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madiepevmadiepev
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add test branch for gh action based labs
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‎.github/workflows/docs-validation.yml‎

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name: Documentation Validation
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on:
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push:
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paths:
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- 'docs/**'
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- '*.md'
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- 'Instructions/**'
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pull_request:
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paths:
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- 'docs/**'
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- '*.md'
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- 'Instructions/**'
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jobs:
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validate-docs:
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runs-on: ubuntu-latest
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steps:
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- name: Checkout repository
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uses: actions/checkout@v4
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- name: Setup Node.js
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uses: actions/setup-node@v4
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with:
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node-version: '18'
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- name: Install markdownlint
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run: npm install -g markdownlint-cli
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- name: Validate markdown files
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run: |
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markdownlint docs/ --ignore node_modules
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markdownlint *.md --ignore node_modules
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markdownlint Instructions/ --ignore node_modules
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continue-on-error: true
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- name: Check markdown links
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uses: gaurav-nelson/github-action-markdown-link-check@v1
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with:
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use-quiet-mode: 'yes'
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use-verbose-mode: 'yes'
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config-file: '.github/workflows/markdown-link-check-config.json'
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folder-path: 'docs/, Instructions/'
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continue-on-error: true
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spell-check:
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runs-on: ubuntu-latest
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steps:
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- name: Checkout repository
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uses: actions/checkout@v4
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- name: Setup Node.js
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uses: actions/setup-node@v4
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with:
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node-version: '18'
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- name: Install cspell
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run: npm install -g cspell
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- name: Run spell check
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run: |
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cspell "docs/**/*.md"
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cspell "*.md"
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cspell "Instructions/**/*.md"
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continue-on-error: true

