CI/CD Pipelines

# AI-Optimized GitHub Actions Pipeline
# .github/workflows/mcpcodex-deploy.yml

name: MCPCodex AI Deploy Pipeline

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

env:
  REGISTRY: ghcr.io
  IMAGE_NAME: ${{ github.repository }}
  AI_MODEL: claude-3-opus

jobs:
  # AI: Code quality and security analysis
  analyze:
    name: AI Code Analysis
    runs-on: ubuntu-latest
    steps:
      - name: Checkout code
        uses: actions/checkout@v4
        with:
          fetch-depth: 0

      - name: Setup MCPCodex CLI
        run: |
          npm install -g @mcpcodex/cli
          mcpcodex auth login --token ${{ secrets.MCPCODEX_TOKEN }}

      - name: AI Code Review
        run: |
          mcpcodex analyze code \
            --model ${{ env.AI_MODEL }} \
            --format github-actions \
            --severity critical
        env:
          GITHUB_TOKEN: ${{ secrets.GITHUB_TOKEN }}

      - name: Security Scan
        run: |
          mcpcodex scan security \
            --secrets --vulnerabilities \
            --compliance-check \
            --fail-on-critical

      - name: Performance Analysis
        run: |
          mcpcodex analyze performance \
            --predict-load \
            --optimization-suggestions

  # AI: Intelligent testing strategy
  test:
    name: AI-Driven Testing
    runs-on: ubuntu-latest
    needs: analyze
    strategy:
      matrix:
        node-version: [18, 20]
    steps:
      - uses: actions/checkout@v4
      
      - name: Setup Node.js
        uses: actions/setup-node@v4
        with:
          node-version: ${{ matrix.node-version }}
          cache: 'npm'

      - name: Install dependencies
        run: npm ci

      - name: AI Test Generation
        run: |
          mcpcodex generate tests \
            --coverage-target 90% \
            --include-edge-cases \
            --model ${{ env.AI_MODEL }}

      - name: Run Tests
        run: |
          npm run test:ci
          mcpcodex test analyze --upload-results

      - name: E2E Testing with AI
        run: |
          mcpcodex test e2e \
            --ai-scenarios \
            --adaptive-waiting \
            --visual-regression

  # AI: Optimized build process
  build:
    name: AI-Optimized Build
    runs-on: ubuntu-latest
    needs: [analyze, test]
    outputs:
      image-digest: ${{ steps.build.outputs.digest }}
    steps:
      - uses: actions/checkout@v4

      - name: Setup Docker Buildx
        uses: docker/setup-buildx-action@v3

      - name: Login to Container Registry
        uses: docker/login-action@v3
        with:
          registry: ${{ env.REGISTRY }}
          username: ${{ github.actor }}
          password: ${{ secrets.GITHUB_TOKEN }}

      - name: AI Build Optimization
        run: |
          mcpcodex docker optimize \
            --dockerfile Dockerfile \
            --target-size minimal \
            --cache-strategy aggressive

      - name: Build and Push
        id: build
        uses: docker/build-push-action@v5
        with:
          context: .
          push: true
          tags: |
            ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:latest
            ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}:${{ github.sha }}
          cache-from: type=gha
          cache-to: type=gha,mode=max
          platforms: linux/amd64,linux/arm64

  # AI: Intelligent deployment
  deploy:
    name: AI-Powered Deployment
    runs-on: ubuntu-latest
    needs: build
    environment: production
    steps:
      - uses: actions/checkout@v4

      - name: Setup Kubernetes
        uses: azure/setup-kubectl@v3

      - name: Configure AWS credentials
        uses: aws-actions/configure-aws-credentials@v4
        with:
          aws-access-key-id: ${{ secrets.AWS_ACCESS_KEY_ID }}
          aws-secret-access-key: ${{ secrets.AWS_SECRET_ACCESS_KEY }}
          aws-region: us-west-2

      - name: AI Deployment Strategy
        run: |
          mcpcodex deploy analyze \
            --environment production \
            --strategy auto-select \
            --risk-assessment

      - name: Deploy to Kubernetes
        run: |
          mcpcodex k8s deploy \
            --image ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}@${{ needs.build.outputs.image-digest }} \
            --namespace production \
            --strategy blue-green \
            --health-check-timeout 300s \
            --rollback-on-failure

      - name: Post-Deployment Validation
        run: |
          mcpcodex validate deployment \
            --load-test \
            --security-check \
            --performance-benchmark

# AI-Optimized GitLab CI/CD Pipeline
# .gitlab-ci.yml

stages:
  - analyze
  - test
  - build
  - deploy

variables:
  DOCKER_DRIVER: overlay2
  REGISTRY: $CI_REGISTRY
  IMAGE_NAME: $CI_PROJECT_PATH
  AI_MODEL: claude-3-opus

# AI: Code analysis and security
analyze:code:
  stage: analyze
  image: node:20-alpine
  script:
    - npm install -g @mcpcodex/cli
    - mcpcodex auth login --token $MCPCODEX_TOKEN
    - mcpcodex analyze code --model $AI_MODEL --format gitlab
    - mcpcodex scan security --fail-on-critical
  artifacts:
    reports:
      codequality: gl-code-quality-report.json
      sast: gl-sast-report.json
  rules:
    - if: $CI_PIPELINE_SOURCE == "push"

