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This guide demonstrates how to add a GitHub Actions job that uploads unit test and code coverage reports to an Amazon S3 bucket. You can place this reporting job anywhere in your workflow by adjusting the needs dependencies. In this example, we insert it after the code coverage job.

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Workflow Configuration

First, define any required environment variables at the top of your workflow: 
env:
  MONGO_URI: mongodb+srv://supercluster.d83jj.mongodb.net/superData
  MONGO_USERNAME: ${{ vars.MONGO_USERNAME }}
  MONGO_PASSWORD: ${{ secrets.MONGO_PASSWORD }}

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reports-s3 Job

Add the following reports-s3 job to download artifacts, merge XML reports, and prepare for an S3 upload: 
jobs:
  reports-s3:
    name: AWS S3 - Upload Reports
    runs-on: ubuntu-latest
    needs: [code-coverage, unit-testing]
    continue-on-error: true

    steps:
      - name: Download Mocha Test Artifact
        uses: actions/download-artifact@v3
        with:
          name: Mocha-Test-Result

      - name: Download Code Coverage Artifact
        uses: actions/download-artifact@v3
        with:
          name: Code-Coverage-Result

      - name: Merge Test Files
        run: |
          mkdir reports-${{ github.sha }}
          mv cobertura-coverage.xml reports-${{ github.sha }}/
          mv test-results.xml reports-${{ github.sha }}/
          ls -ltr reports-${{ github.sha }}/

      - name: Upload to S3 (placeholder)
        run: echo "Uploading reports directory to S3"
  • The needs: [code-coverage, unit-testing] directive ensures this job runs only after your unit tests and coverage jobs finish.
  • continue-on-error: true prevents build failures if uploads fail.
  • Use actions/download-artifact@v3 to fetch artifacts from previous jobs.

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Step Summary

StepActionArtifact / Directory
Download Mocha Testactions/download-artifact@v3Mocha-Test-Result
Download Code Coverageactions/download-artifact@v3Code-Coverage-Result
Merge XML ReportsShell commandsreports-${{ github.sha }}/
Upload to S3 (placeholder)run: echo "Uploading reports directory"N/A

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Example: Unit Testing Job

The following job runs unit tests and uploads the results as an artifact named Mocha-Test-Result. 
unit-testing:
  runs-on: ubuntu-latest
  steps:
    - name: Checkout Repository
      uses: actions/checkout@v4

    - name: Setup Node.js
      uses: actions/setup-node@v3
      with:
        node-version: ${{ matrix.nodejs_version }}

    - name: Cache npm dependencies
      uses: actions/cache@v3
      with:
        path: node_modules
        key: ${{ runner.os }}-node-modules-${{ hashFiles('package-lock.json') }}

    - name: Install Dependencies
      run: npm install

    - name: Run Unit Tests
      run: npm test

    - name: Archive Test Result
      if: always()
      uses: actions/upload-artifact@v3
      with:
        name: Mocha-Test-Result
        path: test-results.xml

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Example: Code Coverage Job

This job executes your coverage script and archives the coverage directory: 
code-coverage:
  runs-on: ubuntu-latest
  steps:
    - name: Checkout Repository
      uses: actions/checkout@v4

    - name: Setup Node.js
      uses: actions/setup-node@v3
      with:
        node-version: ${{ matrix.nodejs_version }}

    - name: Cache npm dependencies
      uses: actions/cache@v3
      with:
        path: node_modules
        key: ${{ runner.os }}-node-modules-${{ hashFiles('package-lock.json') }}

    - name: Install Dependencies
      run: npm install

    - name: Run Code Coverage
      continue-on-error: true
      run: npm run coverage

    - name: Archive Coverage Report
      uses: actions/upload-artifact@v3
      with:
        name: Code-Coverage-Result
        path: coverage
        retention-days: 5
After you push these changes, the GitHub Actions graph will display the AWS S3 - Upload Reports job dependent on both unit testing and code coverage.
The image shows a GitHub Actions workflow interface with a job titled "AWS S3 - Upload Reports" that has successfully completed. It includes steps like setting up the job, downloading artifacts, merging test files, and uploading to AWS S3.

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Sample Merge Output

When this job runs, you’ll see output similar to: 
mkdir reports-570s29c8d7109c898d1ca252789dbece268d3/
mv cobertura-coverage.xml reports-570s29c8d7109c898d1ca252789dbece268d3/
mv test-results.xml reports-570s29c8d7109c898d1ca252789dbece268d3/
ls -ltr reports-570s29c8d7109c898d1ca252789dbece268d3/
This confirms your XML reports are consolidated under reports-${{ github.sha }}.

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Next Steps

In the next guide, you’ll implement the actual Amazon S3 upload using AWS CLI or an official GitHub Action.

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