package gitops

import (
    "context"
    "sync"
    "time"
    "github.com/prometheus/client_golang/prometheus"
    "github.com/opentracing/opentracing-go"
)

// Enterprise GitOps orchestrator with multi-tenant support
type GitOpsOrchestrator struct {
    // Core components
    agents           map[string]*AIAgent
    repositories     map[string]*Repository
    releaseManager   *ReleaseManager
    
    // Enterprise features
    tenantManager    *TenantManager
    complianceEngine *ComplianceEngine
    auditTrail       *AuditTrail
    
    // AI capabilities
    documentationAI  *DocumentationAI
    analysisAI       *AnalysisAI
    deploymentAI     *DeploymentAI
    
    // Performance optimization
    cacheLayer       *CacheLayer
    loadBalancer     *LoadBalancer
    
    // Monitoring
    metrics          *GitOpsMetrics
    tracer           opentracing.Tracer
    
    // Concurrency control
    mu               sync.RWMutex
    shutdown         chan struct{}
}

type GitOpsMetrics struct {
    ReleasesProcessed    prometheus.Counter
    DocumentationGenerated prometheus.Counter
    ComplianceChecks     prometheus.Counter
    AnalysisLatency      prometheus.Histogram
    DeploymentSuccess    prometheus.Gauge
    ErrorRate            prometheus.Gauge
}

func NewGitOpsOrchestrator(config *EnterpriseConfig) *GitOpsOrchestrator {
    orchestrator := &GitOpsOrchestrator{
        agents:           make(map[string]*AIAgent),
        repositories:     make(map[string]*Repository),
        releaseManager:   NewReleaseManager(config.Release),
        tenantManager:    NewTenantManager(config.MultiTenant),
        complianceEngine: NewComplianceEngine(config.Compliance),
        auditTrail:       NewAuditTrail(config.Audit),
        documentationAI:  NewDocumentationAI(config.AI.Documentation),
        analysisAI:       NewAnalysisAI(config.AI.Analysis),
        deploymentAI:     NewDeploymentAI(config.AI.Deployment),
        cacheLayer:       NewCacheLayer(config.Cache),
        loadBalancer:     NewLoadBalancer(config.LoadBalancing),
        metrics:          NewGitOpsMetrics(),
        tracer:           NewTracer(config.Tracing),
        shutdown:         make(chan struct{}),
    }
    
    // Start background services
    go orchestrator.complianceMonitoring()
    go orchestrator.performanceOptimization()
    go orchestrator.healthChecking()
    
    return orchestrator
}

// Enterprise AI agent with sophisticated reasoning capabilities
type EnterpriseAIAgent struct {
    // Core AI capabilities
    llmProvider      *LLMProvider
    reasoning        *ReasoningEngine
    memorySystem     *MemorySystem
    
    // Specialized knowledge
    domainKnowledge  *DomainKnowledge
    codebaseContext  *CodebaseContext
    
    // Enterprise features
    securityPolicy   *SecurityPolicy
    complianceRules  *ComplianceRules
    auditLogger      *AuditLogger
    
    // Performance optimization
    cache            *AgentCache
    rateLimiter      *RateLimiter
    circuitBreaker   *CircuitBreaker
    
    // Observability
    metrics          *AgentMetrics
    logger           *StructuredLogger
    tracer           *AgentTracer
}

type AIWorkflow struct {
    // Workflow definition
    nodes            []WorkflowNode
    dependencies     map[string][]string
    
    // Execution context
    state            *WorkflowState
    executor         *WorkflowExecutor
    
    // Enterprise features
    checkpoints      *CheckpointManager
    rollback         *RollbackManager
    monitoring       *WorkflowMonitoring
}

func (a *EnterpriseAIAgent) ExecuteWorkflow(ctx context.Context, workflow *AIWorkflow) (*WorkflowResult, error) {
    // Start distributed tracing
    span := a.tracer.StartSpan(ctx, "agent.execute_workflow")
    defer span.Finish()
    
    // Security validation
    if err := a.validateSecurity(ctx, workflow); err \!= nil {
        return nil, err
    }
    
    // Compliance checks
    if err := a.validateCompliance(ctx, workflow); err \!= nil {
        return nil, err
    }
    
    // Execute with circuit breaker protection
    result, err := a.circuitBreaker.Execute(func() (interface{}, error) {
        return a.executeWorkflowInternal(ctx, workflow)
    })
    
    if err \!= nil {
        a.metrics.RecordError(err)
        return nil, err
    }
    
    workflowResult := result.(*WorkflowResult)
    a.metrics.RecordSuccess()
    
    // Audit logging
    a.auditLogger.LogWorkflowExecution(ctx, workflow, workflowResult)
    
    return workflowResult, nil
}

// Advanced release manager with AI-powered analysis
type EnterpriseReleaseManager struct {
    // Core components
    versionManager   *VersionManager
    changeAnalyzer   *ChangeAnalyzer
    riskAssessment   *RiskAssessment
    
    // AI components
    impactAnalysis   *ImpactAnalysisAI
    documentation    *DocumentationAI
    testGeneration   *TestGenerationAI
    
    // Enterprise features
    approvalWorkflow *ApprovalWorkflow
    rollbackSystem   *RollbackSystem
    complianceCheck  *ComplianceCheck
    
    // Integration
    cicdIntegration  *CICDIntegration
    notificationHub  *NotificationHub
    
    // Storage
    releaseDatabase  *ReleaseDatabase
    artifactStore    *ArtifactStore
}

type ReleaseContext struct {
    // Release metadata
    Version          string
    TargetEnvironment string
    Commits          []*CommitInfo
    Dependencies     []*Dependency
    
    // Analysis results
    ImpactAnalysis   *ImpactAnalysis
    RiskAssessment   *RiskAssessment
    TestSuite        *TestSuite
    
    // Documentation
    ReleaseNotes     *ReleaseNotes
    ChangeLog        *ChangeLog
    RunBook          *RunBook
    
    // Compliance
    ComplianceReport *ComplianceReport
    SecurityScan     *SecurityScan
    AuditTrail       *AuditTrail
}

func (rm *EnterpriseReleaseManager) ProcessRelease(ctx context.Context, request *ReleaseRequest) (*ReleaseContext, error) {
    // Initialize release context
    releaseCtx := &ReleaseContext{
        Version:           request.Version,
        TargetEnvironment: request.Environment,
    }
    
    // Multi-stage processing pipeline
    stages := []ReleaseStage{
        rm.commitAnalysisStage,
        rm.impactAnalysisStage,
        rm.documentationGenerationStage,
        rm.testGenerationStage,
        rm.complianceValidationStage,
        rm.approvalWorkflowStage,
    }
    
    for _, stage := range stages {
        if err := stage.Execute(ctx, releaseCtx); err \!= nil {
            return nil, fmt.Errorf("release stage failed: %w", err)
        }
    }
    
    // Store release context
    if err := rm.releaseDatabase.Store(ctx, releaseCtx); err \!= nil {
        return nil, err
    }
    
    return releaseCtx, nil
}

# enterprise_commit_analyzer.py
"""Enterprise-grade commit analysis with advanced AI capabilities."""

import asyncio
import logging
import re
from dataclasses import dataclass
from typing import List, Dict, Optional, Tuple
from enum import Enum

import pandas as pd
from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.cluster import KMeans
from transformers import pipeline, AutoTokenizer, AutoModel
import torch

class ChangeType(Enum):
    FEATURE = "feature"
    BUGFIX = "bugfix" 
    REFACTOR = "refactor"
    DOCS = "docs"
    SECURITY = "security"
    PERFORMANCE = "performance"
    BREAKING = "breaking"
    DEPENDENCY = "dependency"

class ImpactLevel(Enum):
    CRITICAL = "critical"
    HIGH = "high"
    MEDIUM = "medium"
    LOW = "low"
    MINIMAL = "minimal"

