"""
Network Intelligence Engine - Enterprise Networking Intelligence for Nexus

The world's first intelligent networking system that provides:
- Automatic CIDR planning and conflict prevention
- Cost-optimized network architecture
- Security-first networking with compliance automation
- Multi-cloud network topology optimization
- Predictive network failure prevention

This extends the Nexus Engine with enterprise-grade networking intelligence.
"""

import asyncio
import ipaddress
import json
import time
from typing import Dict, Any, List, Optional, Tuple, Union, Set
from dataclasses import dataclass, asdict
from datetime import datetime, timedelta
from enum import Enum
import logging

from .cross_cloud_intelligence import ServiceCategory, ProviderCapability

logger = logging.getLogger(__name__)


class NetworkTier(Enum):
    """Network tier classifications"""
    PUBLIC = "public"
    PRIVATE = "private" 
    DATABASE = "database"
    MANAGEMENT = "management"
    CACHE = "cache"


class NetworkTopology(Enum):
    """Network topology patterns"""
    FLAT = "flat"
    THREE_TIER = "three_tier"
    HUB_SPOKE = "hub_spoke"
    MESH = "mesh"
    MICROSERVICES = "microservices"


@dataclass
class CIDRPlan:
    """CIDR allocation plan for an organization"""
    organization_name: str
    global_supernet: str  # e.g., "10.0.0.0/8"
    regional_allocations: Dict[str, str]  # region -> CIDR
    environment_allocations: Dict[str, Dict[str, str]]  # region -> env -> CIDR
    subnet_patterns: Dict[NetworkTier, str]  # tier -> pattern
    reserved_blocks: List[str]  # Reserved for future expansion
    conflict_free: bool
    created_at: datetime


@dataclass
class NetworkSecurityProfile:
    """Network security configuration profile"""
    profile_name: str
    compliance_frameworks: List[str]  # SOC2, HIPAA, PCI, etc.
    default_deny: bool
    required_protocols: List[str]
    forbidden_protocols: List[str]
    mandatory_encryption: bool
    logging_required: bool
    monitoring_endpoints: List[str]


@dataclass
class NetworkCostAnalysis:
    """Network cost analysis and optimization recommendations"""
    resource_type: str
    provider: str
    current_monthly_cost: float
    optimized_monthly_cost: float
    monthly_savings: float
    annual_savings: float
    optimization_actions: List[str]
    implementation_complexity: str  # low, medium, high
    confidence_score: float


@dataclass
class NetworkTopologyRecommendation:
    """Intelligent network topology recommendation"""
    recommended_topology: NetworkTopology
    architecture_components: Dict[str, Any]
    cost_estimate: float
    performance_score: float
    security_score: float
    scalability_score: float
    reasoning: List[str]
    implementation_steps: List[str]


@dataclass
class SubnetAllocationRequest:
    """Request for dynamic subnet allocation"""
    service_name: str
    region: str
    environment: str
    network_tier: NetworkTier
    required_capacity: int  # Number of IP addresses needed
    growth_factor: float = 2.0  # Multiplier for future growth
    compliance_requirements: List[str] = None
    priority: str = "medium"  # low, medium, high, critical


@dataclass
class SubnetAllocationResult:
    """Result of dynamic subnet allocation"""
    allocated_cidr: str
    available_ips: int
    reserved_for_growth: int
    subnet_id: str
    allocation_timestamp: datetime
    expires_at: Optional[datetime]
    can_expand: bool
    next_available_expansion: Optional[str]


@dataclass
class NetworkConflictAlert:
    """Alert for network conflicts"""
    conflict_type: str
    severity: str  # low, medium, high, critical
    affected_resources: List[str]
    conflicting_cidrs: List[str]
    impact_assessment: str
    recommended_actions: List[str]
    auto_remediation_available: bool
    detected_at: datetime


class NetworkIntelligence:
    """
    Revolutionary Network Intelligence Engine
    
    Extends Nexus Engine with enterprise networking intelligence including:
    - Intelligent CIDR planning and conflict prevention
    - Cost-optimized network architecture recommendations
    - Security-first networking with automatic compliance
    - Multi-cloud network topology optimization
    """
    
    def __init__(self, cross_cloud_intelligence = None):
        self.cross_cloud = cross_cloud_intelligence
        
        # Enterprise IP allocation standards
        self.standard_allocations = {
            "global_supernets": [
                "10.0.0.0/8",    # RFC 1918 - 16M addresses
                "172.16.0.0/12", # RFC 1918 - 1M addresses
                "192.168.0.0/16" # RFC 1918 - 65K addresses
            ],
            "region_sizes": {
                "small": "/20",   # 4,096 addresses
                "medium": "/16",  # 65,536 addresses
                "large": "/12",   # 1,048,576 addresses
                "xlarge": "/8"    # 16,777,216 addresses
            },
            "environment_ratios": {
                "production": 0.50,   # 50% of regional allocation
                "staging": 0.30,      # 30% of regional allocation
                "development": 0.15,  # 15% of regional allocation
                "management": 0.05    # 5% for management/monitoring
            }
        }
        
        # Network cost optimization patterns
        self.cost_optimization_rules = {
            "nat_gateway": {
                "threshold_monthly": 45.0,
                "alternatives": [
                    "nat_instance_with_autoscaling",
                    "vpc_endpoints_for_aws_services",
                    "consolidated_nat_strategy"
                ]
            },
            "load_balancer": {
                "utilization_threshold": 0.3,
                "consolidation_opportunities": True
            },
            "cross_az_traffic": {
                "cost_per_gb": 0.01,
                "optimization_strategies": [
                    "az_locality_optimization",
                    "connection_pooling",
                    "data_locality_improvements"
                ]
            }
        }
        
        # Security compliance frameworks
        self.compliance_frameworks = {
            "SOC2": {
                "required_encryption": True,
                "network_segmentation": True,
                "access_logging": True,
                "monitoring_required": ["vpc_flow_logs", "network_acl_changes"]
            },
            "HIPAA": {
                "required_encryption": True,
                "network_isolation": True,
                "access_logging": True,
                "dedicated_instances": True,
                "monitoring_required": ["all_network_traffic", "access_patterns"]
            },
            "PCI": {
                "network_segmentation": True,
                "firewall_rules": "strict",
                "monitoring_required": ["payment_network_access", "cardholder_data_flows"]
            }
        }
    
    def generate_enterprise_cidr_plan(self, 
                                    organization_name: str,
                                    target_regions: List[str],
                                    expected_scale: str = "medium",
                                    compliance_requirements: List[str] = None) -> CIDRPlan:
        """
        Generate intelligent CIDR allocation plan for enterprise deployment
        
        This prevents CIDR conflicts and creates scalable IP allocation strategy
        """
        
        # Select optimal global supernet based on scale
        if expected_scale == "small":
            global_supernet = "192.168.0.0/16"  # 65K addresses
            regional_prefix = 20  # 4K per region
        elif expected_scale == "medium":
            global_supernet = "172.16.0.0/12"   # 1M addresses
            regional_prefix = 16  # 65K per region
        elif expected_scale == "large":
            global_supernet = "10.0.0.0/8"      # 16M addresses
            regional_prefix = 12  # 1M per region
        else:
            global_supernet = "10.0.0.0/8"
            regional_prefix = 16
        
        # Generate regional allocations
        regional_allocations = {}
        environment_allocations = {}
        base_network = ipaddress.IPv4Network(global_supernet)
        
        # Calculate regional subnets
        regional_networks = list(base_network.subnets(new_prefix=regional_prefix))
        
        for i, region in enumerate(target_regions):
            if i >= len(regional_networks):
                logger.warning(f"Insufficient IP space for region {region}")
                continue
                
            region_network = regional_networks[i]
            regional_allocations[region] = str(region_network)
            
            # Generate environment allocations within region
            env_allocations = self._generate_environment_allocations(region_network)
            environment_allocations[region] = env_allocations
        
        # Generate subnet patterns for different tiers
        subnet_patterns = {
            NetworkTier.PUBLIC: f"{{region_base}}.0.0/24",      # 256 addresses
            NetworkTier.PRIVATE: f"{{region_base}}.16.0/20",    # 4096 addresses
            NetworkTier.DATABASE: f"{{region_base}}.32.0/24",   # 256 addresses
            NetworkTier.MANAGEMENT: f"{{region_base}}.48.0/28", # 16 addresses
            NetworkTier.CACHE: f"{{region_base}}.49.0/28"       # 16 addresses
        }
        
        # Reserve blocks for future expansion
        reserved_blocks = []
        if len(regional_networks) > len(target_regions):
            for i in range(len(target_regions), min(len(target_regions) + 3, len(regional_networks))):
                reserved_blocks.append(str(regional_networks[i]))
        