# AI: Dynamic test generation
test:ai-driven:
  stage: test
  image: node:20-alpine
  services:
    - postgres:15
    - redis:7
  script:
    - npm ci
    - mcpcodex generate tests --coverage-target 90%
    - npm run test:coverage
    - mcpcodex test analyze --upload-results
  coverage: '/Coverage: \d+\.\d+%/'
  artifacts:
    reports:
      coverage_report:
        coverage_format: cobertura
        path: coverage/cobertura-coverage.xml
      junit: junit.xml

# AI: Container optimization
build:optimized:
  stage: build
  image: docker:24-dind
  services:
    - docker:24-dind
  before_script:
    - echo $CI_REGISTRY_PASSWORD | docker login -u $CI_REGISTRY_USER --password-stdin $CI_REGISTRY
  script:
    - mcpcodex docker optimize --dockerfile Dockerfile
    - docker build -t $REGISTRY/$IMAGE_NAME:$CI_COMMIT_SHA .
    - docker build -t $REGISTRY/$IMAGE_NAME:latest .
    - docker push $REGISTRY/$IMAGE_NAME:$CI_COMMIT_SHA
    - docker push $REGISTRY/$IMAGE_NAME:latest
  rules:
    - if: $CI_COMMIT_BRANCH == "main"

# AI: Blue-green deployment
deploy:production:
  stage: deploy
  image: alpine/k8s:latest
  environment:
    name: production
    url: https://api.mcpcodex.com
  script:
    - mcpcodex k8s deploy 
        --image $REGISTRY/$IMAGE_NAME:$CI_COMMIT_SHA 
        --namespace production 
        --strategy blue-green
        --ai-validation
  rules:
    - if: $CI_COMMIT_BRANCH == "main"
      when: manual

// AI-Optimized Jenkins Pipeline
// Jenkinsfile

pipeline {
    agent {
        kubernetes {
            yaml '''
                apiVersion: v1
                kind: Pod
                spec:
                  containers:
                  - name: mcpcodex
                    image: mcpcodex/agent:latest
                    command:
                    - sleep
                    args:
                    - 99d
                  - name: docker
                    image: docker:dind
                    securityContext:
                      privileged: true
            '''
        }
    }

    environment {
        REGISTRY = 'ghcr.io'
        IMAGE_NAME = "${env.JOB_NAME}"
        AI_MODEL = 'claude-3-opus'
        MCPCODEX_TOKEN = credentials('mcpcodex-token')
    }

    stages {
        stage('AI Code Analysis') {
            steps {
                container('mcpcodex') {
                    sh '''
                        mcpcodex auth login --token $MCPCODEX_TOKEN
                        mcpcodex analyze code --model $AI_MODEL --format jenkins
                        mcpcodex scan security --fail-on-critical
                    '''
                }
            }
            post {
                always {
                    publishHTML([
                        allowMissing: false,
                        alwaysLinkToLastBuild: true,
                        keepAll: true,
                        reportDir: 'reports',
                        reportFiles: 'code-analysis.html',
                        reportName: 'AI Code Analysis Report'
                    ])
                }
            }
        }

        stage('AI Test Generation & Execution') {
            parallel {
                stage('Unit Tests') {
                    steps {
                        container('mcpcodex') {
                            sh '''
                                mcpcodex generate tests --type unit --coverage-target 85%
                                npm run test:unit
                            '''
                        }
                    }
                }
                stage('Integration Tests') {
                    steps {
                        container('mcpcodex') {
                            sh '''
                                mcpcodex generate tests --type integration --ai-scenarios
                                npm run test:integration
                            '''
                        }
                    }
                }
            }
            post {
                always {
                    junit 'test-results.xml'
                    publishCoverage adapters: [
                        istanbulCoberturaAdapter('coverage/cobertura-coverage.xml')
                    ]
                }
            }
        }

        stage('AI-Optimized Build') {
            when {
                branch 'main'
            }
            steps {
                container('docker') {
                    sh '''
                        mcpcodex docker optimize --dockerfile Dockerfile
                        docker build -t $REGISTRY/$IMAGE_NAME:$BUILD_NUMBER .
                        docker build -t $REGISTRY/$IMAGE_NAME:latest .
                    '''
                }
            }
        }

        stage('AI Security Scan') {
            steps {
                container('mcpcodex') {
                    sh '''
                        mcpcodex docker scan $REGISTRY/$IMAGE_NAME:$BUILD_NUMBER
                        mcpcodex compliance check --standard sox pci gdpr
                    '''
                }
            }
        }

        stage('AI Deployment') {
            when {
                branch 'main'
            }
            steps {
                container('mcpcodex') {
                    input message: 'Deploy to production?', ok: 'Deploy'
                    sh '''
                        mcpcodex deploy analyze --environment production
                        mcpcodex k8s deploy 
                            --image $REGISTRY/$IMAGE_NAME:$BUILD_NUMBER 
                            --namespace production 
                            --strategy canary 
                            --ai-monitoring
                    '''
                }
            }
        }
    }

    post {
        success {
            container('mcpcodex') {
                sh 'mcpcodex notify success --channel slack --webhook $SLACK_WEBHOOK'
            }
        }
        failure {
            container('mcpcodex') {
                sh 'mcpcodex notify failure --channel slack --webhook $SLACK_WEBHOOK --include-logs'
            }
        }
    }
}