@dataclass
class CommitAnalysis:
    """Comprehensive commit analysis results."""
    commit_hash: str
    message: str
    author: str
    timestamp: str
    
    # AI-generated insights
    change_type: ChangeType
    impact_level: ImpactLevel
    user_facing_changes: List[str]
    technical_changes: List[str]
    breaking_changes: List[str]
    
    # Advanced analysis
    semantic_similarity: float
    code_complexity_change: float
    test_coverage_impact: float
    security_implications: List[str]
    
    # Enterprise features
    compliance_impact: List[str]
    rollback_complexity: float
    deployment_risk: float

class EnterpriseCommitAnalyzer:
    """Enterprise-grade commit analyzer with ML capabilities."""
    
    def __init__(self, config: Dict):
        self.config = config
        
        # Initialize AI models
        self.semantic_model = AutoModel.from_pretrained(
            config.get('semantic_model', 'microsoft/codebert-base')
        )
        self.tokenizer = AutoTokenizer.from_pretrained(
            config.get('semantic_model', 'microsoft/codebert-base')
        )
        
        # Classification pipeline
        self.classifier = pipeline(
            "text-classification",
            model=config.get('classification_model', 'microsoft/DialoGPT-medium')
        )
        
        # Security analysis
        self.security_analyzer = pipeline(
            "text-classification",
            model=config.get('security_model', 'huggingface/CodeBERTa-small-v1')
        )
        
        # Similarity analyzer
        self.vectorizer = TfidfVectorizer(
            max_features=1000,
            stop_words='english',
            ngram_range=(1, 3)
        )
        
        # Clustering for pattern recognition
        self.clusterer = KMeans(n_clusters=8, random_state=42)
        
        # Enterprise features
        self.compliance_rules = self._load_compliance_rules()
        self.security_patterns = self._load_security_patterns()
        
    async def analyze_commits(self, commits: List[Dict]) -> List[CommitAnalysis]:
        """Analyze multiple commits with enterprise features."""
        analyses = []
        
        # Batch processing for efficiency
        batch_size = self.config.get('batch_size', 32)
        for i in range(0, len(commits), batch_size):
            batch = commits[i:i + batch_size]
            batch_analyses = await self._analyze_commit_batch(batch)
            analyses.extend(batch_analyses)
        
        # Post-processing analysis
        analyses = await self._enhance_with_cross_commit_analysis(analyses)
        
        return analyses
    
    async def _analyze_commit_batch(self, commits: List[Dict]) -> List[CommitAnalysis]:
        """Analyze a batch of commits."""
        analyses = []
        
        for commit in commits:
            analysis = await self._analyze_single_commit(commit)
            analyses.append(analysis)
        
        return analyses
    
    async def _analyze_single_commit(self, commit: Dict) -> CommitAnalysis:
        """Comprehensive analysis of a single commit."""
        
        # Extract basic information
        commit_hash = commit['hash']
        message = commit['message']
        author = commit['author']
        timestamp = commit['timestamp']
        
        # AI-powered classification
        change_type = await self._classify_change_type(commit)
        impact_level = await self._assess_impact_level(commit)
        
        # Content analysis
        user_facing_changes = await self._extract_user_facing_changes(commit)
        technical_changes = await self._extract_technical_changes(commit)
        breaking_changes = await self._detect_breaking_changes(commit)
        
        # Advanced metrics
        semantic_similarity = await self._calculate_semantic_similarity(commit)
        complexity_change = await self._analyze_complexity_change(commit)
        coverage_impact = await self._assess_test_coverage_impact(commit)
        security_implications = await self._analyze_security_implications(commit)
        
        # Enterprise analysis
        compliance_impact = await self._assess_compliance_impact(commit)
        rollback_complexity = await self._assess_rollback_complexity(commit)
        deployment_risk = await self._assess_deployment_risk(commit)
        
        return CommitAnalysis(
            commit_hash=commit_hash,
            message=message,
            author=author,
            timestamp=timestamp,
            change_type=change_type,
            impact_level=impact_level,
            user_facing_changes=user_facing_changes,
            technical_changes=technical_changes,
            breaking_changes=breaking_changes,
            semantic_similarity=semantic_similarity,
            code_complexity_change=complexity_change,
            test_coverage_impact=coverage_impact,
            security_implications=security_implications,
            compliance_impact=compliance_impact,
            rollback_complexity=rollback_complexity,
            deployment_risk=deployment_risk
        )
    
    async def _classify_change_type(self, commit: Dict) -> ChangeType:
        """Classify the type of change using AI."""
        message = commit['message'].lower()
        diff = commit.get('diff', '')
        
        # Prepare input for classification
        classification_input = f"{message} {diff[:500]}"
        
        # Use ML model for classification
        result = self.classifier(classification_input)
        
        # Map to our change types
        type_mapping = {
            'LABEL_0': ChangeType.FEATURE,
            'LABEL_1': ChangeType.BUGFIX,
            'LABEL_2': ChangeType.REFACTOR,
            'LABEL_3': ChangeType.DOCS,
            'LABEL_4': ChangeType.SECURITY,
            'LABEL_5': ChangeType.PERFORMANCE,
            'LABEL_6': ChangeType.BREAKING,
            'LABEL_7': ChangeType.DEPENDENCY,
        }
        
        return type_mapping.get(result['label'], ChangeType.FEATURE)
    
    async def _assess_impact_level(self, commit: Dict) -> ImpactLevel:
        """Assess the impact level of changes."""
        factors = []
        
        # File count impact
        files_changed = len(commit.get('files', []))
        if files_changed > 50:
            factors.append('high_file_count')
        elif files_changed > 20:
            factors.append('medium_file_count')
        
        # Line count impact
        lines_changed = commit.get('additions', 0) + commit.get('deletions', 0)
        if lines_changed > 1000:
            factors.append('high_line_count')
        elif lines_changed > 200:
            factors.append('medium_line_count')
        
        # Critical file impact
        critical_files = [
            'package.json', 'requirements.txt', 'Dockerfile',
            'docker-compose.yml', 'kubernetes.yaml'
        ]
        if any(f in str(commit.get('files', [])) for f in critical_files):
            factors.append('critical_file_change')
        
        # Message keywords
        message = commit['message'].lower()
        if any(word in message for word in ['breaking', 'major', 'critical']):
            factors.append('breaking_keywords')
        
        # Calculate impact score
        impact_score = len(factors)
        
        if impact_score >= 3:
            return ImpactLevel.CRITICAL
        elif impact_score >= 2:
            return ImpactLevel.HIGH
        elif impact_score >= 1:
            return ImpactLevel.MEDIUM
        else:
            return ImpactLevel.LOW
    
    async def _detect_breaking_changes(self, commit: Dict) -> List[str]:
        """Detect potential breaking changes."""
        breaking_changes = []
        
        diff = commit.get('diff', '')
        message = commit['message']
        
