Lately, I’ve been thinking a lot about what separates a quick prototype from a robust, scalable API that can handle real-world traffic. The combination of GraphQL, TypeScript, and modern tooling isn’t just a trend; it’s a fundamental shift in how we build reliable backends. This guide is my attempt to share a battle-tested setup that goes beyond the basics.

Why does this matter now? GraphQL offers incredible flexibility for front-end developers, but that power comes with responsibility on the backend. Getting the foundation right from the start prevents countless headaches later. Let’s build something that’s not just functional, but production-ready.

The first step is setting up a project structure that can grow with your application. I prefer organizing code by feature rather than by technical layer. This makes it easier for teams to work on different parts of the system without constant merge conflicts.

// src/server.ts - A clean entry point
import { ApolloServer } from '@apollo/server';
import { expressMiddleware } from '@apollo/server/express4';
import { makeExecutableSchema } from '@graphql-tools/schema';
import express from 'express';

const app = express();

const typeDefs = `#graphql
  type Query {
    hello: String
  }
`;

const resolvers = {
  Query: {
    hello: () => 'World',
  },
};

const server = new ApolloServer({
  schema: makeExecutableSchema({ typeDefs, resolvers }),
});

await server.start();
app.use('/graphql', express.json(), expressMiddleware(server));

Did you ever wonder how to maintain type safety from your database all the way to your API responses? This is where Prisma shines. It acts as a single source of truth for your data model, generating a fully typed client that catches errors at compile time.

Here’s a practical database schema for an e-commerce application. Notice how relations and constraints are explicitly defined.

// prisma/schema.prisma
model User {
  id        String   @id @default(cuid())
  email     String   @unique
  createdAt DateTime @default(now())
  posts     Post[]
}

model Post {
  id       String @id @default(cuid())
  title    String
  content  String?
  author   User   @relation(fields: [authorId], references: [id])
  authorId String
}

After defining your schema, running npx prisma generate creates a client tailored to your database. The immediate benefit is autocompletion and error checking in your editor. No more guessing column names or data types.

But what about handling complex queries efficiently? This is a common concern with GraphQL. The N+1 problem can silently degrade performance. Imagine fetching a list of users and their posts; without proper batching, you might trigger a separate database query for each user’s posts.

The solution is straightforward with DataLoaders. They batch and cache requests within a single query execution.

// src/services/DataLoader.ts
import DataLoader from 'dataloader';
import { prisma } from '../lib/prisma';

const createUserLoader = () =>
  new DataLoader(async (userIds: string[]) => {
    const users = await prisma.user.findMany({
      where: { id: { in: userIds } },
    });
    const userMap = new Map(users.map(user => [user.id, user]));
    return userIds.map(id => userMap.get(id));
  });

Authentication is another critical piece. How do you securely manage user sessions in a GraphQL API? I prefer using JWT tokens passed in the Authorization header. The context function in Apollo Server is the perfect place to handle this.

// src/types/context.ts
export interface Context {
  user?: {
    id: string;
    email: string;
  };
}

// src/server.ts - context setup
const server = new ApolloServer({
  schema,
  context: async ({ req }): Promise<Context> => {
    const token = req.headers.authorization?.replace('Bearer ', '');
    if (token) {
      const user = await verifyToken(token); // Your verification logic
      return { user };
    }
    return {};
  },
});

For real-time features, GraphQL subscriptions are incredibly powerful. They allow clients to receive updates when data changes. Setting this up with Apollo Server and a PubSub system like Redis creates a solid foundation for live features.

// src/schema/subscription.ts
import { PubSub } from 'graphql-subscriptions';

const pubsub = new PubSub();

export const typeDefs = `#graphql
  type Subscription {
    postAdded: Post
  }
`;

export const resolvers = {
  Subscription: {
    postAdded: {
      subscribe: () => pubsub.asyncIterator(['POST_ADDED']),
    },
  },
};

Error handling is where many APIs show their maturity. Instead of generic messages, provide structured errors that help client developers understand what went wrong. Apollo Server includes built-in support for this.

// src/utils/errors.ts
export class ValidationError extends Error {
  constructor(message: string, public field: string) {
    super(message);
    this.name = 'ValidationError';
  }
}

// In your resolver
const resolvers = {
  Mutation: {
    createPost: (_, { input }, { user }) => {
      if (!user) throw new AuthenticationError('Authentication required');
      if (!input.title) throw new ValidationError('Title is required', 'title');
      // ... create logic
    },
  },
};

Deployment considerations are often an afterthought, but they shouldn’t be. Environment variables for database connections, proper logging, and health checks are essential. Here’s a simple way to add observability.

// src/utils/logger.ts
import pino from 'pino';

export const logger = pino({
  level: process.env.LOG_LEVEL || 'info',
  transport: {
    target: 'pino-pretty',
    options: {
      colorize: true,
    },
  },
});

Building a production-ready API is a journey of considering these details. Each piece—type safety, performance, security, and observability—contributes to an experience that feels seamless for both developers and end-users. The tools we have today make this more achievable than ever.

What challenges have you faced when moving from prototype to production? I’d love to hear your experiences. If this guide helped clarify the path forward, please consider sharing it with your team or leaving a comment below. Your feedback helps shape what we explore next.