Task 1 Fully Complete #2

Workflow file for this run

	name: ProdSegmenter CI/CD Pipeline

	on:
	push:
	branches: [ main, develop ]
	pull_request:
	branches: [ main ]
	workflow_dispatch:

	env:
	PYTHON_VERSION: '3.10'
	AZURE_FUNCTIONAPP_NAME: 'func-prodsegmenter-inference'
	AZURE_WEBAPP_NAME: 'app-prodsegmenter-frontend'

	jobs:
	# Code Quality and Linting
	lint:
	runs-on: ubuntu-latest
	steps:
	- uses: actions/checkout@v3

	- name: Set up Python
	uses: actions/setup-python@v4
	with:
	python-version: ${{ env.PYTHON_VERSION }}

	- name: Install dependencies
	run: \|
	python -m pip install --upgrade pip
	pip install black flake8 mypy
	pip install -r requirements.txt

	- name: Run Black formatter check
	run: black --check --diff .

	- name: Run Flake8 linter
	run: flake8 . --count --select=E9,F63,F7,F82 --show-source --statistics

	- name: Run MyPy type checker
	run: mypy training/ deployment/ --ignore-missing-imports

	# Unit and Integration Tests
	test:
	runs-on: ubuntu-latest
	needs: lint
	strategy:
	matrix:
	python-version: ['3.9', '3.10', '3.11']

	steps:
	- uses: actions/checkout@v3

	- name: Set up Python ${{ matrix.python-version }}
	uses: actions/setup-python@v4
	with:
	python-version: ${{ matrix.python-version }}

	- name: Cache pip dependencies
	uses: actions/cache@v3
	with:
	path: ~/.cache/pip
	key: ${{ runner.os }}-pip-${{ hashFiles('**/requirements.txt') }}
	restore-keys: \|
	${{ runner.os }}-pip-

	- name: Install dependencies
	run: \|
	python -m pip install --upgrade pip
	pip install pytest pytest-cov pytest-mock pytest-xdist
	pip install -r requirements.txt

	- name: Run unit tests
	run: \|
	pytest tests/ -v --cov=training --cov=deployment \
	--cov-report=xml --cov-report=html \
	--junitxml=test-results.xml \
	-m "not slow and not integration"

	- name: Upload coverage to Codecov
	uses: codecov/codecov-action@v3
	with:
	file: ./coverage.xml
	flags: unittests
	name: codecov-umbrella

	- name: Upload test results
	uses: actions/upload-artifact@v3
	if: always()
	with:
	name: test-results-${{ matrix.python-version }}
	path: \|
	test-results.xml
	htmlcov/

	# Integration Tests (with Azure services mocked)
	integration-test:
	runs-on: ubuntu-latest
	needs: test
	steps:
	- uses: actions/checkout@v3

	- name: Set up Python
	uses: actions/setup-python@v4
	with:
	python-version: ${{ env.PYTHON_VERSION }}

	- name: Install dependencies
	run: \|
	python -m pip install --upgrade pip
	pip install pytest pytest-mock
	pip install -r requirements.txt

	- name: Run integration tests
	run: \|
	pytest tests/integration/ -v \
	--junitxml=integration-test-results.xml \
	-m "integration"

	- name: Upload integration test results
	uses: actions/upload-artifact@v3
	if: always()
	with:
	name: integration-test-results
	path: integration-test-results.xml

	# Security Scanning
	security:
	runs-on: ubuntu-latest
	needs: lint
	steps:
	- uses: actions/checkout@v3

	- name: Set up Python
	uses: actions/setup-python@v4
	with:
	python-version: ${{ env.PYTHON_VERSION }}

	- name: Install security tools
	run: \|
	python -m pip install --upgrade pip
	pip install bandit safety
	pip install -r requirements.txt

	- name: Run Bandit security linter
	run: bandit -r training/ deployment/ -f json -o bandit-report.json
	continue-on-error: true

