CI/CD Pipeline

This document outlines the Continuous Integration and Continuous Deployment (CI/CD) pipeline for the AI Agent Orchestration Platform.

Overview

The CI/CD pipeline automates the testing, building, and deployment of the platform, ensuring consistent quality and rapid delivery of new features. The pipeline is designed to support the development workflow from code commit to production deployment.

Pipeline Architecture

The CI/CD pipeline consists of several stages:

1. Code Commit: Developer pushes code to the repository
2. Code Quality: Static analysis and linting
3. Build: Compile code and build container images
4. Test: Run unit, integration, and end-to-end tests
5. Security Scan: Check for vulnerabilities
6. Artifact Storage: Store container images and other artifacts
7. Deployment: Deploy to target environment
8. Verification: Verify deployment success
9. Notification: Notify team of pipeline status

Note: This is a placeholder for a CI/CD pipeline diagram. The actual diagram should be created and added to the project.

GitHub Actions Implementation

The platform uses GitHub Actions as the primary CI/CD tool. The workflow configurations are stored in .github/workflows/.

Main Workflow

The main workflow (main.yml) runs on pushes to the main branch and pull requests:

name: CI/CD Pipeline

on:
  push:
    branches: [ main ]
  pull_request:
    branches: [ main ]

jobs:
  lint:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Set up Python
        uses: actions/setup-python@v4
        with:
          python-version: '3.11'
      - name: Install dependencies
        run: |
          python -m pip install --upgrade pip
          pip install flake8 black isort
          pip install -r requirements.txt
      - name: Lint with flake8
        run: flake8 .
      - name: Check formatting with black
        run: black --check .
      - name: Check imports with isort
        run: isort --check .

  test:
    needs: lint
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Set up Python
        uses: actions/setup-python@v4
        with:
          python-version: '3.11'
      - name: Install dependencies
        run: |
          python -m pip install --upgrade pip
          pip install -r requirements.txt
          pip install pytest pytest-cov
      - name: Test with pytest
        run: pytest --cov=./ --cov-report=xml
      - name: Upload coverage to Codecov
        uses: codecov/codecov-action@v3
        with:
          file: ./coverage.xml
          fail_ci_if_error: true

  build:
    needs: test
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Set up Docker Buildx
        uses: docker/setup-buildx-action@v2
      - name: Login to DockerHub
        if: github.event_name != 'pull_request'
        uses: docker/login-action@v2
        with:
          username: ${{ secrets.DOCKERHUB_USERNAME }}
          password: ${{ secrets.DOCKERHUB_TOKEN }}
      - name: Build and push backend
        uses: docker/build-push-action@v4
        with:
          context: ./backend
          push: ${{ github.event_name != 'pull_request' }}
          tags: metaagent/backend:latest,metaagent/backend:${{ github.sha }}
      - name: Build and push frontend
        uses: docker/build-push-action@v4
        with:
          context: ./frontend
          push: ${{ github.event_name != 'pull_request' }}
          tags: metaagent/frontend:latest,metaagent/frontend:${{ github.sha }}

  deploy-staging:
    if: github.event_name == 'push' && github.ref == 'refs/heads/main'
    needs: build
    runs-on: ubuntu-latest
    environment: staging
    steps:
      - uses: actions/checkout@v3
      - name: Install kubectl
        uses: azure/setup-kubectl@v3
      - name: Set Kubernetes context
        uses: azure/k8s-set-context@v3
        with:
          kubeconfig: ${{ secrets.KUBE_CONFIG }}
      - name: Deploy to staging
        run: |
          ./infra/scripts/deploy.sh staging ${{ github.sha }}
      - name: Verify deployment
        run: |
          ./infra/scripts/verify_deployment.sh staging

Release Workflow

The release workflow (release.yml) runs when a new release is created:

name: Release Pipeline

on:
  release:
    types: [published]

jobs:
  build-release:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v3
      - name: Set up Docker Buildx
        uses: docker/setup-buildx-action@v2
      - name: Login to DockerHub
        uses: docker/login-action@v2
        with:
          username: ${{ secrets.DOCKERHUB_USERNAME }}
          password: ${{ secrets.DOCKERHUB_TOKEN }}
      - name: Extract version
        id: version
        run: echo "VERSION=${GITHUB_REF#refs/tags/v}" >> $GITHUB_OUTPUT
      - name: Build and push backend
        uses: docker/build-push-action@v4
        with:
          context: ./backend
          push: true
          tags: metaagent/backend:${{ steps.version.outputs.VERSION }}
      - name: Build and push frontend
        uses: docker/build-push-action@v4
        with:
          context: ./frontend
          push: true
          tags: metaagent/frontend:${{ steps.version.outputs.VERSION }}

