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In robust CI/CD workflows, validating your Docker image before pushing to a registry helps catch runtime issues early. This guide shows you how to extend a GitLab CI pipeline with a docker_test job that consumes the image built by docker_build, verifies the /live endpoint, and ensures your container is production-ready.

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CI/CD Pipeline Overview

Define your basic stages and shared variables in .gitlab-ci.yml: 
stages:
  - test
  - containerization

variables:
  DOCKER_USERNAME: siddharth67
  IMAGE_VERSION: $CI_PIPELINE_ID
  MONGO_URI: 'mongodb+srv://supercluster.d83jji.mongodb.net/superData'
  MONGO_USERNAME: superuser
  MONGO_PASSWORD: $M_DB_PASSWORD

unit_testing:
  stage: test
  # …

code_coverage:
  stage: test
  # …
StageJob NamePurpose
testunit_testingExecute unit tests
testcode_coverageGenerate code coverage reports
containerizationdocker_buildBuild Docker image and save as artifact
containerizationdocker_testLoad the image, run container, and test /live

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Building and Archiving Docker Images

The docker_build job builds your Node.js app into a Docker image, then saves it as a tarball artifact for downstream jobs. 
docker_build:
  stage: containerization
  image: docker:24.0.5
  services:
    - docker:24.0.5-dind
  script:
    - docker build -t $DOCKER_USERNAME/solar-system:$IMAGE_VERSION .
    - docker images $DOCKER_USERNAME/solar-system:$IMAGE_VERSION
    - mkdir -p image
    - docker save $DOCKER_USERNAME/solar-system:$IMAGE_VERSION \
        -o image/solar-system-image-$IMAGE_VERSION.tar
  artifacts:
    paths:
      - image
    when: on_success
    expire_in: 3 days
Artifacts are retained for 3 days by default. Adjust expire_in to suit your retention policy.
Make sure sensitive environment variables (like MONGO_PASSWORD) are stored in GitLab CI/CD variables, not hard-coded.

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Testing the Docker Image Before Push

The docker_test job retrieves the saved image artifact, runs the container, and probes the /live endpoint using an Alpine container with wget. 
docker_test:
  stage: containerization
  image: docker:24.0.5
  needs:
    - docker_build
  services:
    - docker:24.0.5-dind
  script:
    - docker load -i image/solar-system-image-$IMAGE_VERSION.tar
    - docker run --name solar-system-app -d -p 3000:3000 \
        $DOCKER_USERNAME/solar-system:$IMAGE_VERSION
    - export IP=$(docker inspect -f \
        '{{range .NetworkSettings.Networks}}{{.IPAddress}}{{end}}' solar-system-app)
    - echo "App IP: $IP"
    - docker run --rm alpine \
        wget -qO- http://$IP:3000/live | grep -q '"live"'
Steps in docker_test:
  1. docker load: Imports the tarball into Docker.
  2. docker run: Starts the container on port 3000 in detached mode.
  3. docker inspect: Extracts the container’s IP address.
  4. wget: From an Alpine image, requests http://$IP:3000/live and checks for "live" in the response.

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Node.js Health Check Endpoints

Below is the simplified app.js. The /live endpoint returns { status: "live" } for liveness probes. 
const express = require('express');
const path = require('path');
const OS = require('os');
const bodyParser = require('body-parser');
const mongoose = require('mongoose');
const cors = require('cors');

const app = express();
app.use(bodyParser.json());
app.use(express.static(path.join(__dirname, '/')));
app.use(cors());

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("MongoDB connection error:", err);
});

app.get('/', (req, res) => {
  res.sendFile(path.join(__dirname, 'index.html'));
});

app.get('/os', (req, res) => {
  res.json({ os: OS.hostname(), env: process.env.NODE_ENV });
});

app.get('/live', (req, res) => {
  res.json({ status: "live" });
});

app.get('/ready', (req, res) => {
  res.json({ status: "ready" });
});

app.listen(3000, () => {
  console.log("Server running on port 3000");
});

module.exports = app;

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Pipeline Visualization

The image shows a GitLab CI/CD pipeline interface for a project named "Solar System NodeJS Pipeline," displaying stages and jobs such as code coverage, unit testing, docker build, and docker test.
With this setup, docker_test will only run once docker_build successfully produces and archives the image. A successful liveness check means the container is ready to be pushed.

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