        # API signature changes
        api_patterns = [
            r'def\s+\w+\([^)]*\)\s*->',  # Python function signatures
            r'function\s+\w+\([^)]*\)',   # JavaScript functions
            r'public\s+\w+\s+\w+\([^)]*\)', # Java/C# methods
        ]
        
        for pattern in api_patterns:
            if re.search(pattern, diff):
                breaking_changes.append("API signature change detected")
                break
        
        # Database schema changes
        if any(word in diff.lower() for word in ['alter table', 'drop table', 'drop column']):
            breaking_changes.append("Database schema change detected")
        
        # Configuration changes
        if any(word in diff.lower() for word in ['config', 'environment', 'settings']):
            breaking_changes.append("Configuration change detected")
        
        # Dependency version changes
        if 'requirements.txt' in str(commit.get('files', [])) or 'package.json' in str(commit.get('files', [])):
            breaking_changes.append("Dependency change detected")
        
        return breaking_changes

# enterprise_documentation_generator.py
"""Enterprise documentation generator with multi-format support."""

from typing import Dict, List, Optional
from dataclasses import dataclass
from enum import Enum
import jinja2
import markdown
import pdfkit
from weasyprint import HTML, CSS

class DocumentationType(Enum):
    RELEASE_NOTES = "release_notes"
    CHANGELOG = "changelog"
    API_DOCS = "api_docs"
    COMPLIANCE_REPORT = "compliance_report"
    SECURITY_BULLETIN = "security_bulletin"
    DEPLOYMENT_GUIDE = "deployment_guide"

class OutputFormat(Enum):
    MARKDOWN = "markdown"
    HTML = "html"
    PDF = "pdf"
    JSON = "json"
    CONFLUENCE = "confluence"
    JIRA = "jira"

@dataclass
class DocumentationConfig:
    """Configuration for documentation generation."""
    template_dir: str
    output_dir: str
    brand_assets: Dict[str, str]
    compliance_requirements: List[str]
    approval_workflow: Dict[str, str]

class EnterpriseDocumentationGenerator:
    """Enterprise-grade documentation generator."""
    
    def __init__(self, config: DocumentationConfig):
        self.config = config
        
        # Template engine setup
        self.jinja_env = jinja2.Environment(
            loader=jinja2.FileSystemLoader(config.template_dir),
            autoescape=jinja2.select_autoescape(['html', 'xml'])
        )
        
        # Custom filters
        self.jinja_env.filters['format_date'] = self._format_date
        self.jinja_env.filters['format_version'] = self._format_version
        self.jinja_env.filters['security_level'] = self._format_security_level
        
        # Output processors
        self.processors = {
            OutputFormat.MARKDOWN: self._process_markdown,
            OutputFormat.HTML: self._process_html,
            OutputFormat.PDF: self._process_pdf,
            OutputFormat.JSON: self._process_json,
            OutputFormat.CONFLUENCE: self._process_confluence,
            OutputFormat.JIRA: self._process_jira,
        }
    
    async def generate_documentation(
        self,
        doc_type: DocumentationType,
        data: Dict,
        formats: List[OutputFormat]
    ) -> Dict[str, str]:
        """Generate documentation in multiple formats."""
        
        results = {}
        
        # Load appropriate template
        template_name = f"{doc_type.value}.j2"
        template = self.jinja_env.get_template(template_name)
        
        # Enhance data with enterprise context
        enhanced_data = await self._enhance_data(data, doc_type)
        
        # Generate base content
        base_content = template.render(**enhanced_data)
        
        # Process for each requested format
        for format_type in formats:
            processor = self.processors[format_type]
            processed_content = await processor(base_content, enhanced_data)
            results[format_type.value] = processed_content
        
        return results
    
    async def _enhance_data(self, data: Dict, doc_type: DocumentationType) -> Dict:
        """Enhance data with enterprise context."""
        enhanced = data.copy()
        
        # Add branding
        enhanced['branding'] = self.config.brand_assets
        
        # Add timestamps
        enhanced['generated_at'] = self._get_timestamp()
        enhanced['generated_by'] = "Enterprise AI Documentation System"
        
        # Add compliance information
        if doc_type in [DocumentationType.RELEASE_NOTES, DocumentationType.COMPLIANCE_REPORT]:
            enhanced['compliance'] = await self._add_compliance_info(data)
        
        # Add security context
        if 'security' in str(doc_type.value):
            enhanced['security_context'] = await self._add_security_context(data)
        
        # Add approval workflow
        enhanced['approval_workflow'] = self.config.approval_workflow
        
        return enhanced
    
    async def _process_markdown(self, content: str, data: Dict) -> str:
        """Process content for Markdown output."""
        # Clean up template artifacts
        content = content.replace('  \n', '\n')
        content = re.sub(r'\n{3,}', '\n\n', content)
        
        return content
    
    async def _process_html(self, content: str, data: Dict) -> str:
        """Process content for HTML output."""
        # Convert markdown to HTML
        html_content = markdown.markdown(
            content,
            extensions=['tables', 'toc', 'codehilite', 'fenced_code']
        )
        
        # Apply enterprise styling
        html_template = self.jinja_env.get_template('html_wrapper.j2')
        return html_template.render(content=html_content, **data)
    
    async def _process_pdf(self, content: str, data: Dict) -> bytes:
        """Process content for PDF output."""
        # Convert to HTML first
        html_content = await self._process_html(content, data)
        
        # Generate PDF with enterprise styling
        css_path = f"{self.config.template_dir}/enterprise.css"
        pdf_bytes = HTML(string=html_content).write_pdf(
            stylesheets=[CSS(filename=css_path)]
        )
        
        return pdf_bytes

# .github/workflows/enterprise-gitops.yml
name: Enterprise GitOps Automation

on:
  push:
    branches: [main, develop, 'release/*']
  pull_request:
    branches: [main, develop]

env:
  ENTERPRISE_AI_ENDPOINT: ${{ secrets.ENTERPRISE_AI_ENDPOINT }}
  COMPLIANCE_WEBHOOK: ${{ secrets.COMPLIANCE_WEBHOOK }}
  SECURITY_SCAN_TOKEN: ${{ secrets.SECURITY_SCAN_TOKEN }}

jobs:
  ai-analysis:
    name: AI-Powered Commit Analysis
    runs-on: enterprise-runners
    timeout-minutes: 30
    
    outputs:
      impact-level: ${{ steps.analysis.outputs.impact-level }}
      breaking-changes: ${{ steps.analysis.outputs.breaking-changes }}
      security-implications: ${{ steps.analysis.outputs.security-implications }}
      
    steps:
      - name: Checkout Repository
        uses: actions/checkout@v4
        with:
          fetch-depth: 0
          token: ${{ secrets.ENTERPRISE_PAT }}
      
      - name: Setup Enterprise AI Environment
        uses: ./.github/actions/setup-ai-env
        with:
          python-version: '3.11'
          cache-dependencies: true
      
      - name: AI Commit Analysis
        id: analysis
        run:  < /dev/null | 
          python scripts/ai_analysis.py \
            --repo-path . \
            --base-ref ${{ github.event.before }} \
            --head-ref ${{ github.sha }} \
            --output-format github-actions
      
      - name: Security Implications Check
        if: contains(steps.analysis.outputs.security-implications, 'high')
        run: |
          echo "High security implications detected"
          python scripts/security_notification.py \
            --level high \
            --webhook ${{ env.COMPLIANCE_WEBHOOK }}
      
