Node.js software architecture and design

One of the main selling points of node.js is it’s accessibility. Node.js opens up server side programming to front end developers, and while this is definitely a good thing it leads to a melting pot of ideas when it comes to software architecture. UI code running in the browser is fundamentally event driven and it’s requirements are very different to an API, so some of the hoops you jump through on the back end might seem a bit alien at first.

Dependency management

One of the most common issues I see in the wider node.js community is not using any form of Inversion of Control. It’s common to see dependencies imported directly into each function:

const express = require("express");
const requestHandler = require("./a-file");
const config = require("./config");

const app = new express();

This makes the code brittle and difficult to test. Using inversion of control it’s possible to structure the code so that dependencies are passed in and can be mocked out while testing:

function createService(app, requestHandler, port) {

  return () => app.listen(port);

Note that a function is used instead of a class here. It could be either, concepts like Inversion of Control do not imply object orientated programming. From this point on I use classes

Now this snippet is no longer responsible for obtaining it’s own dependencies something needs to set it up. My preference is to use a dependency container:

const express = require("express");
const requestHandler = require("./a-file");
const config = require("./config");

class Container {
  getService() {
    return new Service(express(), requestHandler, config.port);

class Service {
  constructor(app, requestHandler, port) { = app;
    this.requestHandler = requestHandler;
    this.port = port;

  start() {;;

const container = new Container();


Granted this is more code but it would be split out into three files: one for the service, one for the container and one for the boot code.

There are full on dependency injection libraries for node.js but I try to adhere to the principle of least power and try to stick to explicit wiring over annotation based injection. To each their own.

Async / await

Factoring in asynchronous code can be an issue for the boot script as there is no top level await. If our requestHandler needs to load some reference data from a database the asynchronous call will propagate all the way back to the bootstrapping code:

class Container {
  async getService() {
    const handler = await this.getRequestHandler();

    return new Service(express(), handler, config.port);

  async getRequestHandler() {
    const repo = this.getSomeRepository();
    const data = await repo.getSomeData();

    return new RequestHandler(data);

const container = new Container();

  .then(service => service.start())
  .catch(e => console.error(e));

Depending on the complexity of your set up this code may become slightly unwieldy. There are two approaches I’ve seen to bootstrapping asynchronous services:

(async () => {
  try {
    const container = new Container();
    const service = await container.getService();

  catch (err) {

// main function
async function main() {
  const container = new Container();
  const service = await container.getService();


main().catch(e => console.log(e));

Domain Driven Design influence

I’m a big fan of Domain Driven Design and loosely follow the layered architecture it suggests. I have a preference for DDD folder structures where code is grouped by domain rather than function:

├── src
│   ├── ...
│   ├── User
│   │   ├── Api <-- controllers, view models etc
│   │   ├── Domain <-- entities, services etc
│   │   ├── Infrastructure <-- repositories, external APIs
│   │   └── Tests
│   ├── Order
|   |   ├── ...

It’s a minor detail but it makes it easier to navigate the project and extract modules if the project gets too large.

The minimalist in me usually stops short of adding the next level of folder until I need it. I also still tend to have a separate test folder at the root level but that’s more habit than design choice.

Functional influence

While my software architecture is influenced by DDD I would say I’m equally or more influenced by functional programming. As a result my entity classes tend to be data structures rather than models that have functionality. TypeScript has support for readonly properties and while they don’t guarantee immutability they are useful:

class User {
    public readonly name: string,
    public readonly email: string,
    public readonly age: string
  ) {}

As the class properties are read only the class does not need getters or setters, it’s just a data structure. This is known as an Anemic Domain Model, which is highly discouraged by Martin Fowler. My justification is that adding lots of methods into an entity is not following the single responsibility principle. I prefer to keep all logic and rules in the other areas of the domain: Cases, Services, Events etc.

class UserRegistrationService {

    private readonly emailService: EmailService,
    private readonly registrationTemplate: Template
  ) {}

  register(user) {
    const content = this.registrationTemplate.render(user);


When I do use classes they tend to only have a single public method (single responsibility), this makes the practical difference between using pure functions and classes minimal. It’s not a hard rule, sometimes it’s convenient to have more than one public method, it’s just a pattern I’ve noticed in my code.

Anyone exposed to JavaScript is normally familiar with higher order functions through methods such as map, filter and reduce. I make extensive use of these methods in my code but mostly to manipulate low level data structures. I strive to ensure the code is still readable by splitting inline functions out into named functions and avoiding too many nested inline functions.

I also try to avoid excessively long function chains, they are fun but after a point you forget what your epically long chain of functions is doing… or why:

return inputs
  .map(i => getResults(i))
  .filter(results => results.length > 0)
  .map(result => getResultView(result))
  .reduce((index, result) => {
    index[] = result;

    return index
  }, {});

Shared state

When writing back end services it quickly becomes apparent that shared mutable state is dangerous. Sharing resources like files and streams across multiple functions becomes a nightmare to debug as you don’t know who changed what and when.

I’m a strong believer that mutable state itself is not evil, but it must be encapsulated and hide from public view. I’ve discussed tactics for encapsulating mutable state before. My rule of thumb is that any public method should always be callable multiple times, it should not have side effects that leave it in an incorrect state the next time it is called.


Principles don’t necessarily dictate software architecture or design but they do guide it. In general I would say that I love principles, but I hate rules. One of the reasons I tend to reject SOLID is that a set of principles people often try to implement as rules, disregarding the context they are being applied in. I also feel that SOLID is a bit of a forced acronym and some elements are vastly more important than others:

  • Single responsibility - important, but slightly ambiguous as to what you define as a responsibility
  • Open-closed principle - irrelevant as you should not be using inheritance.
  • Liskov subsitution - also irrelevant for the same reason
  • Interface segregation - partially a Java specific problem and it violates YAGNI
  • Dependency inversion - important

In general I would say that SOLID is more relevant in the Java world with a stricter adherence to object orientated programming and an over-reliance on inheritance to re-use code.

The principles that I find are actually useful in the node.js world are:

  • encapsulation of complexity - neat abstractions, presenting a nice public interface
  • encapsulation of state - this removes a whole class of errors
  • composition - if you want to re-use code, pass it in as a dependency. This makes it more testable and more flexible
  • the principle of least power - readability is a primary concern, where possible you should make your code understandable to the widest audience possible
  • YAGNI - not just important to reduce the amount of code you write, but to also reduce the amount other people have to read

Object orientated vs functional

As I alluded to earlier, I think people get too hung up on object orientated vs functional programming. You can apply almost all the functional programming principles in an object orientated language, if you want to. What you will find is that the same design choices will arise no matter what style you choose: how do you manage your dependencies? How do you encapsulate your logic? How do you re-use logic?

A good architecture should solve those problems.