        # Check for conflicts with existing deployments
        conflict_free = self._verify_no_cidr_conflicts(regional_allocations)
        
        return CIDRPlan(
            organization_name=organization_name,
            global_supernet=global_supernet,
            regional_allocations=regional_allocations,
            environment_allocations=environment_allocations,
            subnet_patterns=subnet_patterns,
            reserved_blocks=reserved_blocks,
            conflict_free=conflict_free,
            created_at=datetime.now()
        )
    
    def _generate_environment_allocations(self, region_network: ipaddress.IPv4Network) -> Dict[str, str]:
        """Generate environment-specific CIDR allocations within a region"""
        
        env_allocations = {}
        
        # Calculate prefix for environment subnets (typically +2 from regional)
        env_prefix = region_network.prefixlen + 2  # 4 environments per region
        env_networks = list(region_network.subnets(new_prefix=env_prefix))
        
        environments = ["production", "staging", "development", "management"]
        
        for i, env in enumerate(environments):
            if i < len(env_networks):
                env_allocations[env] = str(env_networks[i])
        
        return env_allocations
    
    def _verify_no_cidr_conflicts(self, new_allocations: Dict[str, str]) -> bool:
        """
        Verify that new CIDR allocations don't conflict with existing networks
        
        In production, this would check against:
        - Existing VPC configurations
        - On-premises networks
        - Partner network connections
        """
        
        # For now, we'll implement basic overlap detection
        networks = []
        for cidr in new_allocations.values():
            try:
                networks.append(ipaddress.IPv4Network(cidr))
            except ipaddress.AddressValueError:
                logger.error(f"Invalid CIDR: {cidr}")
                return False
        
        # Check for overlaps
        for i, net1 in enumerate(networks):
            for j, net2 in enumerate(networks[i+1:], i+1):
                if net1.overlaps(net2):
                    logger.error(f"CIDR conflict detected: {net1} overlaps with {net2}")
                    return False
        
        return True
    
    def analyze_network_costs(self, 
                            current_architecture: Dict[str, Any],
                            provider: str = "aws") -> List[NetworkCostAnalysis]:
        """
        Analyze network costs and provide optimization recommendations
        """
        
        analyses = []
        
        # Analyze NAT Gateway costs
        nat_analysis = self._analyze_nat_gateway_costs(current_architecture, provider)
        if nat_analysis:
            analyses.append(nat_analysis)
        
        # Analyze Load Balancer costs
        lb_analysis = self._analyze_load_balancer_costs(current_architecture, provider)
        if lb_analysis:
            analyses.append(lb_analysis)
        
        # Analyze Cross-AZ traffic costs
        traffic_analysis = self._analyze_cross_az_traffic_costs(current_architecture, provider)
        if traffic_analysis:
            analyses.append(traffic_analysis)
        
        return analyses
    
    def _analyze_nat_gateway_costs(self, architecture: Dict[str, Any], provider: str) -> Optional[NetworkCostAnalysis]:
        """Analyze NAT Gateway costs and optimization opportunities"""
        
        nat_gateways = architecture.get("nat_gateways", [])
        if not nat_gateways:
            return None
        
        # Calculate current costs
        nat_count = len(nat_gateways)
        monthly_cost_per_nat = 45.0  # AWS NAT Gateway cost
        current_monthly_cost = nat_count * monthly_cost_per_nat
        
        # Optimization: Consolidate to single NAT with route table optimization
        if nat_count > 1:
            optimized_cost = monthly_cost_per_nat  # Single NAT Gateway
            monthly_savings = current_monthly_cost - optimized_cost
            
            optimization_actions = [
                f"Consolidate {nat_count} NAT Gateways to 1 with optimized routing",
                "Implement VPC Endpoints for AWS services to reduce NAT traffic",
                "Consider NAT Instance with auto-scaling for 60% cost reduction"
            ]
        else:
            # Already optimized, but suggest VPC endpoints
            optimized_cost = current_monthly_cost * 0.7  # 30% reduction with VPC endpoints
            monthly_savings = current_monthly_cost - optimized_cost
            
            optimization_actions = [
                "Implement VPC Endpoints for S3, DynamoDB, and other AWS services",
                "Optimize routing to reduce internet-bound traffic"
            ]
        
        return NetworkCostAnalysis(
            resource_type="nat_gateway",
            provider=provider,
            current_monthly_cost=current_monthly_cost,
            optimized_monthly_cost=optimized_cost,
            monthly_savings=monthly_savings,
            annual_savings=monthly_savings * 12,
            optimization_actions=optimization_actions,
            implementation_complexity="medium",
            confidence_score=0.85
        )
    
    def _analyze_load_balancer_costs(self, architecture: Dict[str, Any], provider: str) -> Optional[NetworkCostAnalysis]:
        """Analyze Load Balancer costs and consolidation opportunities"""
        
        load_balancers = architecture.get("load_balancers", [])
        if not load_balancers:
            return None
        
        lb_count = len(load_balancers)
        monthly_cost_per_lb = 22.50  # AWS ALB cost
        current_monthly_cost = lb_count * monthly_cost_per_lb
        
        # Check for consolidation opportunities
        underutilized_lbs = [lb for lb in load_balancers if lb.get("utilization", 0) < 0.3]
        
        if len(underutilized_lbs) > 1:
            # Can consolidate underutilized load balancers
            consolidated_count = lb_count - len(underutilized_lbs) + 1
            optimized_cost = consolidated_count * monthly_cost_per_lb
            monthly_savings = current_monthly_cost - optimized_cost
            
            optimization_actions = [
                f"Consolidate {len(underutilized_lbs)} underutilized load balancers",
                "Use host-based routing to combine multiple services",
                "Implement path-based routing for better resource utilization"
            ]
            
            return NetworkCostAnalysis(
                resource_type="load_balancer",
                provider=provider,
                current_monthly_cost=current_monthly_cost,
                optimized_monthly_cost=optimized_cost,
                monthly_savings=monthly_savings,
                annual_savings=monthly_savings * 12,
                optimization_actions=optimization_actions,
                implementation_complexity="low",
                confidence_score=0.90
            )
        
        return None
    
    def _analyze_cross_az_traffic_costs(self, architecture: Dict[str, Any], provider: str) -> Optional[NetworkCostAnalysis]:
        """Analyze cross-AZ traffic costs and optimization opportunities"""
        
        # Estimate based on typical patterns
        estimated_monthly_gb = architecture.get("estimated_cross_az_traffic_gb", 1000)
        cost_per_gb = 0.01
        current_monthly_cost = estimated_monthly_gb * cost_per_gb
        
        # Optimization: 40% reduction through locality optimization
        optimized_cost = current_monthly_cost * 0.6
        monthly_savings = current_monthly_cost - optimized_cost
        
        optimization_actions = [
            "Implement AZ-aware application deployment",
            "Optimize database read replicas for local AZ access",
            "Use connection pooling to reduce inter-AZ database connections",
            "Implement caching layers to reduce cross-AZ data transfer"
        ]
        
        return NetworkCostAnalysis(
            resource_type="cross_az_traffic",
            provider=provider,
            current_monthly_cost=current_monthly_cost,
            optimized_monthly_cost=optimized_cost,
            monthly_savings=monthly_savings,
            annual_savings=monthly_savings * 12,
            optimization_actions=optimization_actions,
            implementation_complexity="medium",
            confidence_score=0.75
        )
    
    def recommend_network_topology(self,
                                 application_requirements: Dict[str, Any]) -> NetworkTopologyRecommendation:
        """
        Recommend optimal network topology based on application requirements
        """
        
        # Analyze requirements
        service_count = application_requirements.get("service_count", 1)
        compliance_required = bool(application_requirements.get("compliance_requirements"))
        high_availability = application_requirements.get("high_availability", False)
        expected_traffic = application_requirements.get("expected_traffic", "medium")
        security_tier = application_requirements.get("security_tier", "standard")
        
        # Determine optimal topology
        if service_count <= 3 and not compliance_required:
            topology = NetworkTopology.FLAT
            architecture = self._design_flat_topology()
            cost_multiplier = 1.0
            security_score = 0.7
        elif service_count <= 10 and security_tier == "standard":
            topology = NetworkTopology.THREE_TIER
            architecture = self._design_three_tier_topology()
            cost_multiplier = 1.3
            security_score = 0.85
        elif service_count > 10 or compliance_required:
            topology = NetworkTopology.MICROSERVICES
            architecture = self._design_microservices_topology()
            cost_multiplier = 1.5
            security_score = 0.95
        else:
            topology = NetworkTopology.HUB_SPOKE
            architecture = self._design_hub_spoke_topology()
            cost_multiplier = 1.2
            security_score = 0.90
        
        # Calculate scores
        base_cost = 150.0  # Base monthly cost
        cost_estimate = base_cost * cost_multiplier
        
        performance_score = 0.8 if topology in [NetworkTopology.FLAT, NetworkTopology.THREE_TIER] else 0.9
        scalability_score = 0.6 if topology == NetworkTopology.FLAT else 0.9
        
