GraphQL Federation solves the hardest problem in microservices: giving clients a unified API while teams own independent services. Apollo Federation composes subgraphs from separate teams—users, products, orders, inventory—into a single supergraph that clients query as if it were...
ZTABS builds federated microservices with GraphQL — delivering production-grade solutions backed by 500+ projects and 10+ years of experience. GraphQL Federation solves the hardest problem in microservices: giving clients a unified API while teams own independent services. Apollo Federation composes subgraphs from separate teams—users, products, orders, inventory—into a single supergraph that clients query as if it were one monolithic API. Get a free consultation →
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GraphQL is a proven choice for federated microservices. Our team has delivered hundreds of federated microservices projects with GraphQL, and the results speak for themselves.
GraphQL Federation solves the hardest problem in microservices: giving clients a unified API while teams own independent services. Apollo Federation composes subgraphs from separate teams—users, products, orders, inventory—into a single supergraph that clients query as if it were one monolithic API. Each team deploys its subgraph independently with its own release cycle, technology stack, and database. The federation router handles query planning, splitting a single client query across multiple subgraphs and stitching the results together transparently.
Frontend teams query one GraphQL endpoint that spans all microservices. A single query can fetch a user's profile from the users service, their recent orders from the orders service, and product details from the catalog service—all stitched together by the router.
Each team owns their subgraph, schema, and deployment pipeline. The products team can add fields, fix bugs, and deploy without coordinating with the users or orders teams, dramatically reducing cross-team dependencies.
Federation uses @key directives to define entity boundaries. The users subgraph defines User with an id key, and the orders subgraph extends User with an orders field. The type system enforces correct entity resolution across services.
Teams migrate from a monolith by extracting one subgraph at a time. The router composes existing and new subgraphs seamlessly, so the client API never breaks during migration. This makes federation adoption low-risk and iterative.
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Schedule a CallRun schema composition checks in your CI pipeline before deploying any subgraph. Apollo's rover CLI or Hive's schema checks detect breaking changes—removing a field, changing a type—before they reach production, preventing runtime errors in the supergraph.
GraphQL has become the go-to choice for federated microservices because it balances developer productivity with production performance. The ecosystem maturity means fewer custom solutions and faster time-to-market.
| Layer | Tool |
|---|---|
| Gateway | Apollo Router / GraphQL Mesh |
| Subgraphs | Apollo Server / GraphQL Yoga |
| Schema Registry | Apollo GraphOS / Hive |
| Tracing | OpenTelemetry + Jaeger |
| CI/CD | Schema checks in GitHub Actions |
| Monitoring | Datadog / Grafana |
A federated GraphQL architecture deploys the Apollo Router as the entry point that receives client queries and decomposes them into subgraph operations. Each microservice runs a subgraph server that defines its portion of the schema—the users subgraph owns the User type, the products subgraph owns Product and extends User with a wishlist field, and the orders subgraph extends User with an orders field and references Product for line items. The router builds a query plan that fetches entities in the optimal order, batching requests to minimize inter-service calls.
Schema composition happens at deploy time through a CI pipeline that runs schema checks to detect breaking changes before they reach production. GraphQL Hive or Apollo GraphOS serves as the schema registry, tracking every subgraph version and their composition. OpenTelemetry traces span the entire query lifecycle—from the router through each subgraph resolver—enabling teams to identify slow resolvers and optimize database queries.
Each subgraph connects to its own database (PostgreSQL, MongoDB, Redis) and exposes only a GraphQL interface, maintaining strict service boundaries while providing a unified experience to clients.
Our senior GraphQL engineers have delivered 500+ projects. Get a free consultation with a technical architect.