I’ve been thinking a lot lately about how modern applications demand more from our APIs—speed, flexibility, and reliability. That’s why I wanted to explore building a GraphQL API using NestJS, Prisma, and Redis caching. This combination offers a powerful way to create production-ready systems that can handle real-world demands.

Getting started with NestJS and GraphQL is straightforward. The framework’s modular approach means you can structure your application cleanly from day one. Here’s how I set up the GraphQL module:

GraphQLModule.forRoot<ApolloDriverConfig>({
  driver: ApolloDriver,
  autoSchemaFile: join(process.cwd(), 'src/schema.gql'),
  playground: process.env.NODE_ENV !== 'production',
  context: ({ req, res }) => ({ req, res }),
})

Have you ever considered how much time proper database modeling can save you down the road? Prisma makes this process intuitive with its schema definition. I defined my models carefully, thinking about relationships and scalability from the beginning:

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

When it comes to performance, caching is non-negotiable. Redis integration with NestJS is surprisingly smooth. I implemented a caching layer that significantly reduced database load:

@Injectable()
export class PostsService {
  constructor(
    private prisma: PrismaService,
    @Inject(CACHE_MANAGER) private cacheManager: Cache
  ) {}

  async findOne(id: string) {
    const cached = await this.cacheManager.get(`post:${id}`);
    if (cached) return cached;

    const post = await this.prisma.post.findUnique({ where: { id } });
    await this.cacheManager.set(`post:${id}`, post, 300);
    return post;
  }
}

What if your application needs real-time capabilities? GraphQL subscriptions make this possible without complicating your architecture. The setup is clean and integrates well with the existing GraphQL context:

@Subscription(() => Post, {
  filter: (payload, variables) => 
    payload.postPublished.authorId === variables.userId,
})
postPublished(@Args('userId') userId: string) {
  return pubSub.asyncIterator('POST_PUBLISHED');
}

Error handling is another area where this stack shines. NestJS provides excellent tools for consistent error responses. I created custom filters that work across GraphQL operations:

@Catch()
export class GlobalExceptionFilter implements GqlExceptionFilter {
  catch(exception: unknown, host: ArgumentsHost) {
    const gqlHost = GqlArgumentsHost.create(host);
    // Handle different error types consistently
  }
}

Testing shouldn’t be an afterthought. I found that writing tests alongside development helped catch issues early. The dependency injection system in NestJS makes mocking dependencies straightforward:

describe('PostsService', () => {
  let service: PostsService;
  let prisma: PrismaService;

  beforeEach(async () => {
    const module: TestingModule = await Test.createTestingModule({
      providers: [
        PostsService,
        { provide: PrismaService, useValue: mockPrisma },
      ],
    }).compile();

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

Deployment considerations are crucial for production readiness. I configured environment-specific settings and implemented health checks:

@Controller('health')
export class HealthController {
  @Get()
  check() {
    return { status: 'OK', timestamp: new Date().toISOString() };
  }
}

Building with these technologies has shown me how much easier modern API development can be. The type safety from TypeScript and Prisma, combined with NestJS’s structure, creates a development experience that’s both productive and enjoyable.

What challenges have you faced when building GraphQL APIs? I’d love to hear your experiences—feel free to share your thoughts in the comments below, and if this resonates with you, please like and share this article with others who might find it useful.