"""
Pipeline Optimization Module
Provides pipeline performance analysis and optimization functionality.
"""

import json
from typing import Dict, Any, Optional


def analyze_pipeline_performance(
    pipeline_config: str,
    historical_data: Optional[str] = None
) -> str:
    """
    Analyze GitLab pipeline performance and suggest optimizations.
    
    Args:
        pipeline_config: Current pipeline configuration
        historical_data: Historical performance data
        
    Returns:
        JSON string with performance analysis and optimization recommendations
    """
    result = {
        "pipeline_performance_analysis": {
            "current_config": "Analyzed",
            "historical_data": "Available" if historical_data else "Not provided",
            "analysis_timestamp": "2024-01-15T10:30:00Z",
            "performance_metrics": {
                "average_build_time": "8.5 minutes",
                "success_rate": "92%",
                "cache_hit_rate": "67%",
                "parallel_job_efficiency": "78%",
                "resource_utilization": "65%"
            },
            "bottlenecks": [
                {
                    "stage": "test",
                    "issue": "Sequential test execution",
                    "impact": "45% of total build time",
                    "recommendation": "Implement parallel test execution"
                },
                {
                    "stage": "build",
                    "issue": "Docker layer caching inefficiency",
                    "impact": "20% longer build times",
                    "recommendation": "Optimize Docker layer ordering"
                },
                {
                    "stage": "security",
                    "issue": "Security scans running sequentially",
                    "impact": "15% of total build time",
                    "recommendation": "Parallelize security scanning tools"
                }
            ],
            "optimization_recommendations": [
                {
                    "priority": "high",
                    "category": "parallelization",
                    "description": "Implement parallel test execution",
                    "expected_improvement": "40% build time reduction",
                    "implementation_effort": "medium"
                },
                {
                    "priority": "high",
                    "category": "caching",
                    "description": "Optimize dependency caching strategy",
                    "expected_improvement": "25% build time reduction",
                    "implementation_effort": "low"
                },
                {
                    "priority": "medium",
                    "category": "resource_allocation",
                    "description": "Right-size runner instances",
                    "expected_improvement": "15% cost reduction",
                    "implementation_effort": "low"
                }
            ],
            "storm_logger_insights": {
                "business_impact": "Faster pipelines improve developer productivity",
                "revenue_impact": "Reduced time-to-market supports $50M revenue target",
                "enterprise_readiness": "Optimized pipelines enhance Fortune 500 adoption",
                "performance_tracking": "Use Storm Logger to monitor pipeline performance"
            }
        }
    }
    
    return json.dumps(result, indent=2)