      - name: Upload Analysis Artifacts
        uses: actions/upload-artifact@v4
        with:
          name: ai-analysis-${{ github.sha }}
          path: |
            analysis-report.json
            security-report.json
            compliance-report.json

  documentation-generation:
    name: AI Documentation Generation
    runs-on: enterprise-runners
    needs: ai-analysis
    timeout-minutes: 20
    
    steps:
      - name: Checkout Repository
        uses: actions/checkout@v4
        with:
          fetch-depth: 0
      
      - name: Download Analysis Artifacts
        uses: actions/download-artifact@v4
        with:
          name: ai-analysis-${{ github.sha }}
      
      - name: Generate Release Notes
        run: |
          python scripts/generate_documentation.py \
            --analysis-file analysis-report.json \
            --doc-types release_notes,changelog,api_docs \
            --formats markdown,html,pdf \
            --output-dir docs/generated
      
      - name: Generate Compliance Documentation
        if: github.ref == 'refs/heads/main'
        run: |
          python scripts/generate_compliance_docs.py \
            --analysis-file analysis-report.json \
            --compliance-file compliance-report.json \
            --output-dir compliance/generated
      
      - name: Commit Generated Documentation
        if: github.ref == 'refs/heads/main'
        run: |
          git config --local user.email "ai-system@company.com"
          git config --local user.name "Enterprise AI System"
          git add docs/generated/ compliance/generated/
          git commit -m "docs: AI-generated documentation for ${{ github.sha }}" || exit 0
          git push

  enterprise-deployment:
    name: Enterprise Deployment Pipeline
    runs-on: enterprise-runners
    needs: [ai-analysis, documentation-generation]
    if: github.ref == 'refs/heads/main' && needs.ai-analysis.outputs.impact-level \!= 'critical'
    
    strategy:
      matrix:
        environment: [staging, production]
        
    steps:
      - name: Environment-Specific Deployment
        uses: ./.github/actions/enterprise-deploy
        with:
          environment: ${{ matrix.environment }}
          impact-level: ${{ needs.ai-analysis.outputs.impact-level }}
          breaking-changes: ${{ needs.ai-analysis.outputs.breaking-changes }}

#\!/bin/bash
# enterprise_deployment.sh - Production deployment with AI integration

set -euo pipefail

# Configuration
DEPLOYMENT_ENV="${1:-staging}"
IMPACT_LEVEL="${2:-medium}"
BREAKING_CHANGES="${3:-false}"

# Enterprise configuration
KUBERNETES_CLUSTER="enterprise-${DEPLOYMENT_ENV}"
NAMESPACE="gitops-automation"
AI_ENDPOINT="${ENTERPRISE_AI_ENDPOINT}"

deploy_ai_gitops_system() {
    echo "Deploying Enterprise AI GitOps System to ${DEPLOYMENT_ENV}"
    
    # Validate environment
    kubectl config use-context "${KUBERNETES_CLUSTER}"
    kubectl get namespace "${NAMESPACE}" || kubectl create namespace "${NAMESPACE}"
    
    # Deploy core components
    helm upgrade --install gitops-ai-system ./charts/gitops-ai \
        --namespace "${NAMESPACE}" \
        --set environment="${DEPLOYMENT_ENV}" \
        --set ai.endpoint="${AI_ENDPOINT}" \
        --set scaling.enabled=true \
        --set monitoring.enabled=true \
        --set compliance.enabled=true \
        --wait --timeout=10m
    
    # Deploy analysis workers
    kubectl apply -f manifests/analysis-workers.yaml
    
    # Deploy documentation generators
    kubectl apply -f manifests/documentation-generators.yaml
    
    # Setup monitoring
    kubectl apply -f manifests/monitoring.yaml
    
    echo "Deployment completed successfully"
}

configure_ai_models() {
    echo "Configuring AI models for ${DEPLOYMENT_ENV}"
    
    # Create model configuration
    kubectl create configmap ai-models-config \
        --from-file=configs/ai-models/ \
        --namespace="${NAMESPACE}" \
        --dry-run=client -o yaml | kubectl apply -f -
    
    # Setup model secrets
    kubectl create secret generic ai-model-credentials \
        --from-literal=openai-key="${OPENAI_API_KEY}" \
        --from-literal=anthropic-key="${ANTHROPIC_API_KEY}" \
        --from-literal=huggingface-token="${HUGGINGFACE_TOKEN}" \
        --namespace="${NAMESPACE}" \
        --dry-run=client -o yaml | kubectl apply -f -
    
    echo "AI model configuration completed"
}

setup_enterprise_monitoring() {
    echo "Setting up enterprise monitoring"
    
    # Deploy Prometheus for GitOps metrics
    helm upgrade --install gitops-prometheus prometheus-community/kube-prometheus-stack \
        --namespace monitoring \
        --create-namespace \
        --set grafana.adminPassword="${GRAFANA_PASSWORD}" \
        --set prometheus.prometheusSpec.retention=30d
    
    # Deploy custom dashboards
    kubectl apply -f manifests/monitoring/grafana-dashboards.yaml
    
    # Setup alerting rules
    kubectl apply -f manifests/monitoring/alert-rules.yaml
    
    echo "Monitoring setup completed"
}

validate_deployment() {
    echo "Validating deployment"
    
    # Health checks
    kubectl wait --for=condition=ready pod -l app=gitops-ai-system \
        --namespace="${NAMESPACE}" --timeout=300s
    
    # Functional tests
    kubectl run deployment-test \
        --image=enterprise/gitops-test:latest \
        --rm -it --restart=Never \
        --namespace="${NAMESPACE}" \
        -- /test-suite.sh
    
    echo "Deployment validation completed"
}

# Deployment based on impact level
case "${IMPACT_LEVEL}" in
    "critical")
        echo "Critical changes detected - manual approval required"
        exit 1
        ;;
    "high")
        echo "High impact changes - deploying with extra validation"
        deploy_ai_gitops_system
        configure_ai_models
        setup_enterprise_monitoring
        validate_deployment
        # Additional validation for high impact
        kubectl apply -f manifests/validation/high-impact-tests.yaml
        ;;
    *)
        echo "Standard deployment process"
        deploy_ai_gitops_system
        configure_ai_models
        setup_enterprise_monitoring
        validate_deployment
        ;;
esac

echo "Enterprise AI GitOps deployment completed for ${DEPLOYMENT_ENV}"

# enterprise_agent_orchestrator.py
"""Enterprise multi-agent orchestration system."""

import asyncio
import logging
from typing import Dict, List, Optional, Any
from dataclasses import dataclass
from enum import Enum
import networkx as nx
from concurrent.futures import ThreadPoolExecutor
from langchain.agents import AgentExecutor
from langchain.tools import BaseTool
from langchain.schema import AgentAction, AgentFinish

class AgentRole(Enum):
    ANALYZER = "analyzer"
    DOCUMENTER = "documenter"
    VALIDATOR = "validator"
    DEPLOYER = "deployer"
    MONITOR = "monitor"
    COMPLIANCE = "compliance"

class TaskPriority(Enum):
    CRITICAL = 1
    HIGH = 2
    MEDIUM = 3
    LOW = 4

@dataclass
class AgentTask:
    """Represents a task for an AI agent."""
    id: str
    role: AgentRole
    priority: TaskPriority
    input_data: Dict[str, Any]
    dependencies: List[str]
    timeout: int
    retry_count: int = 0
    max_retries: int = 3

class EnterpriseAgentOrchestrator:
    """Orchestrates multiple AI agents for complex GitOps workflows."""
    
    def __init__(self, config: Dict):
        self.config = config
        self.agents = {}
        self.task_graph = nx.DiGraph()
        self.executor = ThreadPoolExecutor(max_workers=config.get('max_workers', 10))
        self.running_tasks = {}
        
        # Initialize agents
        self._initialize_agents()
        
        # Setup monitoring
        self.metrics = EnterpriseMetrics()
        self.logger = logging.getLogger(__name__)
    
    def _initialize_agents(self):
        """Initialize specialized agents for different roles."""
        
