Nx is a set of extensible dev tools for monorepos. Monorepos provide a lot of advantages:

• Everything at that current commit works together. Changes can be verified across all affected parts of the organization.
• Easy to split code into composable modules
• Easier dependency management
• One toolchain setup
• Code editors and IDEs are "workspace" aware
• Consistent developer experience
• ...

But they come with their own technical challenges. The more code you add into your repository, the slower the CI gets.

This repo is an example Nx Workspace. It has two applications. Each app has 15 libraries, each of which consists of 30 components. The two applications also share code.

If you run nx dep-graph, you will see somethign like this:

This example will use Azure Pipelines, but a very similar setup will work with CircleCI, Jenkins, GitLab, etc..

Most projects that don't use Nx end up building, testing, and linting every single library and application in the repository. The easiest way to implement it with Nx is to do something like this:

jobs:
  - job: ci
    timeoutInMinutes: 120
    pool:
      vmImage: 'ubuntu-latest'
    steps:
      - template: .azure-pipelines/steps/install-node-modules.yml
      - script: yarn nx run-many --target=test --all
      - script: yarn nx run-many --target=lint --all
      - script: yarn nx run-many --target=build --all --prod

This will retest, relint, rebuild every project. Doing this for this repository takes about 45 minutes (note that most enterprise monorepos are significantly larger, so in those cases we are talking about many hours.)

The easiest way to make your CI faster is to do less work, and Nx is great at that.

Nx knows what is affected by your PR, so it doesn't have to test/build/lint everything. Say the PR only touches ng-lib9. If you run nx affected:dep-graph, you will see something like this:

If you update azure-pipelines.yml to use nx affected instead of nx run-many:

jobs:
  - job: ci
    timeoutInMinutes: 120
    pool:
      vmImage: 'ubuntu-latest'
    steps:
      - template: .azure-pipelines/steps/install-node-modules.yml
      - script: yarn nx affected --target=test --base=origin/master
      - script: yarn nx affected --target=lint --base=origin/master
      - script: yarn nx affected --target=build --base=origin/master --prod

the CI time will go down from 45 minutes to 8 minutes.

This is a good result. It helps to lower the average CI time, but doesn't help with the worstcase scenario. Some PR are going to affect a large portion of the repo.

You could make it faster by running the commands in parallel:

jobs:
  - job: ci
    timeoutInMinutes: 120
    pool:
      vmImage: 'ubuntu-latest'
    variables:
      IS_PR: $[ eq(variables['Build.Reason'], 'PullRequest') ]
    steps:
      - template: .azure-pipelines/steps/install-node-modules.yml
      - script: yarn nx affected --target=test --base=origin/master --parallel
      - script: yarn nx affected --target=lint --base=origin/master --parallel
      - script: yarn nx affected --target=build --base=origin/master --prod --parallel

This helps but it still has a ceiling. At some point, this won't be enough. A single agent is simply insufficent. You need to distrubte CI across a grid of machines.

To distribute you need to split your job into multiple jobs.

              / lint1
initial_setup - lint2
              - lint3
              - test1
              ....
              \ build3

The initial_setup job figures out what is affected and what needs to run on what agent.

jobs:
  - job: initial_setup
    pool:
      vmImage: 'ubuntu-latest'
    variables:
      IS_PR: $[ eq(variables['Build.Reason'], 'PullRequest') ]
    steps:
      - template: .azure-pipelines/steps/install-node-modules.yml
      - powershell: echo "##vso[task.setvariable variable=COMMANDS;isOutput=true]$(node ./tools/scripts/calculate-commands.js $(IS_PR))"
        name: setCommands
      - script: echo $(setCommands.COMMANDS)
        name: echoCommands

Where calculate-commands.js looks like this:

const execSync = require('child_process').execSync;
const isMaster = process.argv[2] === 'False';
const baseSha = isMaster ? 'origin/master~1' : 'origin/master';