        # Generate reasoning
        reasoning = [
            f"Recommended {topology.value} topology for {service_count} services",
            f"Security score: {security_score:.1%} meets {security_tier} requirements",
            f"Estimated monthly cost: ${cost_estimate:.2f}"
        ]
        
        if compliance_required:
            reasoning.append("Compliance requirements drive network segmentation needs")
        
        if high_availability:
            reasoning.append("High availability requires multi-AZ deployment")
        
        return NetworkTopologyRecommendation(
            recommended_topology=topology,
            architecture_components=architecture,
            cost_estimate=cost_estimate,
            performance_score=performance_score,
            security_score=security_score,
            scalability_score=scalability_score,
            reasoning=reasoning,
            implementation_steps=self._generate_implementation_steps(topology)
        )
    
    def _design_flat_topology(self) -> Dict[str, Any]:
        """Design flat network topology for simple applications"""
        return {
            "vpc_count": 1,
            "subnet_tiers": ["public", "private"],
            "nat_gateways": 1,
            "load_balancers": 1,
            "security_groups": 3,
            "network_acls": "default"
        }
    
    def _design_three_tier_topology(self) -> Dict[str, Any]:
        """Design three-tier network topology (web/app/data)"""
        return {
            "vpc_count": 1,
            "subnet_tiers": ["public", "private", "database"],
            "nat_gateways": 2,  # Multi-AZ
            "load_balancers": 2,  # Public and internal
            "security_groups": 6,
            "network_acls": "custom",
            "database_subnets": True
        }
    
    def _design_microservices_topology(self) -> Dict[str, Any]:
        """Design microservices network topology with service mesh"""
        return {
            "vpc_count": 1,
            "subnet_tiers": ["public", "private", "database", "cache", "management"],
            "nat_gateways": 3,  # Multi-AZ with redundancy
            "load_balancers": 4,  # External, internal, service mesh
            "security_groups": 12,
            "network_acls": "strict",
            "service_mesh": True,
            "istio_gateway": True,
            "database_subnets": True,
            "cache_subnets": True
        }
    
    def _design_hub_spoke_topology(self) -> Dict[str, Any]:
        """Design hub-spoke topology for multi-region deployment"""
        return {
            "vpc_count": 4,  # Hub + 3 spokes
            "transit_gateway": True,
            "subnet_tiers": ["public", "private", "database"],
            "nat_gateways": 6,  # 2 per major VPC
            "load_balancers": 6,
            "security_groups": 15,
            "network_acls": "strict",
            "cross_region_peering": True
        }
    
    def _generate_implementation_steps(self, topology: NetworkTopology) -> List[str]:
        """Generate step-by-step implementation guide"""
        
        base_steps = [
            "1. Generate CIDR plan with conflict checking",
            "2. Create VPC with intelligent subnetting",
            "3. Configure security groups with least-privilege access",
            "4. Deploy NAT Gateways with cost optimization"
        ]
        
        if topology == NetworkTopology.THREE_TIER:
            base_steps.extend([
                "5. Create database subnet group with encryption",
                "6. Configure network ACLs for tier isolation",
                "7. Deploy internal load balancer for app tier"
            ])
        elif topology == NetworkTopology.MICROSERVICES:
            base_steps.extend([
                "5. Deploy service mesh infrastructure",
                "6. Configure ingress gateway with SSL termination",
                "7. Implement network policies for micro-segmentation",
                "8. Deploy monitoring and observability stack"
            ])
        elif topology == NetworkTopology.HUB_SPOKE:
            base_steps.extend([
                "5. Deploy Transit Gateway in hub region",
                "6. Create spoke VPCs with auto-peering",
                "7. Configure routing tables for hub-spoke traffic",
                "8. Implement cross-region connectivity"
            ])
        
        base_steps.append(f"{len(base_steps) + 1}. Apply network intelligence monitoring with infra-daemon")
        
        return base_steps
    
    def detect_cidr_conflicts(self, 
                            proposed_cidr: str, 
                            existing_networks: List[str]) -> Dict[str, Any]:
        """
        Detect CIDR conflicts and suggest alternatives
        
        This is called by the daemon for real-time conflict prevention
        """
        
        conflicts = []
        suggested_alternatives = []
        
        try:
            proposed_network = ipaddress.IPv4Network(proposed_cidr)
            
            for existing_cidr in existing_networks:
                try:
                    existing_network = ipaddress.IPv4Network(existing_cidr)
                    if proposed_network.overlaps(existing_network):
                        overlap = self._calculate_overlap(proposed_network, existing_network)
                        conflicts.append({
                            "existing_cidr": existing_cidr,
                            "proposed_cidr": proposed_cidr,
                            "overlap_range": str(overlap),
                            "affected_ips": overlap.num_addresses
                        })
                except ipaddress.AddressValueError:
                    logger.warning(f"Invalid existing CIDR: {existing_cidr}")
            
            # Generate alternative CIDRs if conflicts exist
            if conflicts:
                suggested_alternatives = self._generate_alternative_cidrs(
                    proposed_network, 
                    [ipaddress.IPv4Network(cidr) for cidr in existing_networks if self._is_valid_cidr(cidr)]
                )
            
        except ipaddress.AddressValueError:
            return {
                "has_conflicts": True,
                "conflicts": [],
                "error": f"Invalid CIDR format: {proposed_cidr}",
                "suggested_alternatives": []
            }
        
        return {
            "has_conflicts": len(conflicts) > 0,
            "conflicts": conflicts,
            "suggested_alternatives": suggested_alternatives,
            "proposed_cidr": proposed_cidr
        }
    
    def _calculate_overlap(self, net1: ipaddress.IPv4Network, net2: ipaddress.IPv4Network) -> ipaddress.IPv4Network:
        """Calculate the overlapping range between two networks"""
        if net1.subnet_of(net2):
            return net1
        elif net2.subnet_of(net1):
            return net2
        else:
            # Find intersection
            start_ip = max(net1.network_address, net2.network_address)
            end_ip = min(net1.broadcast_address, net2.broadcast_address)
            
            # Create network from the overlapping range
            # This is a simplified approach - in production you'd want more sophisticated overlap calculation
            return ipaddress.IPv4Network(f"{start_ip}/{max(net1.prefixlen, net2.prefixlen)}")
    
    def _generate_alternative_cidrs(self, 
                                  proposed: ipaddress.IPv4Network, 
                                  existing: List[ipaddress.IPv4Network]) -> List[str]:
        """Generate alternative CIDR blocks that don't conflict"""
        
        alternatives = []
        
        # Try different base networks
        base_networks = [
            ipaddress.IPv4Network("10.0.0.0/8"),
            ipaddress.IPv4Network("172.16.0.0/12"),
            ipaddress.IPv4Network("192.168.0.0/16")
        ]
        
        for base in base_networks:
            # Generate subnets of the same size as proposed
            try:
                candidate_subnets = list(base.subnets(new_prefix=proposed.prefixlen))
                
                for candidate in candidate_subnets[:5]:  # Check first 5 candidates
                    if not any(candidate.overlaps(existing_net) for existing_net in existing):
                        alternatives.append(str(candidate))
                        if len(alternatives) >= 3:  # Provide 3 alternatives
                            break
                
                if len(alternatives) >= 3:
                    break
                    
            except ValueError:
                continue  # Skip if prefix is too large
        
        return alternatives
    
    def _is_valid_cidr(self, cidr: str) -> bool:
        """Check if CIDR is valid"""
        try:
            ipaddress.IPv4Network(cidr)
            return True
        except ipaddress.AddressValueError:
            return False


class DynamicSubnetAllocator:
    """
    Dynamic Subnet Allocation Engine
    
    Automatically allocates and expands subnets based on real-time usage patterns
    """
    
    def __init__(self, network_intelligence: NetworkIntelligence):
        self.network_intelligence = network_intelligence
        self.allocated_subnets: Dict[str, SubnetAllocationResult] = {}
        self.usage_patterns: Dict[str, List[float]] = {}  # Track usage over time
        
    def allocate_subnet(self, request: SubnetAllocationRequest) -> SubnetAllocationResult:
        """
        Intelligently allocate subnet with dynamic expansion capability
        """
        
        # Calculate optimal subnet size with growth factor
        base_capacity = request.required_capacity
        growth_capacity = int(base_capacity * request.growth_factor)
        total_capacity = base_capacity + growth_capacity
        
        # Determine optimal CIDR prefix for capacity
        prefix = self._calculate_optimal_prefix(total_capacity)
        
        # Find available CIDR block
        available_cidr = self._find_available_cidr_block(
            request.region, 
            request.environment, 
            prefix,
            request.network_tier
        )
        
        if not available_cidr:
            raise ValueError(f"No available CIDR block for {total_capacity} IPs in {request.region}")
        