        # Code Analysis Agent
        self.agents[AgentRole.ANALYZER] = self._create_analyzer_agent()
        
        # Documentation Agent  
        self.agents[AgentRole.DOCUMENTER] = self._create_documenter_agent()
        
        # Validation Agent
        self.agents[AgentRole.VALIDATOR] = self._create_validator_agent()
        
        # Deployment Agent
        self.agents[AgentRole.DEPLOYER] = self._create_deployer_agent()
        
        # Monitoring Agent
        self.agents[AgentRole.MONITOR] = self._create_monitor_agent()
        
        # Compliance Agent
        self.agents[AgentRole.COMPLIANCE] = self._create_compliance_agent()
    
    def _create_analyzer_agent(self) -> AgentExecutor:
        """Create code analysis agent with specialized tools."""
        tools = [
            CommitAnalysisTool(),
            CodeComplexityTool(),
            DependencyAnalysisTool(),
            SecurityScanTool(),
        ]
        
        return AgentExecutor.from_agent_and_tools(
            agent=self._create_agent_with_tools(tools, "code_analyzer"),
            tools=tools,
            verbose=True,
            max_iterations=10
        )
    
    def _create_documenter_agent(self) -> AgentExecutor:
        """Create documentation generation agent."""
        tools = [
            ReleaseNotesGeneratorTool(),
            ChangelogGeneratorTool(),
            APIDocumentationTool(),
            ComplianceReportTool(),
        ]
        
        return AgentExecutor.from_agent_and_tools(
            agent=self._create_agent_with_tools(tools, "documenter"),
            tools=tools,
            verbose=True,
            max_iterations=8
        )
    
    async def execute_workflow(self, tasks: List[AgentTask]) -> Dict[str, Any]:
        """Execute a complex workflow with multiple agents."""
        
        # Build task dependency graph
        self._build_task_graph(tasks)
        
        # Validate graph (no cycles, all dependencies exist)
        if not nx.is_directed_acyclic_graph(self.task_graph):
            raise ValueError("Task dependencies form a cycle")
        
        # Execute tasks in topological order
        execution_order = list(nx.topological_sort(self.task_graph))
        results = {}
        
        for task_id in execution_order:
            task = next(t for t in tasks if t.id == task_id)
            
            # Wait for dependencies
            await self._wait_for_dependencies(task, results)
            
            # Execute task
            try:
                result = await self._execute_task(task, results)
                results[task_id] = result
                self.metrics.record_task_success(task)
                
            except Exception as e:
                self.logger.error(f"Task {task_id} failed: {e}")
                self.metrics.record_task_failure(task, e)
                
                # Handle retry logic
                if task.retry_count < task.max_retries:
                    task.retry_count += 1
                    self.logger.info(f"Retrying task {task_id} (attempt {task.retry_count})")
                    # Add back to execution queue
                    execution_order.append(task_id)
                else:
                    results[task_id] = {"error": str(e), "status": "failed"}
        
        return results
    
    async def _execute_task(self, task: AgentTask, context: Dict[str, Any]) -> Any:
        """Execute a single task with the appropriate agent."""
        
        agent = self.agents[task.role]
        
        # Prepare input with context
        enhanced_input = task.input_data.copy()
        enhanced_input['context'] = context
        enhanced_input['task_id'] = task.id
        
        # Execute with timeout
        try:
            result = await asyncio.wait_for(
                agent.arun(enhanced_input),
                timeout=task.timeout
            )
            return result
            
        except asyncio.TimeoutError:
            raise Exception(f"Task {task.id} timed out after {task.timeout} seconds")

class CommitAnalysisTool(BaseTool):
    """Tool for analyzing Git commits."""
    
    name = "commit_analyzer"
    description = "Analyzes Git commits for changes, impact, and patterns"
    
    def _run(self, input_data: Dict) -> Dict:
        """Analyze commits and return structured results."""
        
        commits = input_data.get('commits', [])
        
        # Perform analysis
        analysis_results = {
            'commit_count': len(commits),
            'change_types': self._classify_changes(commits),
            'impact_assessment': self._assess_impact(commits),
            'breaking_changes': self._detect_breaking_changes(commits),
            'security_implications': self._analyze_security(commits),
        }
        
        return analysis_results
    
    def _classify_changes(self, commits: List[Dict]) -> Dict[str, int]:
        """Classify types of changes in commits."""
        change_types = {
            'features': 0,
            'bugfixes': 0,
            'refactoring': 0,
            'documentation': 0,
            'dependencies': 0,
        }
        
        for commit in commits:
            message = commit.get('message', '').lower()
            
            if any(word in message for word in ['feat', 'feature', 'add']):
                change_types['features'] += 1
            elif any(word in message for word in ['fix', 'bug', 'patch']):
                change_types['bugfixes'] += 1
            elif any(word in message for word in ['refactor', 'cleanup', 'improve']):
                change_types['refactoring'] += 1
            elif any(word in message for word in ['doc', 'readme', 'comment']):
                change_types['documentation'] += 1
            elif any(word in message for word in ['dep', 'package', 'requirement']):
                change_types['dependencies'] += 1
        
        return change_types

class ReleaseNotesGeneratorTool(BaseTool):
    """Tool for generating release notes."""
    
    name = "release_notes_generator"
    description = "Generates comprehensive release notes from commit analysis"
    
    def _run(self, input_data: Dict) -> str:
        """Generate release notes from analysis data."""
        
        analysis = input_data.get('analysis', {})
        version = input_data.get('version', '1.0.0')
        
        # Generate structured release notes
        release_notes = self._generate_release_notes(analysis, version)
        
        return release_notes
    
    def _generate_release_notes(self, analysis: Dict, version: str) -> str:
        """Generate formatted release notes."""
        
        template = """
# Release Notes v{version}

## Summary
This release includes {total_changes} changes across multiple categories.

## 🚀 New Features
{features}

## 🐛 Bug Fixes  
{bugfixes}

## 🔧 Improvements
{improvements}

## ⚠️ Breaking Changes
{breaking_changes}

## 🔒 Security Updates
{security_updates}

---
*Generated automatically by Enterprise AI GitOps System*
"""
        
        return template.format(
            version=version,
            total_changes=analysis.get('commit_count', 0),
            features=self._format_changes(analysis.get('features', [])),
            bugfixes=self._format_changes(analysis.get('bugfixes', [])),
            improvements=self._format_changes(analysis.get('improvements', [])),
            breaking_changes=self._format_changes(analysis.get('breaking_changes', [])),
            security_updates=self._format_changes(analysis.get('security_updates', []))
        )

// enterprise_integration_hub.go
package integration

import (
    "context"
    "fmt"
    "sync"
    "time"
    
    "github.com/slack-go/slack"
    "github.com/microsoft/azure-devops-go-api/azuredevops"
    "github.com/xanzy/go-gitlab"
    "github.com/google/go-github/v45/github"
)