  deploy-production:
    needs: build-release
    runs-on: ubuntu-latest
    environment: production
    steps:
      - uses: actions/checkout@v3
      - name: Install kubectl
        uses: azure/setup-kubectl@v3
      - name: Set Kubernetes context
        uses: azure/k8s-set-context@v3
        with:
          kubeconfig: ${{ secrets.KUBE_CONFIG_PROD }}
      - name: Extract version
        id: version
        run: echo "VERSION=${GITHUB_REF#refs/tags/v}" >> $GITHUB_OUTPUT
      - name: Deploy to production
        run: |
          ./infra/scripts/deploy.sh production ${{ steps.version.outputs.VERSION }}
      - name: Verify deployment
        run: |
          ./infra/scripts/verify_deployment.sh production
      - name: Create deployment record
        uses: chrnorm/deployment-action@v2
        with:
          token: ${{ secrets.GITHUB_TOKEN }}
          environment: production
          initial-status: success
          ref: ${{ github.ref }}

Alternative CI/CD Tools

While GitHub Actions is the primary CI/CD tool, the platform can also be integrated with:

• Jenkins: For on-premises deployments
• GitLab CI: For GitLab-hosted repositories
• Azure DevOps: For Microsoft-centric environments
• CircleCI: For additional cloud-based CI/CD

Pipeline Scripts

Key pipeline scripts are located in /infra/scripts/:

• deploy.sh - Deploy to target environment
• verify_deployment.sh - Verify deployment success
• rollback.sh - Rollback failed deployment
• run_tests.sh - Run test suite
• build_images.sh - Build container images

Example verification script:

#!/bin/bash
# verify_deployment.sh - Verify deployment success

ENV=$1

if [ -z "$ENV" ]; then
  echo "Usage: ./verify_deployment.sh [environment]"
  echo "Example: ./verify_deployment.sh staging"
  exit 1
fi

echo "Verifying deployment in $ENV environment..."

# Check if pods are running
kubectl get pods -n meta-agent-$ENV | grep -v Running > /dev/null
if [ $? -eq 0 ]; then
  echo "Error: Not all pods are running"
  kubectl get pods -n meta-agent-$ENV
  exit 1
fi

# Check API health
API_URL=$(kubectl get ingress -n meta-agent-$ENV -o jsonpath='{.items[0].spec.rules[0].host}')
curl -f https://$API_URL/health > /dev/null
if [ $? -ne 0 ]; then
  echo "Error: API health check failed"
  exit 1
fi

echo "Deployment verification successful!"
exit 0

GitOps Approach

For Kubernetes deployments, the platform uses a GitOps approach:

1. Infrastructure and application configurations are stored in Git
2. Changes to configurations trigger the CI/CD pipeline
3. The pipeline applies changes to the target environment
4. Tools like ArgoCD or Flux monitor the Git repository for changes
5. Changes are automatically applied to the cluster

Environments

The CI/CD pipeline supports multiple environments:

• Development: For feature development and testing
• Staging: For pre-production validation
• Production: For live deployment
• Edge: For edge device deployments
• Federated: For federated collaboration deployments

Testing Strategy

The pipeline includes comprehensive testing:

• Unit Tests: Test individual components
• Integration Tests: Test component interactions
• End-to-End Tests: Test complete workflows
• Performance Tests: Test system performance
• Security Tests: Test for vulnerabilities

Security Considerations

The CI/CD pipeline includes security measures:

• Secret Management: Secrets are stored securely in GitHub Secrets
• Vulnerability Scanning: Container images are scanned for vulnerabilities
• SAST: Static Application Security Testing
• DAST: Dynamic Application Security Testing
• Dependency Scanning: Check for vulnerable dependencies

Monitoring and Notifications

The pipeline includes monitoring and notifications:

• Slack Integration: Notify team of pipeline status
• Email Notifications: Send emails for critical events
• Dashboard: Visual representation of pipeline status
• Metrics: Track pipeline performance and success rate

Best Practices

• Use infrastructure as code for all environments
• Implement comprehensive testing
• Automate everything
• Use feature flags for controlled rollouts
• Implement canary deployments for risk mitigation
• Monitor deployments for issues
• Have automated rollback procedures
• Keep pipeline configurations in version control
• Use consistent environments across the pipeline

References

• Deployment Infrastructure
• Containerization
• Monitoring Infrastructure
• Security Infrastructure

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Last updated: 2025-04-18