I’ve been developing APIs for various projects over the years, and recently I found myself needing to build something that could handle real-world traffic while remaining maintainable and secure. That’s why I’m excited to share this practical guide on creating a production-ready REST API using NestJS, Prisma, and PostgreSQL. Whether you’re building a startup product or an enterprise system, these tools form a powerful combination that can scale with your needs.

Starting with the foundation, let’s set up our project. I prefer NestJS because it brings structure and scalability to Node.js development. The CLI makes initialization straightforward. Have you ever struggled with messy project structures in larger applications? NestJS’s modular approach naturally organizes your code.

nest new task-management-api
cd task-management-api
npm install @prisma/client prisma @nestjs/config

Configuration is crucial from day one. I always set up environment variables early using @nestjs/config. This prevents hardcoded values and makes deployment smoother. Here’s how I structure the main application file:

// main.ts
import { NestFactory } from '@nestjs/core';
import { ValidationPipe } from '@nestjs/common';
import { AppModule } from './app.module';

async function bootstrap() {
  const app = await NestFactory.create(AppModule);
  app.useGlobalPipes(new ValidationPipe({ whitelist: true }));
  await app.listen(3000);
}
bootstrap();

Moving to the database layer, Prisma has become my go-to ORM for TypeScript projects. Its type safety and intuitive schema language reduce errors significantly. What if your database schema could be version-controlled and easily shared across teams? Prisma makes this possible.

// schema.prisma
model User {
  id    String @id @default(cuid())
  email String @unique
  tasks Task[]
}

model Task {
  id     String @id @default(cuid())
  title  String
  userId String
  user   User   @relation(fields: [userId], references: [id])
}

After defining your schema, generate the client with npx prisma generate. This creates type-safe database queries. I often wonder why more developers don’t leverage type-safe database access—it catches so many runtime errors during development.

Authentication is where many APIs stumble. Implementing JWT properly requires attention to detail. I use Passport.js strategies within NestJS guards. How do you handle token expiration and refresh in your applications?

// jwt.strategy.ts
import { ExtractJwt, Strategy } from 'passport-jwt';
import { PassportStrategy } from '@nestjs/passport';

export class JwtStrategy extends PassportStrategy(Strategy) {
  constructor() {
    super({
      jwtFromRequest: ExtractJwt.fromAuthHeaderAsBearerToken(),
      secretOrKey: process.env.JWT_SECRET,
    });
  }

  async validate(payload: any) {
    return { userId: payload.sub, username: payload.username };
  }
}

Building the actual API endpoints involves creating controllers and services. I follow the single responsibility principle—controllers handle HTTP logic, while services contain business logic. Here’s a task creation endpoint:

// tasks.controller.ts
@Post()
create(@Body() createTaskDto: CreateTaskDto) {
  return this.tasksService.create(createTaskDto);
}

// tasks.service.ts
async create(createTaskDto: CreateTaskDto) {
  return this.prisma.task.create({ data: createTaskDto });
}

Validation is non-negotiable in production APIs. I use class-validator with DTOs. Did you know proper input validation can prevent most injection attacks?

// create-task.dto.ts
export class CreateTaskDto {
  @IsString()
  @MinLength(3)
  title: string;

  @IsOptional()
  @IsString()
  description?: string;
}

Error handling often separates amateur from production code. Global exception filters ensure consistent error responses. What’s your strategy for logging errors without exposing sensitive information?

// http-exception.filter.ts
@Catch(HttpException)
export class HttpExceptionFilter implements ExceptionFilter {
  catch(exception: HttpException, host: ArgumentsHost) {
    const ctx = host.switchToHttp();
    const response = ctx.getResponse<Response>();
    const status = exception.getStatus();

    response.status(status).json({
      statusCode: status,
      timestamp: new Date().toISOString(),
      message: exception.message,
    });
  }
}

Testing might seem tedious, but it’s your safety net. I write unit tests for services and integration tests for API endpoints. How do you balance test coverage with development speed?

// tasks.service.spec.ts
describe('TasksService', () => {
  let service: TasksService;

  beforeEach(async () => {
    const module = await Test.createTestingModule({
      providers: [TasksService, PrismaService],
    }).compile();

    service = module.get<TasksService>(TasksService);
  });

  it('should create a task', async () => {
    const task = await service.create({ title: 'Test Task' });
    expect(task.title).toBe('Test Task');
  });
});

Deployment involves containerization with Docker. I create a multi-stage Dockerfile to keep images small. Environment variables manage different configurations between development and production. Have you considered using health checks for your containers?

FROM node:18-alpine AS builder
WORKDIR /app
COPY package*.json ./
RUN npm ci
COPY . .
RUN npx prisma generate
RUN npm run build

FROM node:18-alpine
WORKDIR /app
COPY --from=builder /app/dist ./dist
COPY --from=builder /app/node_modules ./node_modules
COPY --from=builder /app/package.json ./
EXPOSE 3000
CMD ["node", "dist/main"]

Building this API has taught me that attention to detail in security, testing, and architecture pays off in the long run. The combination of NestJS, Prisma, and PostgreSQL provides a robust foundation that grows with your application. I’d love to hear about your experiences—what challenges have you faced when building production APIs? If this guide helped you, please share it with others who might benefit, and don’t hesitate to leave comments with questions or suggestions.