// Enterprise integration hub for multi-platform connectivity
type EnterpriseIntegrationHub struct {
    // Platform clients
    githubClient    *github.Client
    gitlabClient    *gitlab.Client
    azureClient     *azuredevops.Connection
    slackClient     *slack.Client
    jiraClient      *JiraClient
    confluenceClient *ConfluenceClient
    
    // Enterprise features
    webhook         *WebhookManager
    authentication *AuthManager
    rateLimiter     *RateLimiter
    cache          *IntegrationCache
    
    // Monitoring
    metrics        *IntegrationMetrics
    logger         *Logger
    
    // Concurrency
    mu             sync.RWMutex
    workers        map[string]*Worker
}

type IntegrationEvent struct {
    Source      string
    Type        string
    Payload     interface{}
    Timestamp   time.Time
    Metadata    map[string]string
}

type IntegrationResponse struct {
    Success     bool
    Message     string
    Data        interface{}
    ProcessedAt time.Time
}

func NewEnterpriseIntegrationHub(config *IntegrationConfig) *EnterpriseIntegrationHub {
    hub := &EnterpriseIntegrationHub{
        webhook:         NewWebhookManager(config.Webhook),
        authentication: NewAuthManager(config.Auth),
        rateLimiter:     NewRateLimiter(config.RateLimit),
        cache:          NewIntegrationCache(config.Cache),
        metrics:        NewIntegrationMetrics(),
        logger:         NewLogger(config.Logging),
        workers:        make(map[string]*Worker),
    }
    
    // Initialize platform clients
    hub.initializePlatformClients(config)
    
    // Start background services
    go hub.startEventProcessor()
    go hub.startHealthMonitoring()
    
    return hub
}

func (h *EnterpriseIntegrationHub) ProcessReleaseEvent(ctx context.Context, event *ReleaseEvent) (*IntegrationResponse, error) {
    // Validate event
    if err := h.validateEvent(event); err \!= nil {
        return nil, err
    }
    
    // Process across all platforms
    var wg sync.WaitGroup
    results := make(chan *PlatformResult, len(h.getActivePlatforms()))
    
    for _, platform := range h.getActivePlatforms() {
        wg.Add(1)
        go func(p Platform) {
            defer wg.Done()
            result := h.processPlatformEvent(ctx, p, event)
            results <- result
        }(platform)
    }
    
    // Wait for all platforms to complete
    go func() {
        wg.Wait()
        close(results)
    }()
    
    // Collect results
    var platformResults []*PlatformResult
    for result := range results {
        platformResults = append(platformResults, result)
    }
    
    // Generate aggregated response
    return h.aggregateResults(platformResults), nil
}

func (h *EnterpriseIntegrationHub) processPlatformEvent(ctx context.Context, platform Platform, event *ReleaseEvent) *PlatformResult {
    switch platform.Type {
    case "github":
        return h.processGitHubEvent(ctx, event)
    case "gitlab":
        return h.processGitLabEvent(ctx, event)
    case "slack":
        return h.processSlackEvent(ctx, event)
    case "jira":
        return h.processJiraEvent(ctx, event)
    default:
        return &PlatformResult{
            Platform: platform.Type,
            Success:  false,
            Error:    fmt.Errorf("unsupported platform: %s", platform.Type),
        }
    }
}

func (h *EnterpriseIntegrationHub) processGitHubEvent(ctx context.Context, event *ReleaseEvent) *PlatformResult {
    // Create GitHub release
    release := &github.RepositoryRelease{
        TagName:         &event.Version,
        Name:           &event.Title,
        Body:           &event.ReleaseNotes,
        Draft:          &event.Draft,
        Prerelease:     &event.Prerelease,
    }
    
    createdRelease, _, err := h.githubClient.Repositories.CreateRelease(
        ctx,
        event.Owner,
        event.Repository,
        release,
    )
    
    if err \!= nil {
        return &PlatformResult{
            Platform: "github",
            Success:  false,
            Error:    err,
        }
    }
    
    return &PlatformResult{
        Platform: "github",
        Success:  true,
        Data:     createdRelease,
    }
}

func (h *EnterpriseIntegrationHub) processSlackEvent(ctx context.Context, event *ReleaseEvent) *PlatformResult {
    // Create Slack notification
    attachment := slack.Attachment{
        Color:      "good",
        Title:      fmt.Sprintf("🚀 Release %s", event.Version),
        Text:       event.ReleaseNotes,
        Footer:     "Enterprise AI GitOps System",
        FooterIcon: "https://company.com/icon.png",
        Timestamp:  time.Now().Unix(),
    }
    
    _, _, err := h.slackClient.PostMessage(
        event.SlackChannel,
        slack.MsgOptionAttachments(attachment),
    )
    
    if err \!= nil {
        return &PlatformResult{
            Platform: "slack",
            Success:  false,
            Error:    err,
        }
    }
    
    return &PlatformResult{
        Platform: "slack",
        Success:  true,
        Data:     "notification_sent",
    }
}

# enterprise_webhook_system.py
"""Enterprise webhook system for real-time integrations."""

import asyncio
import json
import hmac
import hashlib
from typing import Dict, List, Optional, Callable
from dataclasses import dataclass
from fastapi import FastAPI, Request, HTTPException, BackgroundTasks
from fastapi.security import HTTPBearer, HTTPAuthorizationCredentials
import redis
from sqlalchemy.ext.asyncio import AsyncSession

@dataclass
class WebhookEvent:
    """Represents a webhook event."""
    id: str
    source: str
    event_type: str
    payload: Dict
    signature: str
    timestamp: float
    headers: Dict[str, str]

class EnterpriseWebhookSystem:
    """Enterprise webhook system with security and reliability."""
    
    def __init__(self, config: Dict):
        self.config = config
        self.app = FastAPI(title="Enterprise Webhook System")
        
        # Storage and caching
        self.redis_client = redis.Redis.from_url(config['redis_url'])
        self.database = AsyncDatabase(config['database_url'])
        
        # Security
        self.security = HTTPBearer()
        self.webhook_secrets = config.get('webhook_secrets', {})
        
        # Event handlers
        self.event_handlers: Dict[str, List[Callable]] = {}
        
        # Setup routes
        self._setup_routes()
    
    def _setup_routes(self):
        """Setup webhook endpoints."""
        
        @self.app.post("/webhooks/{source}")
        async def handle_webhook(
            source: str,
            request: Request,
            background_tasks: BackgroundTasks,
            credentials: HTTPAuthorizationCredentials = None
        ):
            return await self._process_webhook(source, request, background_tasks)
    
    async def _process_webhook(
        self,
        source: str,
        request: Request,
        background_tasks: BackgroundTasks
    ) -> Dict:
        """Process incoming webhook."""
        
