disaster_scenarios:
  natural_disasters:
    - earthquakes
    - floods
    - hurricanes
    - wildfires
    - extreme_weather

  technical_failures:
    - hardware_failure
    - software_bugs
    - network_outages
    - power_failures
    - cooling_system_failure

  human_errors:
    - accidental_deletion
    - misconfiguration
    - deployment_errors
    - security_breaches

  cyber_attacks:
    - ransomware
    - ddos_attacks
    - data_breaches
    - malware
    - insider_threats

  provider_issues:
    - region_outage
    - service_degradation
    - api_failures
    - account_suspension

class BusinessImpactAnalysis:
    def __init__(self):
        self.applications = {}
        self.dependencies = {}

    def analyze_application_criticality(self):
        """Analyze and categorize applications by criticality"""

        criticality_matrix = {
            'tier_1_critical': {
                'description': 'Mission-critical, customer-facing',
                'max_downtime': '1 hour',
                'max_data_loss': '5 minutes',
                'examples': [
                    'E-commerce platform',
                    'Payment processing',
                    'Core banking systems'
                ],
                'recovery_priority': 1,
                'dr_strategy': 'Multi-region active-active'
            },

            'tier_2_essential': {
                'description': 'Important business functions',
                'max_downtime': '4 hours',
                'max_data_loss': '1 hour',
                'examples': [
                    'Email systems',
                    'CRM applications',
                    'Internal portals'
                ],
                'recovery_priority': 2,
                'dr_strategy': 'Warm standby'
            },

            'tier_3_standard': {
                'description': 'Standard business applications',
                'max_downtime': '24 hours',
                'max_data_loss': '4 hours',
                'examples': [
                    'Development environments',
                    'Internal tools',
                    'Reporting systems'
                ],
                'recovery_priority': 3,
                'dr_strategy': 'Pilot light'
            },

            'tier_4_non_critical': {
                'description': 'Non-essential systems',
                'max_downtime': '7 days',
                'max_data_loss': '24 hours',
                'examples': [
                    'Archive systems',
                    'Test environments',
                    'Legacy applications'
                ],
                'recovery_priority': 4,
                'dr_strategy': 'Backup and restore'
            }
        }

        return criticality_matrix

    def calculate_downtime_cost(self, application, downtime_hours):
        """Calculate financial impact of downtime"""

        cost_factors = {
            'revenue_loss': application['hourly_revenue'] * downtime_hours,
            'productivity_loss': application['affected_users'] * application['hourly_cost'] * downtime_hours,
            'sla_penalties': self.calculate_sla_penalties(application, downtime_hours),
            'reputation_damage': self.estimate_reputation_impact(application, downtime_hours),
            'recovery_costs': self.estimate_recovery_costs(downtime_hours)
        }

        total_cost = sum(cost_factors.values())

        return {
            'total_cost': total_cost,
            'breakdown': cost_factors,
            'cost_per_hour': total_cost / downtime_hours
        }

dr_strategy_framework:
  decision_factors:
    technical:
      - application_architecture
      - data_volume
      - change_rate
      - dependencies
      - network_requirements

    business:
      - criticality_tier
      - budget_constraints
      - compliance_requirements
      - customer_sla
      - geographic_presence

    operational:
      - team_expertise
      - existing_tools
      - automation_capability
      - testing_requirements

  strategy_comparison:
    backup_restore:
      rto: "24+ hours"
      rpo: "24 hours"
      cost: "$"
      complexity: "Low"
      use_cases:
        - "Non-critical applications"
        - "Development environments"
        - "Archive systems"

    pilot_light:
      rto: "4-24 hours"
      rpo: "1-4 hours"
      cost: "$$"
      complexity: "Medium"
      use_cases:
        - "Business applications"
        - "Internal systems"
        - "Seasonal workloads"

    warm_standby:
      rto: "1-4 hours"
      rpo: "5-60 minutes"
      cost: "$$$"
      complexity: "Medium-High"
      use_cases:
        - "Customer-facing apps"
        - "Critical databases"
        - "Revenue-generating systems"

    multi_site_active:
      rto: "< 1 hour"
      rpo: "< 5 minutes"
      cost: "$$$$"
      complexity: "High"
      use_cases:
        - "Mission-critical systems"
        - "Zero-downtime requirements"
        - "Global applications"

class RecoveryObjectives:
    def __init__(self):
        self.objectives = {}

    def define_recovery_objectives(self, application):
        """Define RTO and RPO for an application"""

        recovery_objectives = {
            'rto': {  # Recovery Time Objective
                'definition': 'Maximum acceptable downtime',
                'factors': [
                    'Business impact',
                    'Customer expectations',
                    'Regulatory requirements',
                    'Competitive landscape'
                ],
                'calculation': self.calculate_rto(application),
                'components': {
                    'detection_time': '5-15 minutes',
                    'decision_time': '15-30 minutes',
                    'recovery_execution': '30 minutes - 4 hours',
                    'validation_time': '15-60 minutes'
                }
            },