	- name: Run Safety vulnerability check
	run: safety check --json --output safety-report.json
	continue-on-error: true

	- name: Upload security reports
	uses: actions/upload-artifact@v3
	if: always()
	with:
	name: security-reports
	path: \|
	bandit-report.json
	safety-report.json

	# Build Docker Images
	build-images:
	runs-on: ubuntu-latest
	needs: [test, integration-test]
	if: github.ref == 'refs/heads/main' \|\| github.ref == 'refs/heads/develop'

	steps:
	- uses: actions/checkout@v3

	- name: Set up Docker Buildx
	uses: docker/setup-buildx-action@v2

	- name: Login to Azure Container Registry
	uses: azure/docker-login@v1
	with:
	login-server: ${{ secrets.AZURE_CONTAINER_REGISTRY }}
	username: ${{ secrets.AZURE_ACR_USERNAME }}
	password: ${{ secrets.AZURE_ACR_PASSWORD }}

	- name: Build and push Azure Function image
	uses: docker/build-push-action@v4
	with:
	context: ./deployment/azure_function
	push: true
	tags: \|
	${{ secrets.AZURE_CONTAINER_REGISTRY }}/prodsegmenter-api:latest
	${{ secrets.AZURE_CONTAINER_REGISTRY }}/prodsegmenter-api:${{ github.sha }}
	cache-from: type=gha
	cache-to: type=gha,mode=max

	- name: Build and push Streamlit frontend image
	uses: docker/build-push-action@v4
	with:
	context: ./deployment/streamlit_frontend
	push: true
	tags: \|
	${{ secrets.AZURE_CONTAINER_REGISTRY }}/prodsegmenter-frontend:latest
	${{ secrets.AZURE_CONTAINER_REGISTRY }}/prodsegmenter-frontend:${{ github.sha }}
	cache-from: type=gha
	cache-to: type=gha,mode=max

	# Deploy to Development Environment
	deploy-dev:
	runs-on: ubuntu-latest
	needs: build-images
	if: github.ref == 'refs/heads/develop'
	environment: development

	steps:
	- uses: actions/checkout@v3

	- name: Azure Login
	uses: azure/login@v1
	with:
	creds: ${{ secrets.AZURE_CREDENTIALS }}

	- name: Deploy Azure Function (Dev)
	uses: Azure/functions-action@v1
	with:
	app-name: ${{ env.AZURE_FUNCTIONAPP_NAME }}-dev
	package: './deployment/azure_function'
	respect-funcignore: true

	- name: Deploy Streamlit App (Dev)
	uses: azure/webapps-deploy@v2
	with:
	app-name: ${{ env.AZURE_WEBAPP_NAME }}-dev
	images: ${{ secrets.AZURE_CONTAINER_REGISTRY }}/prodsegmenter-frontend:${{ github.sha }}

	- name: Run smoke tests
	run: \|
	# Wait for deployment to be ready
	sleep 60

	# Test function app health
	curl -f https://${{ env.AZURE_FUNCTIONAPP_NAME }}-dev.azurewebsites.net/api/health

	# Test web app health
	curl -f https://${{ env.AZURE_WEBAPP_NAME }}-dev.azurewebsites.net

	# Deploy to Production Environment
	deploy-prod:
	runs-on: ubuntu-latest
	needs: [build-images, deploy-dev]
	if: github.ref == 'refs/heads/main'
	environment: production

	steps:
	- uses: actions/checkout@v3

	- name: Azure Login
	uses: azure/login@v1
	with:
	creds: ${{ secrets.AZURE_CREDENTIALS }}

	- name: Deploy Azure Function (Prod)
	uses: Azure/functions-action@v1
	with:
	app-name: ${{ env.AZURE_FUNCTIONAPP_NAME }}
	package: './deployment/azure_function'
	respect-funcignore: true

	- name: Deploy Streamlit App (Prod)
	uses: azure/webapps-deploy@v2
	with:
	app-name: ${{ env.AZURE_WEBAPP_NAME }}
	images: ${{ secrets.AZURE_CONTAINER_REGISTRY }}/prodsegmenter-frontend:${{ github.sha }}