        # Extract payload and headers
        payload = await request.json()
        headers = dict(request.headers)
        
        # Validate signature
        if not await self._validate_signature(source, payload, headers):
            raise HTTPException(status_code=401, detail="Invalid signature")
        
        # Create webhook event
        event = WebhookEvent(
            id=self._generate_event_id(),
            source=source,
            event_type=self._extract_event_type(source, payload, headers),
            payload=payload,
            signature=headers.get('x-hub-signature', ''),
            timestamp=time.time(),
            headers=headers
        )
        
        # Store event for reliability
        await self._store_event(event)
        
        # Process asynchronously
        background_tasks.add_task(self._handle_event, event)
        
        return {"status": "accepted", "event_id": event.id}
    
    async def _validate_signature(self, source: str, payload: Dict, headers: Dict) -> bool:
        """Validate webhook signature."""
        
        secret = self.webhook_secrets.get(source)
        if not secret:
            return False
        
        signature = headers.get('x-hub-signature-256', headers.get('x-hub-signature', ''))
        if not signature:
            return False
        
        # Compute expected signature
        payload_bytes = json.dumps(payload, separators=(',', ':')).encode()
        expected = hmac.new(
            secret.encode(),
            payload_bytes,
            hashlib.sha256
        ).hexdigest()
        
        return hmac.compare_digest(f"sha256={expected}", signature)
    
    async def _handle_event(self, event: WebhookEvent):
        """Handle webhook event with registered handlers."""
        
        handlers = self.event_handlers.get(event.event_type, [])
        
        for handler in handlers:
            try:
                await handler(event)
            except Exception as e:
                logger.error(f"Handler failed for event {event.id}: {e}")
                await self._record_handler_failure(event, handler, e)
    
    def register_handler(self, event_type: str, handler: Callable):
        """Register event handler."""
        if event_type not in self.event_handlers:
            self.event_handlers[event_type] = []
        
        self.event_handlers[event_type].append(handler)

# Example handlers for different platforms
async def github_push_handler(event: WebhookEvent):
    """Handle GitHub push events."""
    payload = event.payload
    
    # Extract commit information
    commits = payload.get('commits', [])
    repository = payload.get('repository', {})
    
    # Trigger AI analysis
    analysis_task = {
        'repository': repository['full_name'],
        'commits': commits,
        'branch': payload.get('ref', '').replace('refs/heads/', ''),
        'pusher': payload.get('pusher', {})
    }
    
    # Queue for processing
    await queue_ai_analysis(analysis_task)

async def gitlab_merge_request_handler(event: WebhookEvent):
    """Handle GitLab merge request events."""
    payload = event.payload
    
    if payload.get('object_attributes', {}).get('action') == 'merge':
        # Trigger release documentation generation
        await generate_release_documentation(payload)

async def jira_issue_handler(event: WebhookEvent):
    """Handle Jira issue events."""
    payload = event.payload
    
    # Link issue to commits and releases
    await link_issue_to_commits(payload)

// enterprise_security.go
package security

import (
    "context"
    "crypto/aes"
    "crypto/cipher"
    "crypto/rand"
    "encoding/base64"
    "fmt"
    "time"
    
    "github.com/golang-jwt/jwt/v4"
    "github.com/casbin/casbin/v2"
)

// Enterprise security manager
type EnterpriseSecurityManager struct {
    // Encryption
    encryptionKey   []byte
    gcm            cipher.AEAD
    
    // Authentication
    jwtSecret      []byte
    tokenDuration  time.Duration
    
    // Authorization
    rbacEnforcer   *casbin.Enforcer
    
    // Audit
    auditLogger    *AuditLogger
    
    // Compliance
    complianceRules map[string]*ComplianceRule
}

type SecurityContext struct {
    UserID      string
    Roles       []string
    Permissions []string
    TenantID    string
    IPAddress   string
    UserAgent   string
}

type AuditEvent struct {
    Timestamp   time.Time
    UserID      string
    Action      string
    Resource    string
    Result      string
    IPAddress   string
    Details     map[string]interface{}
}

func NewEnterpriseSecurityManager(config *SecurityConfig) (*EnterpriseSecurityManager, error) {
    // Initialize encryption
    block, err := aes.NewCipher(config.EncryptionKey)
    if err \!= nil {
        return nil, err
    }
    
    gcm, err := cipher.NewGCM(block)
    if err \!= nil {
        return nil, err
    }
    
    // Initialize RBAC
    enforcer, err := casbin.NewEnforcer(config.RBACModel, config.RBACPolicy)
    if err \!= nil {
        return nil, err
    }
    
    return &EnterpriseSecurityManager{
        encryptionKey:   config.EncryptionKey,
        gcm:            gcm,
        jwtSecret:      config.JWTSecret,
        tokenDuration:  config.TokenDuration,
        rbacEnforcer:   enforcer,
        auditLogger:    NewAuditLogger(config.Audit),
        complianceRules: loadComplianceRules(config.Compliance),
    }, nil
}

func (sm *EnterpriseSecurityManager) AuthenticateUser(ctx context.Context, token string) (*SecurityContext, error) {
    // Validate JWT token
    claims := &jwt.MapClaims{}
    
    _, err := jwt.ParseWithClaims(token, claims, func(token *jwt.Token) (interface{}, error) {
        return sm.jwtSecret, nil
    })
    
    if err \!= nil {
        return nil, fmt.Errorf("invalid token: %w", err)
    }
    
    // Extract user information
    userID := (*claims)["user_id"].(string)
    roles := (*claims)["roles"].([]interface{})
    tenantID := (*claims)["tenant_id"].(string)
    
    // Convert roles
    userRoles := make([]string, len(roles))
    for i, role := range roles {
        userRoles[i] = role.(string)
    }
    
    // Get permissions
    permissions := sm.getUserPermissions(userID, userRoles)
    
    return &SecurityContext{
        UserID:      userID,
        Roles:       userRoles,
        Permissions: permissions,
        TenantID:    tenantID,
    }, nil
}

func (sm *EnterpriseSecurityManager) AuthorizeAction(ctx context.Context, secCtx *SecurityContext, action string, resource string) error {
    // Check RBAC permissions
    for _, role := range secCtx.Roles {
        allowed, err := sm.rbacEnforcer.Enforce(role, resource, action)
        if err \!= nil {
            return err
        }
        
        if allowed {
            // Log successful authorization
            sm.auditLogger.LogEvent(&AuditEvent{
                Timestamp: time.Now(),
                UserID:    secCtx.UserID,
                Action:    action,
                Resource:  resource,
                Result:    "allowed",
                IPAddress: secCtx.IPAddress,
            })
            return nil
        }
    }
    
    // Log failed authorization
    sm.auditLogger.LogEvent(&AuditEvent{
        Timestamp: time.Now(),
        UserID:    secCtx.UserID,
        Action:    action,
        Resource:  resource,
        Result:    "denied",
        IPAddress: secCtx.IPAddress,
    })
    
    return fmt.Errorf("access denied")
}

func (sm *EnterpriseSecurityManager) EncryptSensitiveData(data []byte) (string, error) {
    // Generate nonce
    nonce := make([]byte, sm.gcm.NonceSize())
    if _, err := rand.Read(nonce); err \!= nil {
        return "", err
    }
    
    // Encrypt data
    ciphertext := sm.gcm.Seal(nonce, nonce, data, nil)
    
    // Return base64 encoded
    return base64.StdEncoding.EncodeToString(ciphertext), nil
}

func (sm *EnterpriseSecurityManager) DecryptSensitiveData(encryptedData string) ([]byte, error) {
    // Decode from base64
    data, err := base64.StdEncoding.DecodeString(encryptedData)
    if err \!= nil {
        return nil, err
    }
    
    // Extract nonce
    nonceSize := sm.gcm.NonceSize()
    if len(data) < nonceSize {
        return nil, fmt.Errorf("invalid encrypted data")
    }
    
    nonce := data[:nonceSize]
    ciphertext := data[nonceSize:]
    
