Your API breaks at 500 users. Ours handles 50,000. Here is why.
We build Node.js backends in TypeScript using NestJS and Fastify. REST APIs, GraphQL, real-time WebSockets, and microservices — all delivered with 85% test coverage and an architecture your team can own on day one.
Loop
A traffic spike becomes an outage when your server runs out of threads. Node.js never runs out of threads.
The gap is not theoretical. Watch what happens to each model when 10,000 connections hit at once.
Nine things most Node.js agencies get wrong. We do them right. See the difference.
Every row below is a decision that shapes the cost and quality of your codebase for years. These are not preferences. They are engineering standards.
Four Node.js specializations. Each built for a different scaling challenge your team will face.
Chat apps, trading platforms, collaborative tools, and live dashboards need persistent connections. Missed events or slow updates cost users and revenue. We build WebSocket servers using Socket.io on NestJS Gateways, with room-based routing, JWT authentication, and Redis pub/sub so the system keeps working when you scale to multiple servers.
GET /api/v1/orders/1004Every API ships with an OpenAPI 3.1 spec generated directly from the code. The documentation is never out of date because it is compiled, not written by hand. We add rate limiting, Zod request validation, structured error responses, and OpenTelemetry tracing on every endpoint. Fastify handles endpoints where raw throughput is the priority.
A tightly coupled monolith makes it dangerous to deploy new features and impossible to scale one part of the system independently. We split domains into Node.js microservices that communicate through message queues — RabbitMQ, Kafka, or AWS SQS. Each service has its own database, its own pipeline, and its own test suite. You deploy one service without touching the rest.
When the project is full-stack, a shared TypeScript monorepo means your API types and your frontend types can never go out of sync. One commit validates and deploys both. One PR review covers the full change. We use Nx or Turborepo to manage the monorepo, with a shared Prisma schema and a shared design system library.
We rebuilt a failing B2B SaaS monolith into Node.js microservices on AWS EKS. Releases went from two weeks to two days.
A B2B SaaS platform could not release new features without risking an outage. The monolith's tightly coupled services meant every deployment touched the entire system. Releases took two weeks. One bad deploy took the product down for hours.
- Broke the monolith into independent Node.js microservices — each team deploys their own service on its own schedule
- Moved to Kubernetes on AWS EKS for auto-scaling — the system now handles 5x the load without adding servers
- Built GitHub Actions CI/CD pipelines — manual deployments are gone, and rollbacks take 90 seconds
The Node.js stack we use in production. Click any tool to see exactly how we use it and why.
NestJS is our primary framework for every production Node.js application. It enforces a modular architecture through dependency injection — which means every service is testable in isolation, every feature lives in its own module, and new engineers can find their way around the codebase without a guide. We stopped building production apps in plain Express. Structure is not optional at scale.
We catch bugs before they reach production. TypeScript in strict mode eliminates entire categories of runtime errors at compile time. Every external API, every shared type, every database query is typed end to end across the monorepo. We have not shipped plain JavaScript to production since 2021.
Fastify is 2x faster than Express on the same hardware. When an API endpoint serves thousands of requests per second, that speed difference is real money saved on infrastructure. We use Fastify as a NestJS adapter or standalone for any microservice where throughput is the primary constraint. JSON schema validation is built in — no separate middleware needed.
Our default ORM for every relational database. Prisma generates TypeScript types directly from your database schema — every query is type-safe, every column name is checked at compile time. Prisma Migrate tracks schema changes in version control, so your database schema and your code are always in sync. Query logging catches N+1 problems in development before they reach production.
When a job fails silently, you find out from a user complaint. BullMQ gives every background job retry logic, priority queues, exponential backoff, and real-time progress tracking on a dashboard. Email sends, payment processing, report generation, file uploads — all run asynchronously on Redis-backed queues that keep working even when a worker goes down.
We ship at 85% test coverage — measured across unit and integration layers, not just counted against lines of code. Unit tests run with Jest or Vitest. Integration tests use Testcontainers to spin up real databases in the CI pipeline, not mocks. End-to-end API tests use Supertest. You inherit a codebase that breaks loudly when something is wrong.
Redis does three things in our stack: caches API responses to cut database load, manages distributed sessions across multiple servers, and runs pub/sub for real-time WebSocket broadcasting. Redis Cluster handles production resilience with automatic failover. Rate limiting is also implemented at the Redis layer — fast and consistent across all nodes.
When a request fails in a microservices system, you need to trace it across every service it touched. OpenTelemetry SDK instruments every HTTP request, database query, and outbound API call automatically. Trace context travels through message queues, so you see the full chain. We export to Datadog, Grafana Tempo, or AWS X-Ray depending on your existing infrastructure.
Three things we do on every Node.js project that most agencies skip.
Cutting type safety to "move faster" creates technical debt that slows every future sprint. Every handler, every service, and every database query in a Redefine codebase is typed at compile time. The engineer who joins six months after launch can refactor it safely, not spend weeks figuring out what it does.
Node.js runs on one thread. One CPU-heavy task — a big report, a large image, a complex calculation — blocks every request behind it. We profile workloads during discovery to catch these before they are deployed. Heavy computation goes to a worker thread, a separate process, or a dedicated service. You sleep through the night.
Manual API documentation is always one refactor behind. It drifts the moment a developer changes a field name and does not update the docs. We generate the OpenAPI 3.1 spec automatically from code, using NestJS and Swagger decorators. The documentation is compiled, not maintained. Your frontend team always has the spec they need.
Questions technical leaders ask before starting a Node.js project with us.
We use NestJS as our primary framework for production Node.js applications because it enforces a modular, testable architecture out of the box. We use Fastify for high-throughput APIs where raw performance is the primary constraint. For projects requiring GraphQL, we use Apollo Server on top of NestJS. We do not build new projects with Express alone.
Yes, always. We have not shipped plain JavaScript to production since 2021. TypeScript in strict mode catches entire categories of bugs at compile time. It makes refactoring safe at scale. And it produces self-documenting code that new engineers can read without needing a briefing from the original author.
Node.js uses a single-threaded, non-blocking event loop. Traditional servers create one OS thread per connection and block during I/O. Node.js registers a callback for each I/O operation and keeps processing the queue. A single Node.js process handles tens of thousands of concurrent connections using a few megabytes of RAM total. See the comparison above for the live demo.
Node.js is the wrong choice for CPU-heavy workloads: video encoding, large-scale image processing, machine learning inference, or heavy numerical computation. Node.js is single-threaded, so a CPU-bound task blocks every other request behind it. For those workloads, Python, Go, or Rust are better fits. We tell you this before the engagement starts, not after you have paid a deposit.
Engagements typically run between $50,000 and $300,000 depending on API complexity, real-time requirements, third-party integrations, and whether the project includes a frontend. We scope the work before we quote. The discovery phase produces an architecture plan and a detailed estimate before any code is written. See our Node.js pricing guide for a phase-by-phase breakdown.
Describe your project. Get an architecture proposal in 3 days.
We respond within two business days. One call. No slide deck. An engineer reviews your brief and comes prepared with questions and early recommendations.
Submit brief → call within 48 hours → architecture proposal in 3 days → Sprint 1 starts week 2