// prints an object with keys {lint1: [...], lint2: [...], lint3: [...], test1: [...], .... build3: [...]}
console.log(
  JSON.stringify({
    ...commands('lint'),
    ...commands('test'),
    ...commands('build')
  })
);

function commands(target) {
  const array = JSON.parse(
    execSync(`npx nx print-affected --base=${baseSha} --target=${target}`)
      .toString()
      .trim()
  ).tasks.map(t => t.target.project);

  array.sort(() => 0.5 - Math.random());
  const third = Math.floor(array.length / 3);
  const a1 = array.slice(0, third);
  const a2 = array.slice(third, third * 2);
  const a3 = array.slice(third * 2);
  return {
    [target + '1']: a1,
    [target + '2']: a2,
    [target + '3']: a3
  };
}

Let's step through it:

The following defines the base sha Nx uses to execute affected commands.

const isMaster = process.argv[2] === 'False';
const baseSha = isMaster ? 'origin/master~1' : 'origin/master';

If it is a PR, Nx sees what has changed compared to origin/master. If it's master, Nx sees what has changed compared to the previous commit (this can be made more robust by remembering the last successful master run, which can be done by labeling the commit).

The following prints information about affected project that have the needed target. print-affected doesn't run any targets, just prints information about them.

execSync(`npx nx print-affected --base=${baseSha} --target=${target}`)
  .toString()
  .trim();

The rest of the commands splits the list of projects into three grouprs or bins.

Other jobs use the information crated by initial_step to execute the needed tasks.

- job: lint1
  dependsOn: initial_setup # this tells lin1 to wait for initial_setup to complete
  condition: |
    and(
      succeeded(),
      not(contains(
        dependencies.initial_setup.outputs['setCommands.COMMANDS'],
        '"lint1":[]'
      ))
    )
  pool:
    vmImage: 'ubuntu-latest'
  variables:
    COMMANDS: $[ dependencies.initial_setup.outputs['setCommands.COMMANDS'] ]
  steps:
    - template: .azure-pipelines/steps/install-node-modules.yml
    - script: node ./tools/scripts/run-many.js '$(COMMANDS)' lint1 lint

where run-many.js:

const execSync = require('child_process').execSync;

const commands = JSON.parse(process.argv[2]);
const projects = commands[process.argv[3]];
const target = process.argv[4];
execSync(
  `npx nx run-many --target=${target} --projects=${projects.join(
    ','
  )} --parallel`,
  {
    stdio: [0, 1, 2]
  }
);

This example doesn't do anything with the artifacts created by the build, but often you will need to upload/deploy them. There are several ways to handle it.

1. You can create a job per application and then copy the output to the staging area, and then once tests complete unstage the files in a separate job and then deploy them.
2. You can use the outputs property from running npx nx print-affected --target=build to stash and unstash files without having a job per app.

{
  "tasks": [
    {
      "id": "react-app:build",
      "overrides": {},
      "target": {
        "project": "react-app",
        "target": "build"
      },
      "command": "npm run nx -- build react-app",
      "outputs": [
        "dist/apps/react-app"
      ]
    },
    {
      "id": "ng-app:build",
      "overrides": {},
      "target": {
        "project": "ng-app",
        "target": "build"
      },
      "command": "npm run nx -- build ng-app",
      "outputs": [
        "dist/apps/ng-app"
      ]
    }
  ],
  "dependencyGraph": {
    ...
  }
}

With these changes, rebuild/retesting/relinting everything takes only 7 minutes. The average CI time is even faster. The best part of this is that you can add more agents to your pool when needed, so the worst-case scenaro CI time will always be under 15 minutes regardless of how big the repo is.

This example uses a fixed agent graph. This setup works without any problems for all CI providers. It also scales well for repo of almost any size. So before doing anything more sophisticated, I'd try this approach. Some CI providers (e.g., Jenkins) allow scaling the number of agents dynamically. The print-affected and run-many commands can be used to implement those setups as well.

1. Rebuilding/retesting/relinting everyting on every code change doesn't scale. In this example it takes 45 minutes.
2. Nx lets you rebuild only what is affected, which drastically improves the average CI time, but it doesn't address the worst-case scenario.
3. Nx helps you run multiple targets in parallel on the same machine.
4. Nx provides print-affected and run-many which make implemented distributed CI simple. In this example the time went down from 45 minutes to only 7