‎.github/workflows/lab-07-monitor.yml‎

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name: "Lab 07: Monitor GenAI Application"
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on:
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workflow_dispatch:
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inputs:
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environment:
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description: 'Environment to deploy to'
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required: true
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default: 'dev'
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type: choice
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options:
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- dev
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- staging
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- prod
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num_requests:
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description: 'Number of telemetry requests to generate'
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required: false
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default: '5'
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type: string
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push:
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paths:
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- 'labs/07-observability/**'
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- '.github/workflows/lab-07-monitor.yml'
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branches:
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- main
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- 'lab/07-*'
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pull_request:
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paths:
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- 'labs/07-observability/**'
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env:
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LAB_NAME: "07-observability"
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LAB_TITLE: "Monitor GenAI Application"
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jobs:
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monitor-genai:
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runs-on: ubuntu-latest
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environment: ${{ github.event.inputs.environment || 'dev' }}
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steps:
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- name: Checkout repository
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uses: actions/checkout@v4
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- name: Set up Python 3.8+
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uses: actions/setup-python@v4
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with:
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python-version: '3.8'
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip
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pip install azure-ai-projects azure-identity azure-monitor-opentelemetry python-dotenv
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- name: Azure login
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uses: azure/login@v1
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with:
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creds: ${{ secrets.AZURE_CREDENTIALS }}
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- name: Set up environment variables
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run: |
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echo "PROJECT_CONNECTION_STRING=${{ secrets.PROJECT_CONNECTION_STRING }}" >> $GITHUB_ENV
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echo "CI_MODE=true" >> $GITHUB_ENV
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- name: Run Lab 07 - Monitor GenAI Application
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working-directory: ./labs/07-observability
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run: |
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echo "::group::Lab Execution"
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python monitor_genai.py --ci-mode --requests ${{ github.event.inputs.num_requests || '5' }}
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echo "::endgroup::"
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- name: Upload lab results
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uses: actions/upload-artifact@v3
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if: always()
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with:
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name: lab-07-monitoring-results-${{ github.run_id }}
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path: |
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labs/07-observability/monitoring_results.json
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retention-days: 30
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- name: Comment on PR with results
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if: github.event_name == 'pull_request'
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uses: actions/github-script@v6
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with:
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script: |
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const fs = require('fs');
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let resultsContent = 'Lab execution failed - no results file found';
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try {
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const results = JSON.parse(fs.readFileSync('labs/07-observability/monitoring_results.json', 'utf8'));
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const summary = results.summary || {};
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resultsContent = `## 📊 Lab 07: Monitor GenAI Application Results
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**Status:** ${results.status === 'success' ? '✅ Success' : '❌ Failed'}
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**Environment:** ${{ github.event.inputs.environment || 'dev' }}
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**Execution Time:** ${new Date().toISOString()}
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### 📈 Monitoring Results
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- **Monitoring Enabled:** ${summary.monitoring_enabled ? '✅' : '❌'}
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- **Application Insights Connected:** ${summary.application_insights_connected ? '✅' : '❌'}
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- **Requests Generated:** ${summary.total_requests_generated || 0}
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- **Success Rate:** ${summary.success_rate || '0%'}
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- **Average Response Time:** ${Math.round(summary.avg_response_time_ms || 0)}ms
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### 🔍 Telemetry Data
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- **Total Requests:** ${summary.total_requests_generated || 0}
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- **Successful Requests:** ${summary.successful_requests || 0}
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${results.status === 'failed' ? `
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### ❌ Errors
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\`\`\`
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${results.error || 'Unknown error occurred'}
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\`\`\`
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` : ''}
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### 🔗 View Results
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- **Azure AI Foundry:** Check the monitoring dashboard in your AI Foundry project
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- **Application Insights:** View detailed telemetry in Azure Portal
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- [Download detailed results](https://github.com/${{ github.repository }}/actions/runs/${{ github.run_id }})
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### 📚 Next Steps
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1. Open your Azure AI Foundry project
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2. Navigate to the **Monitoring** section
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3. Review the generated telemetry data
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4. Set up custom alerts and dashboards
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`;
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} catch (error) {
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console.error('Error reading results:', error);
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}
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github.rest.issues.createComment({
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issue_number: context.issue.number,
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owner: context.repo.owner,
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repo: context.repo.repo,
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body: resultsContent
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});
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- name: Final status check
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if: always()
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run: |
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if [ -f "labs/07-observability/monitoring_results.json" ]; then
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status=$(python -c "import json; print(json.load(open('labs/07-observability/monitoring_results.json')).get('status', 'failed'))")
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if [ "$status" = "success" ]; then
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echo "::notice title=Lab 07 Success::Monitoring lab completed successfully! 📊"
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exit 0
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else
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echo "::error title=Lab 07 Failed::Monitoring lab failed. Check logs for details."
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exit 1
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fi
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else
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echo "::error title=Lab 07 Failed::No results file found."
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exit 1
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fi