        # Generate subnet ID
        subnet_id = f"{request.service_name}-{request.environment}-{request.network_tier.value}-{int(time.time())}"
        
        # Check for compliance requirements
        if request.compliance_requirements:
            self._validate_compliance_requirements(available_cidr, request.compliance_requirements)
        
        # Calculate next expansion possibility
        next_expansion = self._calculate_next_expansion(available_cidr, request.region)
        
        allocation_result = SubnetAllocationResult(
            allocated_cidr=available_cidr,
            available_ips=total_capacity - 5,  # Reserve 5 for AWS/GCP system use
            reserved_for_growth=growth_capacity,
            subnet_id=subnet_id,
            allocation_timestamp=datetime.now(),
            expires_at=None,  # Dynamic subnets don't expire
            can_expand=bool(next_expansion),
            next_available_expansion=next_expansion
        )
        
        # Store allocation
        self.allocated_subnets[subnet_id] = allocation_result
        
        return allocation_result
    
    def _calculate_optimal_prefix(self, required_capacity: int) -> int:
        """Calculate optimal CIDR prefix for required capacity"""
        
        # Add overhead for system addresses
        total_needed = required_capacity + 10
        
        # Find smallest prefix that can accommodate capacity
        for prefix in range(16, 29):  # /16 to /28
            available_addresses = 2 ** (32 - prefix) - 2  # Subtract network and broadcast
            if available_addresses >= total_needed:
                return prefix
        
        raise ValueError(f"Cannot allocate subnet for {required_capacity} addresses")
    
    def _find_available_cidr_block(self, region: str, environment: str, prefix: int, tier: NetworkTier) -> Optional[str]:
        """Find available CIDR block that doesn't conflict"""
        
        # Get existing allocations for the region/environment
        existing_cidrs = self._get_existing_cidrs(region, environment)
        
        # Base networks for different tiers
        tier_bases = {
            NetworkTier.PUBLIC: "10.0.0.0/16",
            NetworkTier.PRIVATE: "10.1.0.0/16", 
            NetworkTier.DATABASE: "10.2.0.0/16",
            NetworkTier.MANAGEMENT: "10.3.0.0/16",
            NetworkTier.CACHE: "10.4.0.0/16"
        }
        
        base_network = ipaddress.IPv4Network(tier_bases.get(tier, "10.1.0.0/16"))
        
        # Generate candidate subnets
        try:
            candidate_subnets = list(base_network.subnets(new_prefix=prefix))
            
            for candidate in candidate_subnets:
                # Check for conflicts
                conflicts = self.network_intelligence.detect_cidr_conflicts(
                    str(candidate), 
                    existing_cidrs
                )
                
                if not conflicts["has_conflicts"]:
                    return str(candidate)
                    
        except ValueError:
            logger.error(f"Invalid prefix {prefix} for base network {base_network}")
        
        return None
    
    def _get_existing_cidrs(self, region: str, environment: str) -> List[str]:
        """Get existing CIDR allocations for conflict checking"""
        
        existing = []
        
        # Get from stored allocations
        for allocation in self.allocated_subnets.values():
            existing.append(allocation.allocated_cidr)
        
        # In production, would also query cloud providers for existing VPCs/subnets
        # For now, return stored allocations
        return existing
    
    def _validate_compliance_requirements(self, cidr: str, requirements: List[str]):
        """Validate subnet allocation meets compliance requirements"""
        
        network = ipaddress.IPv4Network(cidr)
        
        for requirement in requirements:
            if requirement == "HIPAA":
                # HIPAA requires dedicated tenancy - check if CIDR is large enough for isolation
                if network.prefixlen > 24:
                    raise ValueError(f"HIPAA compliance requires subnet size >= /24, got /{network.prefixlen}")
            
            elif requirement == "SOC2":
                # SOC2 requires network segmentation - ensure proper tier isolation
                if network.prefixlen > 26:
                    logger.warning(f"SOC2 compliance recommends subnet size >= /26 for proper segmentation")
            
            elif requirement == "PCI":
                # PCI requires network isolation for cardholder data
                if network.prefixlen > 24:
                    raise ValueError(f"PCI compliance requires subnet size >= /24, got /{network.prefixlen}")
    
    def _calculate_next_expansion(self, current_cidr: str, region: str) -> Optional[str]:
        """Calculate next available expansion CIDR"""
        
        current_network = ipaddress.IPv4Network(current_cidr)
        
        # Find next adjacent network of same size
        next_network_int = int(current_network.broadcast_address) + 1
        
        try:
            next_network = ipaddress.IPv4Network(f"{ipaddress.IPv4Address(next_network_int)}/{current_network.prefixlen}")
            
            # Check if next network is available
            existing_cidrs = self._get_existing_cidrs(region, "all")
            conflicts = self.network_intelligence.detect_cidr_conflicts(
                str(next_network), 
                existing_cidrs
            )
            
            if not conflicts["has_conflicts"]:
                return str(next_network)
                
        except (ipaddress.AddressValueError, ValueError):
            pass
        
        return None
    
    def expand_subnet(self, subnet_id: str) -> SubnetAllocationResult:
        """Expand existing subnet allocation"""
        
        if subnet_id not in self.allocated_subnets:
            raise ValueError(f"Subnet {subnet_id} not found")
        
        current_allocation = self.allocated_subnets[subnet_id]
        
        if not current_allocation.can_expand or not current_allocation.next_available_expansion:
            raise ValueError(f"Subnet {subnet_id} cannot be expanded")
        
        # Merge current and expansion CIDRs
        current_network = ipaddress.IPv4Network(current_allocation.allocated_cidr)
        expansion_network = ipaddress.IPv4Network(current_allocation.next_available_expansion)
        
        # Create supernet that encompasses both
        merged_cidr = list(ipaddress.collapse_addresses([current_network, expansion_network]))[0]
        
        # Update allocation
        current_allocation.allocated_cidr = str(merged_cidr)
        current_allocation.available_ips = merged_cidr.num_addresses - 5
        current_allocation.allocation_timestamp = datetime.now()
        current_allocation.next_available_expansion = self._calculate_next_expansion(
            str(merged_cidr), 
            "region"  # Would extract from subnet_id in production
        )
        
        return current_allocation
    
    def monitor_subnet_usage(self, subnet_id: str, current_usage_percent: float):
        """Monitor subnet usage for automatic expansion triggers"""
        
        if subnet_id not in self.usage_patterns:
            self.usage_patterns[subnet_id] = []
        
        self.usage_patterns[subnet_id].append(current_usage_percent)
        
        # Keep only last 24 hours of data (assuming hourly updates)
        if len(self.usage_patterns[subnet_id]) > 24:
            self.usage_patterns[subnet_id] = self.usage_patterns[subnet_id][-24:]
        
        # Check for automatic expansion trigger
        if current_usage_percent > 85.0:  # 85% utilization threshold
            recent_usage = self.usage_patterns[subnet_id][-3:]  # Last 3 hours
            if len(recent_usage) >= 3 and all(usage > 80.0 for usage in recent_usage):
                logger.warning(f"Subnet {subnet_id} approaching capacity: {current_usage_percent:.1f}%")
                
                # Trigger automatic expansion if possible
                if subnet_id in self.allocated_subnets:
                    allocation = self.allocated_subnets[subnet_id]
                    if allocation.can_expand:
                        logger.info(f"Auto-expanding subnet {subnet_id}")
                        try:
                            self.expand_subnet(subnet_id)
                        except Exception as e:
                            logger.error(f"Failed to auto-expand subnet {subnet_id}: {e}")


class ComplianceNetworkValidator:
    """
    Advanced Compliance Network Validator
    
