Pipeline Configure Unit Testing

In this guide, we’ll configure GitLab CI/CD for the Solar System NodeJS project and add a robust unit testing job. You’ll learn how to create a structured .gitlab-ci.yml, manage sensitive MongoDB credentials via CI/CD variables, and ensure your NodeJS tests run reliably.

1. Initialize GitLab CI/CD Configuration

Start by creating a new file named .gitlab-ci.yml at your repository root. Define the pipeline stages and add a placeholder build job:

stages:
  # Define the execution order of pipeline stages
  - build
  - test
  - deploy

build-job:
  stage: build
  script:
    - echo "Building the project..."

Explicit stages improve readability and make it easier to extend the pipeline with additional jobs.

2. Define Workflow Rules

Specify when the pipeline should trigger by adding a workflow section with conditional rules:

workflow:
  name: Solar System NodeJS Pipeline
  rules:
    # Run on pushes to main or feature branches
    - if: $CI_COMMIT_BRANCH == "main" || $CI_COMMIT_BRANCH =~ /^feature/
      when: always
    # Run on merge request events from feature branches
    - if: $CI_MERGE_REQUEST_SOURCE_BRANCH_NAME =~ /^feature/ && $CI_PIPELINE_SOURCE == "merge_request_event"
      when: always

stages:
  - test

3. Add the Unit Testing Job

Next, define the unit_testing job in the test stage. This job uses the official NodeJS Docker image, installs dependencies, and runs tests with Mocha:

unit_testing:
  stage: test
  image: node:17-alpine3.14
  before_script:
    - npm install
  script:
    - npm test

Commit these changes to a new feature branch:

git checkout -b feature/setup-gitlab-ci
git add .gitlab-ci.yml
git commit -m "chore: add GitLab CI/CD pipeline with unit testing"
git push -u origin feature/setup-gitlab-ci

Pushing to feature/* will trigger a pipeline run.

The image shows a GitLab CI/CD pipeline interface for a project named "Solar System NodeJS Pipeline," indicating a failed unit testing job. The sidebar includes options for managing the project, such as issues, merge requests, and pipelines.

4. Diagnose the Test Failure

Inspect the job logs. The runner pulls the NodeJS image and installs packages, but npm test fails with a Mongoose connection error. Our application code in app.js relies on environment variables:

const mongoose = require('mongoose');

mongoose.connect(process.env.MONGO_URI, {
  user: process.env.MONGO_USERNAME,
  pass: process.env.MONGO_PASSWORD,
  useNewUrlParser: true,
  useUnifiedTopology: true,
}, err => {
  if (err) {
    console.error("Connection error:", err);
  } else {
    console.log("MongoDB Connection Successful");
  }
});

Without the MongoDB credentials, tests cannot connect.

5. Supply Environment Variables

Add a variables section at the top of your .gitlab-ci.yml to inject the connection details:

variables:
  MONGO_URI: 'mongodb+srv://supercluster.d83jj.mongodb.net/superData'
  MONGO_USERNAME: superuser
  MONGO_PASSWORD: $M_DB_PASSWORD

stages:
  - test

unit_testing:
  stage: test
  image: node:17-alpine3.14
  before_script:
    - npm install
  script:
    - npm test

Never expose plain-text passwords in your repository. Always use masked CI/CD variables for credentials.

Here’s a quick reference for these variables:

Variable Name	Purpose	Example
MONGO_URI	MongoDB connection string	`mongodb+srv://.../superData`
MONGO_USERNAME	Database user name	`superuser`
MONGO_PASSWORD	Masked variable reference	`$M_DB_PASSWORD`

6. Configure Masked Variables in GitLab

In your GitLab project, navigate to Settings > CI/CD > Variables. Create a new variable:

Key: M_DB_PASSWORD
Value: (your database password)
Masked: ✔
Protected: as required

The image shows a GitLab CI/CD settings page, specifically focusing on the section for managing variables. It includes details about a masked variable named "M_DB_PASSWORD" and a notification confirming its successful addition.

Return to the Pipeline Editor on your feature branch and commit the updated .gitlab-ci.yml:

The image shows a GitLab Pipeline Editor interface with options to switch branches and configure a CI/CD pipeline. The sidebar includes various project management options like Merge requests, Manage, Plan, and more.

7. Verify the Successful Pipeline

A new pipeline should start automatically. This time, the unit_testing job completes successfully:

The image shows a GitLab CI/CD pipeline interface for a project named "Solar System NodeJS Pipeline," indicating a successful test job labeled "unittesting." The pipeline has passed, and the interface displays various project management options on the left sidebar.

8. Review the Test Logs

The job log confirms the install and test steps:

$ npm install
added 364 packages, and audited 365 packages in 8s
44 packages are looking for funding
Run `npm fund` for details
vulnerabilities (1 high, 1 critical)
To address all issues, run:
  npm audit fix

$ npm test
> Solar System@6.7.6 test
> mocha app-test.js --timeout 10000 --reporter mocha-junit-reporter --exit
Server successfully running on port 3000
  ✓ should return all planets
  ✓ should return planet by ID
  ...

Now that unit tests are passing, the next step is to collect test reports using the artifacts keyword.

Introduction

Architecture & Core Concepts

Continuous Integration with GitLab

Continuous Deployment with GitLab

Optimization, Security and Monitoring

Self-Managed Runners

Auto DevOps

Pipeline Configure Unit Testing

1. Initialize GitLab CI/CD Configuration

2. Define Workflow Rules

3. Add the Unit Testing Job

4. Diagnose the Test Failure

5. Supply Environment Variables

6. Configure Masked Variables in GitLab

7. Verify the Successful Pipeline

8. Review the Test Logs

References

Watch Video

​1. Initialize GitLab CI/CD Configuration

​2. Define Workflow Rules

​3. Add the Unit Testing Job

​4. Diagnose the Test Failure

​5. Supply Environment Variables

​6. Configure Masked Variables in GitLab

​7. Verify the Successful Pipeline

​8. Review the Test Logs

​References

Watch Video

1. Initialize GitLab CI/CD Configuration

2. Define Workflow Rules

3. Add the Unit Testing Job

4. Diagnose the Test Failure

5. Supply Environment Variables

6. Configure Masked Variables in GitLab

7. Verify the Successful Pipeline

8. Review the Test Logs

References