‎.github/workflows/lab-08-trace.yml‎

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name: "Lab 08: Trace GenAI Application"
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on:
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workflow_dispatch:
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inputs:
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environment:
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description: 'Environment to deploy to'
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required: true
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default: 'dev'
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type: choice
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options:
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- dev
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- staging
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- prod
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push:
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paths:
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- 'labs/08-tracing/**'
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- '.github/workflows/lab-08-trace.yml'
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branches:
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- main
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- 'lab/08-*'
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pull_request:
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paths:
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- 'labs/08-tracing/**'
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env:
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LAB_NAME: "08-tracing"
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LAB_TITLE: "Trace GenAI Application"
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jobs:
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trace-genai:
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runs-on: ubuntu-latest
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environment: ${{ github.event.inputs.environment || 'dev' }}
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steps:
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- name: Checkout repository
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uses: actions/checkout@v4
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- name: Set up Python 3.8+
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uses: actions/setup-python@v4
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with:
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python-version: '3.8'
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- name: Install dependencies
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run: |
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python -m pip install --upgrade pip
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pip install azure-ai-projects azure-identity azure-monitor-opentelemetry azure-ai-inference python-dotenv
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- name: Azure login
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uses: azure/login@v1
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with:
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creds: ${{ secrets.AZURE_CREDENTIALS }}
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- name: Set up environment variables
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run: |
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echo "PROJECT_CONNECTION_STRING=${{ secrets.PROJECT_CONNECTION_STRING }}" >> $GITHUB_ENV
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echo "CI_MODE=true" >> $GITHUB_ENV
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- name: Run Lab 08 - Trace GenAI Application
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working-directory: ./labs/08-tracing
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run: |
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echo "::group::Lab Execution"
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python trace_genai.py --ci-mode
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echo "::endgroup::"
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- name: Upload lab results
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uses: actions/upload-artifact@v3
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if: always()
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with:
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name: lab-08-tracing-results-${{ github.run_id }}
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path: |
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labs/08-tracing/tracing_results.json
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retention-days: 30
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- name: Comment on PR with results
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if: github.event_name == 'pull_request'
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uses: actions/github-script@v6
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with:
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script: |
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const fs = require('fs');
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let resultsContent = 'Lab execution failed - no results file found';
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try {
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const results = JSON.parse(fs.readFileSync('labs/08-tracing/tracing_results.json', 'utf8'));
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const summary = results.summary || {};
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resultsContent = `## 🔍 Lab 08: Trace GenAI Application Results
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**Status:** ${results.status === 'success' ? '✅ Success' : '❌ Failed'}
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**Environment:** ${{ github.event.inputs.environment || 'dev' }}
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**Execution Time:** ${new Date().toISOString()}
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### 🔬 Tracing Results
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- **Tracing Enabled:** ${summary.tracing_enabled ? '✅' : '❌'}
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- **Content Recording:** ${summary.content_recording_enabled ? '✅' : '❌'}
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- **Workflows Executed:** ${summary.workflows_executed || 0}
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- **Spans Created:** ${summary.total_spans_created || 0}
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- **Workflow Success Rate:** ${summary.workflow_success_rate || '0%'}
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- **Error Scenarios Traced:** ${summary.error_scenarios_traced || 0}
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### 🏃‍♂️ Workflow Analysis
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- **Hiking Assistant Workflow:** Multi-step AI workflow with preferences, recommendations, and gear suggestions
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- **Error Scenario Tracing:** Demonstrated error handling and tracing capabilities
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- **Distributed Tracing:** Each step traced with detailed span information
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${results.status === 'failed' ? `
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### ❌ Errors
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\`\`\`
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${results.error || 'Unknown error occurred'}
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\`\`\`
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` : ''}
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### 🔗 View Traces
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- **Azure AI Foundry:** Check the tracing dashboard in your AI Foundry project
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- **Application Insights:** View detailed distributed traces in Azure Portal
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- **Transaction Search:** Use Application Insights transaction search to find specific traces
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- [Download detailed results](https://github.com/${{ github.repository }}/actions/runs/${{ github.run_id }})
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### 📚 Next Steps
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1. Open your Azure AI Foundry project
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2. Navigate to the **Tracing** section
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3. Search for traces with your session IDs
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4. Analyze the workflow execution paths
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5. Review error scenarios and debugging information
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`;
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} catch (error) {
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console.error('Error reading results:', error);
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}
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github.rest.issues.createComment({
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issue_number: context.issue.number,
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owner: context.repo.owner,
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repo: context.repo.repo,
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body: resultsContent
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});
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- name: Final status check
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if: always()
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run: |
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if [ -f "labs/08-tracing/tracing_results.json" ]; then
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status=$(python -c "import json; print(json.load(open('labs/08-tracing/tracing_results.json')).get('status', 'failed'))")
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if [ "$status" = "success" ]; then
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echo "::notice title=Lab 08 Success::Tracing lab completed successfully! 🔍"
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exit 0
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else
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echo "::error title=Lab 08 Failed::Tracing lab failed. Check logs for details."
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exit 1
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fi
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else
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echo "::error title=Lab 08 Failed::No results file found."
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exit 1
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fi

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