    Validates network configurations against regulatory requirements (SOC2, HIPAA, PCI-DSS)
    """
    
    def __init__(self, network_intelligence: NetworkIntelligence):
        self.network_intelligence = network_intelligence
        self.compliance_rules = {
            "SOC2": {
                "network_segmentation": True,
                "encryption_in_transit": True,
                "access_logging": True,
                "minimum_subnet_size": 26,  # /26 or larger
                "required_monitoring": ["vpc_flow_logs", "network_access_logs"],
                "forbidden_protocols": ["telnet", "ftp", "http"],
                "required_security_groups": ["database_isolation", "web_tier_isolation"]
            },
            "HIPAA": {
                "network_isolation": True,
                "encryption_in_transit": True,
                "encryption_at_rest": True,
                "dedicated_tenancy": True,
                "minimum_subnet_size": 24,  # /24 or larger
                "required_monitoring": ["all_network_traffic", "phi_access_logs"],
                "forbidden_protocols": ["telnet", "ftp", "http", "snmp_v1", "snmp_v2"],
                "required_security_groups": ["phi_isolation", "application_isolation", "database_isolation"],
                "audit_trail_retention": 2555  # 7 years in days
            },
            "PCI": {
                "network_segmentation": True,
                "cardholder_data_isolation": True,
                "encryption_in_transit": True,
                "minimum_subnet_size": 24,  # /24 or larger
                "required_monitoring": ["cardholder_data_access", "network_changes"],
                "forbidden_protocols": ["telnet", "ftp", "http"],
                "required_security_groups": ["cardholder_data_isolation", "payment_processing_isolation"],
                "regular_penetration_testing": True
            },
            "GDPR": {
                "data_locality": True,
                "encryption_in_transit": True,
                "encryption_at_rest": True,
                "minimum_subnet_size": 26,
                "required_monitoring": ["personal_data_access", "data_transfers"],
                "data_retention_controls": True,
                "right_to_be_forgotten": True
            }
        }
    
    def validate_network_compliance(self, 
                                  network_config: Dict[str, Any], 
                                  required_frameworks: List[str]) -> Dict[str, Any]:
        """
        Validate network configuration against compliance frameworks
        """
        
        validation_results = {
            "compliant": True,
            "framework_results": {},
            "violations": [],
            "recommendations": [],
            "risk_score": 0.0
        }
        
        for framework in required_frameworks:
            if framework not in self.compliance_rules:
                validation_results["violations"].append(f"Unknown compliance framework: {framework}")
                continue
            
            framework_result = self._validate_framework(network_config, framework)
            validation_results["framework_results"][framework] = framework_result
            
            if not framework_result["compliant"]:
                validation_results["compliant"] = False
                validation_results["violations"].extend(framework_result["violations"])
                validation_results["recommendations"].extend(framework_result["recommendations"])
                validation_results["risk_score"] = max(validation_results["risk_score"], framework_result["risk_score"])
        
        return validation_results
    
    def _validate_framework(self, network_config: Dict[str, Any], framework: str) -> Dict[str, Any]:
        """Validate against specific compliance framework"""
        
        rules = self.compliance_rules[framework]
        result = {
            "compliant": True,
            "violations": [],
            "recommendations": [],
            "risk_score": 0.0
        }
        
        # Validate network segmentation
        if rules.get("network_segmentation"):
            segmentation_result = self._validate_network_segmentation(network_config, framework)
            if not segmentation_result["compliant"]:
                result["compliant"] = False
                result["violations"].extend(segmentation_result["violations"])
                result["recommendations"].extend(segmentation_result["recommendations"])
                result["risk_score"] = max(result["risk_score"], segmentation_result["risk_score"])
        
        # Validate subnet sizes
        if "minimum_subnet_size" in rules:
            subnet_result = self._validate_subnet_sizes(network_config, rules["minimum_subnet_size"], framework)
            if not subnet_result["compliant"]:
                result["compliant"] = False
                result["violations"].extend(subnet_result["violations"])
                result["recommendations"].extend(subnet_result["recommendations"])
                result["risk_score"] = max(result["risk_score"], subnet_result["risk_score"])
        
        # Validate encryption requirements
        if rules.get("encryption_in_transit"):
            encryption_result = self._validate_encryption_in_transit(network_config, framework)
            if not encryption_result["compliant"]:
                result["compliant"] = False
                result["violations"].extend(encryption_result["violations"])
                result["recommendations"].extend(encryption_result["recommendations"])
                result["risk_score"] = max(result["risk_score"], encryption_result["risk_score"])
        
        # Validate monitoring requirements
        if "required_monitoring" in rules:
            monitoring_result = self._validate_monitoring_requirements(network_config, rules["required_monitoring"], framework)
            if not monitoring_result["compliant"]:
                result["compliant"] = False
                result["violations"].extend(monitoring_result["violations"])
                result["recommendations"].extend(monitoring_result["recommendations"])
                result["risk_score"] = max(result["risk_score"], monitoring_result["risk_score"])
        
        # Validate forbidden protocols
        if "forbidden_protocols" in rules:
            protocol_result = self._validate_protocol_restrictions(network_config, rules["forbidden_protocols"], framework)
            if not protocol_result["compliant"]:
                result["compliant"] = False
                result["violations"].extend(protocol_result["violations"])
                result["recommendations"].extend(protocol_result["recommendations"])
                result["risk_score"] = max(result["risk_score"], protocol_result["risk_score"])
        
        return result
    
    def _validate_network_segmentation(self, network_config: Dict[str, Any], framework: str) -> Dict[str, Any]:
        """Validate network segmentation requirements"""
        
        result = {"compliant": True, "violations": [], "recommendations": [], "risk_score": 0.0}
        
        # Check for proper tier separation
        subnets = network_config.get("subnets", [])
        tiers = set()
        
        for subnet in subnets:
            tier = subnet.get("tier", "unknown")
            tiers.add(tier)
        
        required_tiers = {"public", "private", "database"}
        if framework == "HIPAA":
            required_tiers.add("phi_isolation")
        elif framework == "PCI":
            required_tiers.add("cardholder_data")
        
        missing_tiers = required_tiers - tiers
        if missing_tiers:
            result["compliant"] = False
            result["violations"].append(f"Missing required network tiers: {missing_tiers}")
            result["recommendations"].append(f"Create isolated subnets for: {missing_tiers}")
            result["risk_score"] = 8.0  # High risk
        
        # Check for proper CIDR separation
        subnet_cidrs = [subnet.get("cidr") for subnet in subnets if subnet.get("cidr")]
        for i, cidr1 in enumerate(subnet_cidrs):
            for cidr2 in subnet_cidrs[i+1:]:
                if cidr1 and cidr2:
                    conflict_result = self.network_intelligence.detect_cidr_conflicts(cidr1, [cidr2])
                    if conflict_result["has_conflicts"]:
                        result["compliant"] = False
                        result["violations"].append(f"CIDR overlap detected: {cidr1} and {cidr2}")
                        result["recommendations"].append("Redesign CIDR allocation to eliminate overlaps")
                        result["risk_score"] = max(result["risk_score"], 6.0)
        
        return result
    
    def _validate_subnet_sizes(self, network_config: Dict[str, Any], min_size: int, framework: str) -> Dict[str, Any]:
        """Validate subnet sizes meet compliance requirements"""
        
        result = {"compliant": True, "violations": [], "recommendations": [], "risk_score": 0.0}
        
        subnets = network_config.get("subnets", [])
        
        for subnet in subnets:
            cidr = subnet.get("cidr")
            if not cidr:
                continue
            
            try:
                network = ipaddress.IPv4Network(cidr)
                if network.prefixlen > min_size:
                    result["compliant"] = False
                    result["violations"].append(
                        f"Subnet {cidr} (/{network.prefixlen}) smaller than required /{min_size} for {framework}"
                    )
                    result["recommendations"].append(
                        f"Resize subnet {cidr} to at least /{min_size} for {framework} compliance"
                    )
                    result["risk_score"] = max(result["risk_score"], 5.0)
            except ipaddress.AddressValueError:
                result["violations"].append(f"Invalid CIDR format: {cidr}")
                result["risk_score"] = max(result["risk_score"], 3.0)
        
        return result
    
    def _validate_encryption_in_transit(self, network_config: Dict[str, Any], framework: str) -> Dict[str, Any]:
        """Validate encryption in transit requirements"""
        
        result = {"compliant": True, "violations": [], "recommendations": [], "risk_score": 0.0}
        
        # Check load balancer SSL/TLS configuration
        load_balancers = network_config.get("load_balancers", [])
        for lb in load_balancers:
            if not lb.get("ssl_enabled", False):
                result["compliant"] = False
                result["violations"].append(f"Load balancer {lb.get('name', 'unknown')} missing SSL/TLS encryption")
                result["recommendations"].append("Enable SSL/TLS encryption on all load balancers")
                result["risk_score"] = max(result["risk_score"], 7.0)
        
        # Check for HTTP listeners (should be HTTPS)
        for lb in load_balancers:
            listeners = lb.get("listeners", [])
            for listener in listeners:
                if listener.get("protocol") == "HTTP":
                    result["compliant"] = False
                    result["violations"].append(f"HTTP listener detected on load balancer {lb.get('name', 'unknown')}")
                    result["recommendations"].append("Replace HTTP listeners with HTTPS")
                    result["risk_score"] = max(result["risk_score"], 8.0)
        
        return result
    
    def _validate_monitoring_requirements(self, network_config: Dict[str, Any], required_monitoring: List[str], framework: str) -> Dict[str, Any]:
        """Validate monitoring requirements"""
        
        result = {"compliant": True, "violations": [], "recommendations": [], "risk_score": 0.0}
        
        enabled_monitoring = network_config.get("monitoring", {}).get("enabled_features", [])
        
        missing_monitoring = set(required_monitoring) - set(enabled_monitoring)
        if missing_monitoring:
            result["compliant"] = False
            result["violations"].append(f"Missing required monitoring for {framework}: {missing_monitoring}")
            result["recommendations"].append(f"Enable monitoring features: {missing_monitoring}")
            result["risk_score"] = 6.0
        
        return result
    
    def _validate_protocol_restrictions(self, network_config: Dict[str, Any], forbidden_protocols: List[str], framework: str) -> Dict[str, Any]:
        """Validate protocol restrictions"""
        
        result = {"compliant": True, "violations": [], "recommendations": [], "risk_score": 0.0}
        