	- name: Run production smoke tests
	run: \|
	# Wait for deployment to be ready
	sleep 60

	# Test function app health
	curl -f https://${{ env.AZURE_FUNCTIONAPP_NAME }}.azurewebsites.net/api/health

	# Test web app health
	curl -f https://${{ env.AZURE_WEBAPP_NAME }}.azurewebsites.net

	- name: Create GitHub Release
	if: success()
	uses: actions/create-release@v1
	env:
	GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}
	with:
	tag_name: v${{ github.run_number }}
	release_name: Release v${{ github.run_number }}
	body: \|
	Automated release for commit ${{ github.sha }}

	Changes in this release:
	- See commit history for details

	Deployment:
	- Azure Function: ${{ env.AZURE_FUNCTIONAPP_NAME }}
	- Streamlit App: ${{ env.AZURE_WEBAPP_NAME }}
	draft: false
	prerelease: false

	# Model Training Job (Triggered separately)
	train-model:
	runs-on: ubuntu-latest
	if: github.event_name == 'workflow_dispatch'
	environment: production

	steps:
	- uses: actions/checkout@v3

	- name: Azure Login
	uses: azure/login@v1
	with:
	creds: ${{ secrets.AZURE_CREDENTIALS }}

	- name: Set up Python
	uses: actions/setup-python@v4
	with:
	python-version: ${{ env.PYTHON_VERSION }}

	- name: Install Azure ML CLI
	run: \|
	az extension add -n ml -y
	az extension update -n ml

	- name: Submit training job
	run: \|
	az ml job create --file .azure/training-job.yml \
	--workspace-name ml-prodsegmenter \
	--resource-group rg-prodsegmenter

	- name: Monitor training job
	run: \|
	# Get job name from submission
	JOB_NAME=$(az ml job list --workspace-name ml-prodsegmenter \
	--resource-group rg-prodsegmenter \
	--query "[0].name" -o tsv)

	# Wait for completion (max 4 hours)
	az ml job show --name $JOB_NAME \
	--workspace-name ml-prodsegmenter \
	--resource-group rg-prodsegmenter \
	--query "status"

	# Performance Testing
	performance-test:
	runs-on: ubuntu-latest
	needs: deploy-prod
	if: github.ref == 'refs/heads/main'

	steps:
	- uses: actions/checkout@v3

	- name: Set up Python
	uses: actions/setup-python@v4
	with:
	python-version: ${{ env.PYTHON_VERSION }}

	- name: Install load testing tools
	run: \|
	pip install locust requests

	- name: Run performance tests
	run: \|
	cd tests/performance
	locust -f load_test.py \
	--host https://${{ env.AZURE_FUNCTIONAPP_NAME }}.azurewebsites.net \
	--users 50 \
	--spawn-rate 5 \
	--run-time 300s \
	--headless \
	--html performance-report.html

	- name: Upload performance report
	uses: actions/upload-artifact@v3
	with:
	name: performance-report
	path: tests/performance/performance-report.html

	# Cleanup
	cleanup:
	runs-on: ubuntu-latest
	needs: [deploy-prod, performance-test]
	if: always()

	steps:
	- name: Clean up old container images
	uses: azure/login@v1
	with:
	creds: ${{ secrets.AZURE_CREDENTIALS }}

	- name: Delete old images from ACR
	run: \|
	# Keep only last 10 images
	az acr repository show-manifests \
	--name ${{ secrets.AZURE_CONTAINER_REGISTRY }} \
	--repository prodsegmenter-api \
	--orderby time_desc \
	--query "[10:].digest" -o tsv \| \
	xargs -I {} az acr repository delete \
	--name ${{ secrets.AZURE_CONTAINER_REGISTRY }} \
	--image prodsegmenter-api@{} --yes

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Task 1 Fully Complete #2

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Task 1 Fully Complete #2

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