    // Decrypt
    plaintext, err := sm.gcm.Open(nil, nonce, ciphertext, nil)
    if err \!= nil {
        return nil, err
    }
    
    return plaintext, nil
}

# enterprise_compliance.py
"""Enterprise compliance automation system."""

import asyncio
import json
from typing import Dict, List, Optional
from dataclasses import dataclass
from enum import Enum
import pandas as pd
from datetime import datetime, timedelta

class ComplianceFramework(Enum):
    SOC2 = "soc2"
    PCI_DSS = "pci_dss"
    GDPR = "gdpr"
    HIPAA = "hipaa"
    ISO27001 = "iso27001"

class ComplianceStatus(Enum):
    COMPLIANT = "compliant"
    NON_COMPLIANT = "non_compliant"
    NEEDS_REVIEW = "needs_review"
    PENDING = "pending"

@dataclass
class ComplianceRule:
    """Represents a compliance rule."""
    id: str
    framework: ComplianceFramework
    title: str
    description: str
    severity: str
    automated_check: bool
    check_function: Optional[str]

@dataclass
class ComplianceViolation:
    """Represents a compliance violation."""
    rule_id: str
    severity: str
    description: str
    affected_resources: List[str]
    detected_at: datetime
    remediation_steps: List[str]

class EnterpriseComplianceEngine:
    """Enterprise compliance automation engine."""
    
    def __init__(self, config: Dict):
        self.config = config
        self.rules = self._load_compliance_rules()
        self.audit_trail = []
        
        # Integration with external systems
        self.security_scanner = SecurityScanner(config.get('security_scanner'))
        self.audit_logger = AuditLogger(config.get('audit_logger'))
        
    def _load_compliance_rules(self) -> Dict[str, ComplianceRule]:
        """Load compliance rules from configuration."""
        rules = {}
        
        # SOC2 Type II rules
        rules['soc2_access_control'] = ComplianceRule(
            id='soc2_access_control',
            framework=ComplianceFramework.SOC2,
            title='Access Control Management',
            description='Ensure proper access controls are in place',
            severity='high',
            automated_check=True,
            check_function='check_access_controls'
        )
        
        rules['soc2_data_encryption'] = ComplianceRule(
            id='soc2_data_encryption',
            framework=ComplianceFramework.SOC2,
            title='Data Encryption at Rest and Transit',
            description='Verify data encryption requirements',
            severity='critical',
            automated_check=True,
            check_function='check_data_encryption'
        )
        
        # GDPR rules
        rules['gdpr_data_retention'] = ComplianceRule(
            id='gdpr_data_retention',
            framework=ComplianceFramework.GDPR,
            title='Data Retention Policy',
            description='Ensure data retention policies are followed',
            severity='high',
            automated_check=True,
            check_function='check_data_retention'
        )
        
        rules['gdpr_consent_management'] = ComplianceRule(
            id='gdpr_consent_management',
            framework=ComplianceFramework.GDPR,
            title='Consent Management',
            description='Verify proper consent management',
            severity='high',
            automated_check=False,
            check_function=None
        )
        
        return rules
    
    async def run_compliance_check(self, frameworks: List[ComplianceFramework]) -> Dict[str, Any]:
        """Run comprehensive compliance check."""
        
        results = {
            'overall_status': ComplianceStatus.COMPLIANT,
            'framework_results': {},
            'violations': [],
            'recommendations': [],
            'checked_at': datetime.now()
        }
        
        for framework in frameworks:
            framework_result = await self._check_framework_compliance(framework)
            results['framework_results'][framework.value] = framework_result
            
            # Collect violations
            results['violations'].extend(framework_result.get('violations', []))
            
            # Update overall status
            if framework_result['status'] \!= ComplianceStatus.COMPLIANT:
                results['overall_status'] = ComplianceStatus.NON_COMPLIANT
        
        # Generate recommendations
        results['recommendations'] = await self._generate_recommendations(results['violations'])
        
        # Store audit record
        await self._store_compliance_audit(results)
        
        return results
    
    async def _check_framework_compliance(self, framework: ComplianceFramework) -> Dict[str, Any]:
        """Check compliance for a specific framework."""
        
        framework_rules = [rule for rule in self.rules.values() if rule.framework == framework]
        
        violations = []
        passed_checks = 0
        total_checks = len(framework_rules)
        
        for rule in framework_rules:
            if rule.automated_check and rule.check_function:
                try:
                    check_result = await self._execute_compliance_check(rule)
                    if check_result['compliant']:
                        passed_checks += 1
                    else:
                        violations.append(ComplianceViolation(
                            rule_id=rule.id,
                            severity=rule.severity,
                            description=check_result['description'],
                            affected_resources=check_result.get('affected_resources', []),
                            detected_at=datetime.now(),
                            remediation_steps=check_result.get('remediation_steps', [])
                        ))
                except Exception as e:
                    # Log check failure but continue
                    self.audit_logger.error(f"Compliance check failed for {rule.id}: {e}")
        
        # Determine framework status
        compliance_percentage = (passed_checks / total_checks) * 100 if total_checks > 0 else 100
        
        if compliance_percentage == 100:
            status = ComplianceStatus.COMPLIANT
        elif compliance_percentage >= 80:
            status = ComplianceStatus.NEEDS_REVIEW
        else:
            status = ComplianceStatus.NON_COMPLIANT
        
        return {
            'framework': framework.value,
            'status': status,
            'compliance_percentage': compliance_percentage,
            'passed_checks': passed_checks,
            'total_checks': total_checks,
            'violations': violations
        }
    
    async def check_access_controls(self) -> Dict[str, Any]:
        """Check access control compliance."""
        
        violations = []
        
        # Check for overprivileged users
        privileged_users = await self._get_privileged_users()
        for user in privileged_users:
            if not await self._verify_user_justification(user):
                violations.append(f"User {user['id']} has excessive privileges")
        
        # Check for unused service accounts
        service_accounts = await self._get_service_accounts()
        for account in service_accounts:
            if not await self._verify_account_usage(account):
                violations.append(f"Service account {account['id']} appears unused")
        
        return {
            'compliant': len(violations) == 0,
            'description': f"Found {len(violations)} access control violations",
            'affected_resources': violations,
            'remediation_steps': [
                "Review and remove excessive privileges",
                "Implement principle of least privilege",
                "Regular access reviews"
            ]
        }
    
    async def check_data_encryption(self) -> Dict[str, Any]:
        """Check data encryption compliance."""
        
        violations = []
        
        # Check database encryption
        databases = await self._get_database_instances()
        for db in databases:
            if not db.get('encryption_at_rest', False):
                violations.append(f"Database {db['name']} lacks encryption at rest")
        
        # Check storage encryption
        storage_buckets = await self._get_storage_buckets()
        for bucket in storage_buckets:
            if not bucket.get('encryption_enabled', False):
                violations.append(f"Storage bucket {bucket['name']} is not encrypted")
        
        # Check transit encryption
        endpoints = await self._get_api_endpoints()
        for endpoint in endpoints:
            if not endpoint.get('tls_enabled', False):
                violations.append(f"Endpoint {endpoint['url']} lacks TLS encryption")
        
        return {
            'compliant': len(violations) == 0,
            'description': f"Found {len(violations)} encryption violations",
            'affected_resources': violations,
            'remediation_steps': [
                "Enable encryption at rest for all databases",
                "Configure storage bucket encryption",
                "Enforce TLS for all API endpoints"
            ]
        }