        # Check security group rules
        security_groups = network_config.get("security_groups", [])
        for sg in security_groups:
            rules = sg.get("rules", [])
            for rule in rules:
                protocol = rule.get("protocol", "").lower()
                if protocol in forbidden_protocols:
                    result["compliant"] = False
                    result["violations"].append(
                        f"Forbidden protocol {protocol} found in security group {sg.get('name', 'unknown')}"
                    )
                    result["recommendations"].append(f"Remove {protocol} protocol from security group rules")
                    result["risk_score"] = max(result["risk_score"], 7.0)
        
        return result
    
    def generate_compliance_report(self, network_config: Dict[str, Any], frameworks: List[str]) -> Dict[str, Any]:
        """Generate comprehensive compliance report"""
        
        validation_results = self.validate_network_compliance(network_config, frameworks)
        
        report = {
            "report_id": f"compliance-{int(time.time())}",
            "generated_at": datetime.now().isoformat(),
            "network_config_summary": {
                "total_vpcs": len(network_config.get("vpcs", [])),
                "total_subnets": len(network_config.get("subnets", [])),
                "total_security_groups": len(network_config.get("security_groups", [])),
                "frameworks_evaluated": frameworks
            },
            "compliance_status": {
                "overall_compliant": validation_results["compliant"],
                "risk_score": validation_results["risk_score"],
                "total_violations": len(validation_results["violations"]),
                "framework_breakdown": validation_results["framework_results"]
            },
            "violations": validation_results["violations"],
            "recommendations": validation_results["recommendations"],
            "remediation_priority": self._prioritize_remediation(validation_results["violations"]),
            "estimated_remediation_time": self._estimate_remediation_time(validation_results["violations"])
        }
        
        return report
    
    def _prioritize_remediation(self, violations: List[str]) -> List[Dict[str, Any]]:
        """Prioritize remediation actions"""
        
        priority_mapping = {
            "encryption": {"priority": "critical", "effort": "medium"},
            "protocol": {"priority": "high", "effort": "low"},
            "segmentation": {"priority": "high", "effort": "high"},
            "monitoring": {"priority": "medium", "effort": "low"},
            "subnet": {"priority": "medium", "effort": "medium"}
        }
        
        prioritized = []
        for violation in violations:
            priority_info = {"violation": violation, "priority": "low", "effort": "unknown"}
            
            for key, mapping in priority_mapping.items():
                if key in violation.lower():
                    priority_info.update(mapping)
                    break
            
            prioritized.append(priority_info)
        
        # Sort by priority: critical -> high -> medium -> low
        priority_order = {"critical": 0, "high": 1, "medium": 2, "low": 3}
        prioritized.sort(key=lambda x: priority_order.get(x["priority"], 4))
        
        return prioritized
    
    def _estimate_remediation_time(self, violations: List[str]) -> Dict[str, Any]:
        """Estimate time required for remediation"""
        
        time_estimates = {
            "encryption": 2,  # days
            "protocol": 0.5,  # days
            "segmentation": 5,  # days
            "monitoring": 1,  # days
            "subnet": 3  # days
        }
        
        total_days = 0
        breakdown = {}
        
        for violation in violations:
            for key, days in time_estimates.items():
                if key in violation.lower():
                    total_days += days
                    breakdown[key] = breakdown.get(key, 0) + days
                    break
        
        return {
            "total_days": total_days,
            "total_weeks": round(total_days / 7, 1),
            "breakdown_by_category": breakdown,
            "parallel_execution_days": max(breakdown.values()) if breakdown else 0
        }


class NetworkConflictMonitor:
    """
    Real-time Network Conflict Detection and Monitoring
    """
    
    def __init__(self, network_intelligence: NetworkIntelligence):
        self.network_intelligence = network_intelligence
        self.active_alerts: Dict[str, NetworkConflictAlert] = {}
        self.monitoring_enabled = True
        
    def scan_for_conflicts(self, target_environment: str = "all") -> List[NetworkConflictAlert]:
        """Scan for network conflicts across infrastructure"""
        
        alerts = []
        
        # Get all current network allocations
        current_networks = self._discover_existing_networks(target_environment)
        
        # Check for overlapping CIDRs
        overlap_conflicts = self._detect_cidr_overlaps(current_networks)
        alerts.extend(overlap_conflicts)
        
        # Check for routing conflicts
        routing_conflicts = self._detect_routing_conflicts(current_networks)
        alerts.extend(routing_conflicts)
        
        # Check for security group conflicts
        security_conflicts = self._detect_security_group_conflicts(current_networks)
        alerts.extend(security_conflicts)
        
        # Update active alerts
        for alert in alerts:
            alert_id = f"{alert.conflict_type}_{hash(str(alert.conflicting_cidrs))}"
            self.active_alerts[alert_id] = alert
        
        return alerts
    
    def _discover_existing_networks(self, environment: str) -> List[Dict[str, Any]]:
        """Discover existing network configurations"""
        
        # In production, this would query cloud providers APIs
        # For now, return mock data structure
        return [
            {
                "provider": "aws",
                "region": "us-east-1", 
                "environment": "production",
                "vpc_id": "vpc-123456",
                "cidr": "10.0.0.0/16",
                "subnets": [
                    {"subnet_id": "subnet-111", "cidr": "10.0.1.0/24", "tier": "public"},
                    {"subnet_id": "subnet-222", "cidr": "10.0.2.0/24", "tier": "private"}
                ]
            }
        ]
    
    def _detect_cidr_overlaps(self, networks: List[Dict[str, Any]]) -> List[NetworkConflictAlert]:
        """Detect overlapping CIDR blocks"""
        
        alerts = []
        
        for i, net1 in enumerate(networks):
            for net2 in networks[i+1:]:
                conflict_result = self.network_intelligence.detect_cidr_conflicts(
                    net1["cidr"], 
                    [net2["cidr"]]
                )
                
                if conflict_result["has_conflicts"]:
                    alert = NetworkConflictAlert(
                        conflict_type="cidr_overlap",
                        severity="high",
                        affected_resources=[net1["vpc_id"], net2["vpc_id"]],
                        conflicting_cidrs=[net1["cidr"], net2["cidr"]],
                        impact_assessment="Network routing may be unpredictable",
                        recommended_actions=[
                            "Redesign CIDR allocation to eliminate overlap",
                            "Implement network segmentation",
                            "Consider VPC peering instead of overlapping ranges"
                        ],
                        auto_remediation_available=False,
                        detected_at=datetime.now()
                    )
                    alerts.append(alert)
        
        return alerts
    
    def _detect_routing_conflicts(self, networks: List[Dict[str, Any]]) -> List[NetworkConflictAlert]:
        """Detect routing table conflicts"""
        
        # Mock implementation - in production would analyze route tables
        return []
    
    def _detect_security_group_conflicts(self, networks: List[Dict[str, Any]]) -> List[NetworkConflictAlert]:
        """Detect security group rule conflicts"""
        
        # Mock implementation - in production would analyze security groups
        return []


class CrossCloudCIDRManager:
    """
    Cross-Cloud CIDR Management System
    
    Unified IP address planning and management across AWS, GCP, Azure, and other providers
    """
    
    def __init__(self, network_intelligence: NetworkIntelligence):
        self.network_intelligence = network_intelligence
        self.provider_allocations: Dict[str, Dict[str, Any]] = {}
        self.global_allocation_map: Dict[str, str] = {}  # region -> CIDR
        self.cross_cloud_peering: Dict[str, List[str]] = {}  # provider -> list of peer providers
        
