led me to GraphQL Federation with Apollo Server and TypeScript. When you have multiple services handling different domains—users, products, orders—you need a way to stitch them together without creating a tangled mess. This approach has transformed how I design APIs, and I want to share how you can implement it effectively.

GraphQL Federation lets you compose multiple GraphQL services into a single gateway. Each service, called a subgraph, owns part of your overall schema. The gateway handles query planning and execution across these subgraphs. Why is this better than a monolithic GraphQL server? It enables teams to deploy and scale their services independently while maintaining a cohesive API. Have you ever struggled with coordinating schema changes across a large team? Federation solves that by allowing each subgraph to define and extend types.

Setting up a federated architecture starts with a monorepo structure. I use a workspace configuration in package.json to manage multiple services. Here’s a basic setup:

{
  "name": "graphql-federation-tutorial",
  "private": true,
  "workspaces": ["packages/*"],
  "scripts": {
    "dev": "concurrently npm:dev:*",
    "dev:gateway": "npm run dev --workspace=gateway"
  }
}

Each subgraph is an independent Apollo Server instance. For example, a users service might define a User type with the @key directive, marking it as an entity that other services can reference. This is where federation directives come into play—they enable cross-service relationships without tight coupling.

const typeDefs = gql`
  extend schema @link(url: "https://specs.apollo.dev/federation/v2.0", import: ["@key"])
  type User @key(fields: "id") {
    id: ID!
    email: String!
    username: String!
  }
  type Query {
    user(id: ID!): User
  }
`;

But how do you handle data that spans multiple services? Federation uses entity resolution. When a query needs user data from the users service and order data from the orders service, the gateway intelligently plans and batches requests. It feels like magic, but it’s built on solid principles. Have you considered how query planning affects performance? The gateway minimizes over-fetching by only requesting necessary fields from each subgraph.

Implementing the gateway involves composing schemas from all subgraphs. I configure it to poll subgraphs for their schemas and handle composition automatically. Here’s a simplified version:

import { ApolloGateway } from '@apollo/gateway';
const gateway = new ApolloGateway({
  serviceList: [
    { name: 'users', url: 'http://localhost:4001' },
    { name: 'products', url: 'http://localhost:4002' }
  ]
});

Performance optimization is crucial. I enable query planning and caching strategies. For instance, using persisted queries reduces payload size, and distributed caching with Redis can speed up repeated requests. Monitoring is equally important—I integrate with Apollo Studio to track query performance and errors across services.

Error handling in a federated system requires graceful degradation. If one subgraph fails, the gateway should still return partial data if possible. I implement custom error handling and health checks to ensure reliability. What happens when a service goes down? Proper error handling ensures the system remains usable.

Deploying federated services involves service discovery and health checks. I use Docker Compose for local development and Kubernetes for production, ensuring each service can be scaled independently. Testing strategies include unit tests for resolvers and integration tests for the composed schema.

Throughout this process, I’ve learned that federation isn’t just about technology—it’s about enabling team autonomy. By defining clear boundaries between services, you reduce coordination overhead and accelerate development. The result is a scalable, maintainable API that grows with your organization.

I hope this guide helps you build high-performance federated systems. If you found these insights valuable, please like, share, and comment with your experiences or questions. Let’s continue the conversation and learn from each other’s journeys in distributed systems development.