Why Node.js
Node.js runs JavaScript on the server. Its non-blocking design handles many simultaneous connections efficiently, which makes it a strong fit for APIs, real-time features and products where the front end already uses JavaScript or TypeScript.
When Node.js is the right choice
| Use cases | |
|---|---|
| Great fit | REST and GraphQL APIs, real-time chat and notifications, SaaS back ends, BFF layers for React apps, serverless functions |
| Less ideal | Heavy CPU-bound number crunching or machine learning, where Python or Go are usually better |
What we build with Node.js
APIs & SaaS back ends
Typed, tested APIs for web and mobile apps.
Real-time apps
Chat, live dashboards, collaboration and tracking with WebSockets.
Microservices
Event-driven services with queues and clear contracts.
Serverless
AWS Lambda, Vercel and Cloudflare functions.
Our Node.js stack
Writing Node.js that stays maintainable
Node.js gives developers a lot of freedom, which can lead to codebases where every module follows a different pattern. We bring structure: TypeScript with strict settings, a clear separation between HTTP handling, business logic and data access, dependency injection where it simplifies testing, and validation of all incoming data with schemas that also generate API documentation.
Error handling is consistent across the application, with structured logs that include request IDs so issues can be traced from the user’s action to the database query. Configuration is read from the environment and validated on start-up. These conventions make it easy for new developers to find their way around and reduce the bugs that come from inconsistency.
Real-time features with Node.js
Node.js is particularly good at keeping many connections open at once, which makes it a natural fit for real-time features: live chat, notifications, collaborative editing, dashboards that update as data changes and tracking of deliveries or vehicles. We build these with WebSockets or server-sent events, use Redis to coordinate messages across multiple servers, and design graceful fallbacks so the app keeps working if a connection drops.
Node.js and serverless
Node.js is one of the most popular runtimes for serverless platforms such as AWS Lambda, Vercel Functions and Cloudflare Workers, thanks to fast start-up times and a small footprint. Serverless suits APIs with irregular traffic, webhooks, scheduled jobs and lightweight back ends, because you pay only for actual use and do not manage servers. For steady, high-volume traffic or long-running connections, containers are often cheaper and simpler. We help you choose — and many systems use both.
Node.js versions and release lines
Node.js publishes a new major version every six months. Even-numbered releases become long-term support (LTS) versions, receiving fixes for about 30 months; odd-numbered releases are short-lived. Production applications should run on an Active or Maintenance LTS release.
| Situation | What we recommend |
|---|---|
| New project | Current Active LTS release |
| Running an end-of-life version | Upgrade promptly — security fixes have stopped |
| Two or more LTS versions behind | Upgrade one LTS at a time, running tests at each step |
| Native add-ons or old build tools | Check compatibility first; replace unmaintained packages |
See the official Node.js release schedule for exact dates.
Choosing a Node.js framework
| Framework | Strengths | Best for |
|---|---|---|
| Express | Minimal, flexible, huge ecosystem | Small services and teams who want full control |
| Fastify | High performance, schema-based validation | Performance-sensitive APIs |
| NestJS | Structure, dependency injection, modules | Large applications and teams |
| Hono | Lightweight, runs on many runtimes including edge | Edge and serverless functions |
| Next.js route handlers | API and front end in one project | Full-stack React applications |
Data access and background work
- Prisma or Drizzle for type-safe database access with migrations
- PostgreSQL as our default database; MongoDB where documents genuinely fit better
- BullMQ with Redis for queues, retries and scheduled jobs
- Worker threads for CPU-heavy tasks so the event loop stays responsive
- Streams for large file imports and exports without loading everything into memory
Testing and security
- TypeScript in strict mode across the codebase
- Unit and integration tests with Vitest or Jest, plus Supertest for HTTP endpoints
- Input validation with Zod or JSON schemas at every boundary
- Dependency auditing with npm audit or Snyk, and lockfiles committed
- Helmet, rate limiting and secure cookie settings for web APIs
- Secrets loaded from environment variables or a secrets manager
Monitoring Node.js in production
Node.js problems in production usually show up as event-loop lag, memory leaks or slow downstream calls. We make these visible from day one with structured logging (pino), OpenTelemetry tracing, event-loop and heap metrics, and alerts on error rates and latency. Graceful shutdown and health checks let containers restart without dropping requests.
Looking for engineers rather than a project team? See hire Node.js developers, or explore TypeScript development.
Node.js architecture we favour
Node.js gives teams freedom, and freedom without structure produces codebases that are hard to change. We organise applications by feature module, keep business logic out of route handlers, and separate side effects — database calls, HTTP requests, queues — behind small interfaces that are easy to test and replace.
- Modular monolith first — one deployable service with clear internal boundaries
- Services only when justified — by team ownership, scaling or release cadence
- Typed contracts — shared TypeScript types or OpenAPI schemas between front end and back end
- Idempotent jobs so retries never double-charge or double-send
- Configuration validated at startup so missing variables fail fast instead of in production
Typical Node.js project scope
| Project | Typical timeline | What drives effort |
|---|---|---|
| REST or GraphQL API for a web/mobile app | 6–12 weeks | Endpoints, auth, integrations |
| Real-time features (chat, live updates) | 3–8 weeks | Scale, presence and message history |
| Integration or webhook service | 2–6 weeks | Number of systems and error handling |
| Upgrade of an older Node.js app | 1–4 weeks | Version gap, dependencies, tests |
Typical ranges for planning; we confirm in a written estimate.
Node.js or another back end?
Node.js is an excellent fit for I/O-heavy APIs, real-time features and teams already using TypeScript on the front end. For CPU-heavy number crunching or machine-learning workloads, Python or Go is often a better tool, and many systems combine them — a Node.js API in front of a Python service for data science, for example. We recommend based on your workload and team, not habit.
Compare options in our backend technologies overview.
Questions we ask before a Node.js project
- Which clients will call the API — web, mobile, partners or internal systems?
- Do any features need real-time updates, and for how many concurrent users?
- Are there CPU-heavy tasks that should run outside the main service?
- Which databases, queues and third-party APIs are involved?
- Will the service run in containers, on serverless functions or at the edge?
- Who will be on call, and what monitoring do they already use?
The answers decide the framework, the hosting model and how we structure the code from the first sprint.
How we work
- Discovery and architecture — a short design phase that agrees structure, data model and hosting.
- Two-week sprints — working software on a staging environment, with code reviews on every change.
- Automated tests and CI/CD — tests and quality checks run before anything reaches production.
- Documentation and handover — setup guides, architecture notes and API documentation.
Need Node.js engineers in your team? See hire Node.js developers. For complete products, see custom software development.
This page is part of Backend Development Services — see the full overview for related services, approach and pricing.