        # Provider-specific CIDR preferences
        self.provider_preferences = {
            "aws": {
                "preferred_supernets": ["10.0.0.0/8", "172.16.0.0/12"],
                "default_vpc_size": "/16",
                "region_allocation_strategy": "geographic_proximity"
            },
            "gcp": {
                "preferred_supernets": ["10.0.0.0/8", "192.168.0.0/16"], 
                "default_vpc_size": "/16",
                "region_allocation_strategy": "performance_optimized"
            },
            "azure": {
                "preferred_supernets": ["10.0.0.0/8", "172.16.0.0/12"],
                "default_vnet_size": "/16", 
                "region_allocation_strategy": "cost_optimized"
            },
            "digitalocean": {
                "preferred_supernets": ["10.0.0.0/8"],
                "default_vpc_size": "/20",
                "region_allocation_strategy": "simple_sequential"
            }
        }
    
    def generate_global_cidr_plan(self, 
                                organization_name: str,
                                target_providers: List[str],
                                target_regions: Dict[str, List[str]],  # provider -> regions
                                connectivity_requirements: Dict[str, Any] = None) -> Dict[str, Any]:
        """
        Generate unified CIDR plan across multiple cloud providers
        """
        
        if connectivity_requirements is None:
            connectivity_requirements = {}
        
        # Calculate total regional requirements
        total_regions = sum(len(regions) for regions in target_regions.values())
        
        # Select global supernet based on scale
        if total_regions <= 8:
            global_supernet = "10.0.0.0/8"
            provider_prefix = 12  # /12 per provider (1M addresses each)
        elif total_regions <= 16:
            global_supernet = "10.0.0.0/8" 
            provider_prefix = 13  # /13 per provider (512K addresses each)
        else:
            global_supernet = "10.0.0.0/8"
            provider_prefix = 14  # /14 per provider (256K addresses each)
        
        base_network = ipaddress.IPv4Network(global_supernet)
        provider_networks = list(base_network.subnets(new_prefix=provider_prefix))
        
        global_plan = {
            "organization_name": organization_name,
            "global_supernet": global_supernet,
            "total_providers": len(target_providers),
            "total_regions": total_regions,
            "provider_allocations": {},
            "cross_cloud_connectivity": {},
            "conflict_analysis": {"conflicts_detected": False, "conflicts": []},
            "created_at": datetime.now().isoformat()
        }
        
        # Allocate CIDRs per provider
        for i, provider in enumerate(target_providers):
            if i >= len(provider_networks):
                raise ValueError(f"Insufficient IP space for provider {provider}")
            
            provider_network = provider_networks[i]
            provider_regions = target_regions.get(provider, [])
            
            # Generate provider-specific allocations
            provider_allocation = self._generate_provider_allocation(
                provider,
                str(provider_network),
                provider_regions,
                connectivity_requirements.get(provider, {})
            )
            
            global_plan["provider_allocations"][provider] = provider_allocation
            
            # Track for conflict analysis
            self.provider_allocations[provider] = provider_allocation
        
        # Analyze cross-provider connectivity requirements
        if connectivity_requirements.get("cross_cloud_peering"):
            global_plan["cross_cloud_connectivity"] = self._plan_cross_cloud_connectivity(
                target_providers,
                connectivity_requirements["cross_cloud_peering"]
            )
        
        # Perform global conflict analysis
        conflict_analysis = self._analyze_global_conflicts(global_plan["provider_allocations"])
        global_plan["conflict_analysis"] = conflict_analysis
        
        return global_plan
    
    def _generate_provider_allocation(self, 
                                    provider: str, 
                                    provider_cidr: str, 
                                    regions: List[str],
                                    connectivity_requirements: Dict[str, Any]) -> Dict[str, Any]:
        """Generate CIDR allocation for a specific provider"""
        
        provider_network = ipaddress.IPv4Network(provider_cidr)
        preferences = self.provider_preferences.get(provider, self.provider_preferences["aws"])
        
        # Determine regional prefix based on number of regions
        if len(regions) <= 4:
            regional_prefix = provider_network.prefixlen + 2  # 4 regions max
        elif len(regions) <= 8:
            regional_prefix = provider_network.prefixlen + 3  # 8 regions max
        elif len(regions) <= 16:
            regional_prefix = provider_network.prefixlen + 4  # 16 regions max
        else:
            raise ValueError(f"Too many regions ({len(regions)}) for provider {provider}")
        
        regional_networks = list(provider_network.subnets(new_prefix=regional_prefix))
        
        allocation = {
            "provider": provider,
            "provider_cidr": provider_cidr,
            "strategy": preferences["region_allocation_strategy"],
            "regional_allocations": {},
            "reserved_blocks": [],
            "connectivity_config": connectivity_requirements
        }
        
        # Allocate regions based on strategy
        if preferences["region_allocation_strategy"] == "geographic_proximity":
            sorted_regions = self._sort_regions_geographically(regions, provider)
        elif preferences["region_allocation_strategy"] == "performance_optimized":
            sorted_regions = self._sort_regions_by_performance(regions, provider)
        elif preferences["region_allocation_strategy"] == "cost_optimized":
            sorted_regions = self._sort_regions_by_cost(regions, provider)
        else:
            sorted_regions = regions  # simple_sequential
        
        for i, region in enumerate(sorted_regions):
            if i >= len(regional_networks):
                logger.warning(f"Insufficient IP space for region {region} in provider {provider}")
                continue
            
            regional_network = regional_networks[i]
            
            # Generate environment allocations within region
            env_allocations = self._generate_regional_environment_allocations(
                regional_network, 
                provider, 
                region
            )
            
            allocation["regional_allocations"][region] = {
                "region_cidr": str(regional_network),
                "available_ips": regional_network.num_addresses - 1000,  # Reserve for overhead
                "environment_allocations": env_allocations,
                "can_expand": i < len(regional_networks) - 1
            }
        
        # Reserve remaining blocks for future expansion
        if len(regions) < len(regional_networks):
            for i in range(len(regions), min(len(regions) + 2, len(regional_networks))):
                allocation["reserved_blocks"].append(str(regional_networks[i]))
        
        return allocation
    
    def _generate_regional_environment_allocations(self, 
                                                 regional_network: ipaddress.IPv4Network,
                                                 provider: str,
                                                 region: str) -> Dict[str, Any]:
        """Generate environment allocations within a region"""
        
        # Standard environments: prod (50%), staging (25%), dev (15%), mgmt (10%)
        env_ratios = {
            "production": 0.50,
            "staging": 0.25, 
            "development": 0.15,
            "management": 0.10
        }
        
        # Calculate environment prefix (typically +2 from regional)
        env_prefix = regional_network.prefixlen + 2
        env_networks = list(regional_network.subnets(new_prefix=env_prefix))
        
        allocations = {}
        
        for i, (env_name, ratio) in enumerate(env_ratios.items()):
            if i >= len(env_networks):
                break
                
            env_network = env_networks[i]
            
            # Generate subnet tier allocations within environment
            tier_allocations = self._generate_tier_allocations(env_network, provider)
            
            allocations[env_name] = {
                "environment_cidr": str(env_network),
                "allocated_ratio": ratio,
                "available_ips": env_network.num_addresses - 100,
                "tier_allocations": tier_allocations
            }
        
        return allocations
    
    def _generate_tier_allocations(self, env_network: ipaddress.IPv4Network, provider: str) -> Dict[str, str]:
        """Generate network tier allocations within an environment"""
        
        # Standard tiers with typical sizing
        tier_configs = {
            NetworkTier.PUBLIC: {"ratio": 0.10, "min_prefix": 24},
            NetworkTier.PRIVATE: {"ratio": 0.60, "min_prefix": 20}, 
            NetworkTier.DATABASE: {"ratio": 0.20, "min_prefix": 24},
            NetworkTier.CACHE: {"ratio": 0.05, "min_prefix": 26},
            NetworkTier.MANAGEMENT: {"ratio": 0.05, "min_prefix": 26}
        }
        
        tier_prefix = env_network.prefixlen + 3  # 8 tier subnets max
        tier_networks = list(env_network.subnets(new_prefix=tier_prefix))
        
        allocations = {}
        
        for i, (tier, config) in enumerate(tier_configs.items()):
            if i >= len(tier_networks):
                break
            
            tier_network = tier_networks[i]
            
            # Adjust prefix based on minimum requirements
            final_prefix = max(tier_network.prefixlen, config["min_prefix"])
            if final_prefix > tier_network.prefixlen:
                # Need to create smaller subnet
                adjusted_subnets = list(tier_network.subnets(new_prefix=final_prefix))
                if adjusted_subnets:
                    allocations[tier.value] = str(adjusted_subnets[0])
            else:
                allocations[tier.value] = str(tier_network)
        
        return allocations
    
    def _sort_regions_geographically(self, regions: List[str], provider: str) -> List[str]:
        """Sort regions by geographic proximity"""
        
        # Simplified geographic grouping - in production would use actual coordinates
        geographic_groups = {
            "aws": {
                "us": ["us-east-1", "us-east-2", "us-west-1", "us-west-2"],
                "eu": ["eu-west-1", "eu-west-2", "eu-central-1"],
                "ap": ["ap-southeast-1", "ap-southeast-2", "ap-northeast-1"]
            },
            "gcp": {
                "us": ["us-central1", "us-east1", "us-west1"],
                "eu": ["europe-west1", "europe-west2", "europe-west3"],
                "asia": ["asia-southeast1", "asia-northeast1"]
            }
        }
        
        provider_groups = geographic_groups.get(provider, {})
        sorted_regions = []
        
        # Group regions geographically
        for group_regions in provider_groups.values():
            for region in regions:
                if region in group_regions and region not in sorted_regions:
                    sorted_regions.append(region)
        
