Organizing backend code

I’ve come to prefer a backend codebase structure that involves four top-level directories, arranged in an ordered dependency hierarchy:

• app/ - high-level stateless code that ties things together but is largely domain-agnostic
• domain/ - domain-specific stateful code for the relevant problem domain
• system/ - domain-agnostic stateful code for things like revision history, event log, bots
• common/ - low-level stateless domain-agnostic libraries, utilities, and constants

Code in app/ can depend on all other code; code in domain/ can depend on anything except app/; etc.

Dependency restrictions can be enforced with tools like eslint’s no-restricted-imports or ArchUnit for Java.

Let’s walk through these directories in detail, starting from the bottom up.

Common code

Examples of common code include:

• Wrappers around external logging and monitoring libraries
• Pure function utilities for things like string or list manipulation
• Widely used standardized constants such as ISO country codes

One way to think about common code is: if your startup pivots and you need to start a totally new codebase in a different domain, you should be able to copy over all the common code without needing to refactor anything.

Another way to think about common code is: it could be easily bundled up and distributed as packages or libraries via npm, maven, etc. Indeed, reusing open source external packages instead of hand rolling common code is generally the best approach. But in every codebase I’ve worked in, we’ve ended up with some components that are common-like in nature (ie domain-agnostic) but still specific to our particular application.

System code

Examples of system code:

• An entity revision history tracking system
• An event logging system backed by Postgres

The difference between “system” and “common” is stateful vs stateless. When I say “stateful”, I mean the component actively reads/writes from a persistent data store like PostgreSQL, Redis, Elasticsearch.

A Redis client library wrapper would live in “common”. A durable event system that uses that client library to write messages for consumers to read – that would be a system-level component.

Domain code

The contents of the domain directory will vary based on the application problem domain. For example:

• For a restaurant app, it could contain components for managing reservations, menus, order tracking, etc
• For a freight forwarding app, it could contain components for booking management, freight execution, contract and pricing controls, etc
• For a property management app, it could contain components leasing, rent payments, work orders, etc

One way to think about domain code is: if a concept is part of your domain model shared with business stakeholders, it should be within the domain directory. If a concept is exposed to end users in the product, it should live within the domain directory. End users do not care about which logging library you use (at the common layer) or which web server runner you use (at the app layer). End users do care about the domain concepts they manipulate through the product (at the domain layer).

For this reason, I tend to include in the domain directory any modules responsible for tenants, users, and roles. While on the one hand these modules might be considered domain-agnostic and therefore better fits for the system directory, the behavior of such modules heavily impacts product behavior and therefore can be considered part of the domain model.

App code

The app directory is the orchestrator of the system. It is like the common directory in that it doesn’t deal directly with domain concepts, but it differs in that it depends on the domain code. Here are some examples of things that live at the app layer:

• Web server entry point that loads web-facing components and starts listening for requests
• Command line utility entry point that loads CLI components and dispatches commands to the relevant components
• An authentication component, perhaps in the form of a token issuer or a session manager
• A GraphQL global node query resolver that can resolve any entity from any part of the domain
• A health check endpoint that verifies the status of different components across the entire system

Unlike the common code, app code cannot simply be copied from one codebase to another. But the parts that reference the domain code can be built in a configurable way that is easy to swap out for other domains.

Tying it all together

A codebase for a restaurant SaaS application might look something like:

app/
  authentication
  entity-lookup
  gql-server
  http-server-entry
  cli-entry

domain/
  reservations
  menu
  orders
  seating-layout
  users
  tenants

system/
  durable-event
  revision-history
  system-bots

common/
  db-client
  metrics-client
  s3-client
  string-util

These buckets provide the high-level scaffolding for an application, and other techniques for code organization within these buckets merit their own descriptions.