        # Add any remaining regions
        for region in regions:
            if region not in sorted_regions:
                sorted_regions.append(region)
        
        return sorted_regions
    
    def _sort_regions_by_performance(self, regions: List[str], provider: str) -> List[str]:
        """Sort regions by performance characteristics"""
        
        # Simplified performance scoring - in production would use real metrics
        performance_scores = {
            "aws": {
                "us-east-1": 10, "us-west-2": 9, "eu-west-1": 8,
                "ap-southeast-1": 7, "us-east-2": 6
            },
            "gcp": {
                "us-central1": 10, "us-east1": 9, "europe-west1": 8,
                "asia-southeast1": 7
            }
        }
        
        scores = performance_scores.get(provider, {})
        return sorted(regions, key=lambda r: scores.get(r, 5), reverse=True)
    
    def _sort_regions_by_cost(self, regions: List[str], provider: str) -> List[str]:
        """Sort regions by cost optimization"""
        
        # Simplified cost scoring - in production would use real pricing data
        cost_scores = {
            "aws": {
                "us-east-1": 10, "us-east-2": 9, "us-west-1": 6,
                "eu-west-1": 7, "ap-southeast-1": 5
            },
            "gcp": {
                "us-central1": 10, "us-east1": 8, "europe-west1": 6,
                "asia-southeast1": 5
            }
        }
        
        scores = cost_scores.get(provider, {})
        return sorted(regions, key=lambda r: scores.get(r, 5), reverse=True)
    
    def _plan_cross_cloud_connectivity(self, 
                                     providers: List[str], 
                                     peering_requirements: Dict[str, Any]) -> Dict[str, Any]:
        """Plan cross-cloud connectivity and peering"""
        
        connectivity_plan = {
            "peering_connections": [],
            "transit_gateways": {},
            "vpn_connections": [],
            "estimated_costs": {},
            "bandwidth_requirements": {}
        }
        
        # Analyze required peering connections
        for provider1 in providers:
            for provider2 in providers:
                if provider1 != provider2:
                    peering_key = f"{provider1}-{provider2}"
                    reverse_key = f"{provider2}-{provider1}"
                    
                    # Check if peering is required and not already planned
                    if (peering_requirements.get(peering_key) and 
                        not any(conn["connection_id"] == peering_key for conn in connectivity_plan["peering_connections"])):
                        
                        connection = {
                            "connection_id": peering_key,
                            "provider_1": provider1,
                            "provider_2": provider2,
                            "connection_type": self._determine_connection_type(provider1, provider2),
                            "bandwidth_requirement": peering_requirements[peering_key].get("bandwidth", "1Gbps"),
                            "estimated_monthly_cost": self._estimate_connection_cost(provider1, provider2),
                            "latency_requirement": peering_requirements[peering_key].get("latency", "< 100ms")
                        }
                        
                        connectivity_plan["peering_connections"].append(connection)
        
        return connectivity_plan
    
    def _determine_connection_type(self, provider1: str, provider2: str) -> str:
        """Determine optimal connection type between providers"""
        
        # Connection type mapping based on provider compatibility
        connection_types = {
            ("aws", "gcp"): "vpn_gateway",
            ("aws", "azure"): "express_route_gateway", 
            ("gcp", "azure"): "interconnect_vpn",
            ("aws", "digitalocean"): "vpn_tunnel",
            ("gcp", "digitalocean"): "vpn_tunnel",
            ("azure", "digitalocean"): "vpn_tunnel"
        }
        
        key = tuple(sorted([provider1, provider2]))
        return connection_types.get(key, "vpn_tunnel")
    
    def _estimate_connection_cost(self, provider1: str, provider2: str) -> float:
        """Estimate monthly cost for cross-cloud connection"""
        
        # Simplified cost estimation - in production would use real pricing
        base_costs = {
            "vpn_gateway": 45.0,
            "express_route_gateway": 200.0,
            "interconnect_vpn": 100.0,
            "vpn_tunnel": 25.0
        }
        
        connection_type = self._determine_connection_type(provider1, provider2)
        return base_costs.get(connection_type, 50.0)
    
    def _analyze_global_conflicts(self, provider_allocations: Dict[str, Dict[str, Any]]) -> Dict[str, Any]:
        """Analyze conflicts across all provider allocations"""
        
        conflicts = []
        all_cidrs = []
        
        # Collect all CIDRs across providers
        for provider, allocation in provider_allocations.items():
            provider_cidr = allocation["provider_cidr"]
            all_cidrs.append({"provider": provider, "cidr": provider_cidr, "type": "provider"})
            
            for region, region_data in allocation["regional_allocations"].items():
                region_cidr = region_data["region_cidr"]
                all_cidrs.append({"provider": provider, "region": region, "cidr": region_cidr, "type": "region"})
        
        # Check for conflicts
        for i, cidr1 in enumerate(all_cidrs):
            for cidr2 in all_cidrs[i+1:]:
                conflict_result = self.network_intelligence.detect_cidr_conflicts(
                    cidr1["cidr"], 
                    [cidr2["cidr"]]
                )
                
                if conflict_result["has_conflicts"]:
                    conflicts.append({
                        "conflict_type": "cross_provider_overlap",
                        "cidr_1": cidr1,
                        "cidr_2": cidr2,
                        "overlap_details": conflict_result["conflicts"][0] if conflict_result["conflicts"] else {}
                    })
        
        return {
            "conflicts_detected": len(conflicts) > 0,
            "total_conflicts": len(conflicts),
            "conflicts": conflicts,
            "resolution_recommendations": self._generate_conflict_resolutions(conflicts)
        }
    
    def _generate_conflict_resolutions(self, conflicts: List[Dict[str, Any]]) -> List[str]:
        """Generate recommendations for resolving conflicts"""
        
        if not conflicts:
            return ["No conflicts detected - CIDR allocation is clean"]
        
        recommendations = []
        
        for conflict in conflicts:
            cidr1 = conflict["cidr_1"] 
            cidr2 = conflict["cidr_2"]
            
            if cidr1["type"] == "provider" and cidr2["type"] == "provider":
                recommendations.append(
                    f"Critical: Provider-level CIDR conflict between {cidr1['provider']} and {cidr2['provider']} - "
                    f"redesign global supernet allocation"
                )
            elif cidr1["type"] == "region" and cidr2["type"] == "region":
                recommendations.append(
                    f"Regional CIDR conflict between {cidr1['provider']}:{cidr1['region']} and "
                    f"{cidr2['provider']}:{cidr2['region']} - adjust regional allocations"
                )
        
        recommendations.append("Consider using larger global supernet (e.g., 10.0.0.0/8 -> dedicated /12 per provider)")
        
        return recommendations
    
    def validate_cross_cloud_plan(self, global_plan: Dict[str, Any]) -> Dict[str, Any]:
        """Validate cross-cloud CIDR plan for deployment readiness"""
        
        validation = {
            "valid": True,
            "warnings": [],
            "errors": [],
            "recommendations": []
        }
        
        # Check for conflicts
        if global_plan["conflict_analysis"]["conflicts_detected"]:
            validation["valid"] = False
            validation["errors"].append("CIDR conflicts detected - plan cannot be deployed")
            validation["errors"].extend(global_plan["conflict_analysis"]["resolution_recommendations"])
        
        # Validate provider allocations
        for provider, allocation in global_plan["provider_allocations"].items():
            provider_validation = self._validate_provider_allocation(provider, allocation)
            
            if not provider_validation["valid"]:
                validation["valid"] = False
                validation["errors"].extend(provider_validation["errors"])
            
            validation["warnings"].extend(provider_validation["warnings"])
            validation["recommendations"].extend(provider_validation["recommendations"])
        
        return validation
    
    def _validate_provider_allocation(self, provider: str, allocation: Dict[str, Any]) -> Dict[str, Any]:
        """Validate individual provider allocation"""
        
        validation = {"valid": True, "warnings": [], "errors": [], "recommendations": []}
        
        # Check if provider CIDR is large enough
        provider_network = ipaddress.IPv4Network(allocation["provider_cidr"])
        regions_count = len(allocation["regional_allocations"])
        
        if provider_network.prefixlen > 12 and regions_count > 4:
            validation["warnings"].append(
                f"{provider}: Small provider CIDR /{provider_network.prefixlen} for {regions_count} regions"
            )
        
        # Check regional allocations
        for region, region_data in allocation["regional_allocations"].items():
            region_network = ipaddress.IPv4Network(region_data["region_cidr"])
            
            if region_network.prefixlen > 20:
                validation["warnings"].append(
                    f"{provider}:{region}: Small regional CIDR /{region_network.prefixlen} may limit scaling"
                )
            
            # Check environment allocations
            env_count = len(region_data["environment_allocations"])
            if env_count < 3:
                validation["recommendations"].append(
                    f"{provider}:{region}: Consider adding more environments (currently {env_count})"
                )
        
        return validation


# Global Network Intelligence instance
network_intelligence = NetworkIntelligence()