            'rpo': {  # Recovery Point Objective
                'definition': 'Maximum acceptable data loss',
                'factors': [
                    'Data criticality',
                    'Transaction volume',
                    'Compliance requirements',
                    'Storage costs'
                ],
                'calculation': self.calculate_rpo(application),
                'implementation': {
                    'continuous_replication': '< 1 minute',
                    'frequent_snapshots': '5-60 minutes',
                    'regular_backups': '1-24 hours'
                }
            },

            'rco': {  # Recovery Cost Objective
                'definition': 'Maximum acceptable recovery cost',
                'factors': [
                    'Infrastructure costs',
                    'Data transfer costs',
                    'Operational costs',
                    'Opportunity costs'
                ],
                'budget': self.calculate_recovery_budget(application)
            }
        }

        return recovery_objectives

dr_patterns:
  backup_and_restore:
    architecture:
      primary_region: "us-east-1"
      backup_storage: "Cross-region S3 with lifecycle"

    implementation:
      backup_strategy:
        - type: "Full backup"
          frequency: "Weekly"
          retention: "4 weeks"

        - type: "Incremental"
          frequency: "Daily"
          retention: "7 days"

        - type: "Transaction logs"
          frequency: "Hourly"
          retention: "24 hours"

    recovery_process:
      - "Provision infrastructure"
      - "Restore latest full backup"
      - "Apply incremental backups"
      - "Apply transaction logs"
      - "Validate data integrity"
      - "Update DNS/routing"

  pilot_light:
    architecture:
      primary_region: "us-east-1"
      dr_region: "us-west-2"

    always_on_components:
      - "Core databases (minimal capacity)"
      - "Data replication"
      - "Critical configuration"

    scaled_down_components:
      - "Application servers (stopped)"
      - "Web servers (stopped)"
      - "Load balancers (configured)"

    activation_process:
      - "Start stopped instances"
      - "Scale up databases"
      - "Deploy latest application code"
      - "Configure load balancers"
      - "Update DNS records"
      - "Validate functionality"

  warm_standby:
    architecture:
      primary_region: "us-east-1"
      dr_region: "eu-west-1"

    running_components:
      - "Scaled-down application stack"
      - "Active data replication"
      - "Minimal traffic handling"

    scaling_strategy:
      normal_capacity: "20%"
      failover_capacity: "100%"
      auto_scaling: "Enabled"

    failover_process:
      - "Scale up DR environment"
      - "Verify data synchronization"
      - "Update DNS with health checks"
      - "Monitor traffic shift"
      - "Validate full functionality"

  multi_site_active_active:
    architecture:
      regions:
        - "us-east-1 (primary)"
        - "eu-west-1 (active)"
        - "ap-southeast-1 (active)"

    traffic_distribution:
      method: "Geo-routing with health checks"
      load_balancing: "Cross-region"

    data_consistency:
      strategy: "Multi-master replication"
      conflict_resolution: "Last-write-wins or CRDT"

    benefits:
      - "Zero RTO for region failures"
      - "Improved global performance"
      - "Load distribution"
      - "No failover needed"

class AWSDRSolutions:
    def __init__(self):
        self.services = {
            'backup': 'AWS Backup',
            'replication': 'AWS DRS',
            'pilot_light': 'CloudFormation + AMIs',
            'multi_region': 'Route 53 + Multi-Region'
        }

    def implement_aws_backup(self):
        """Implement AWS Backup solution"""

        backup_configuration = {
            'backup_plan': {
                'name': 'ComprehensiveDRPlan',
                'rules': [
                    {
                        'name': 'DailyBackups',
                        'schedule': 'cron(0 5 ? * * *)',
                        'target_vault': 'Default',
                        'lifecycle': {
                            'move_to_cold_storage': 30,
                            'delete_after': 365
                        },
                        'copy_actions': [{
                            'destination_vault': 'arn:aws:backup:us-west-2:123456789012:vault:Default',
                            'lifecycle': {
                                'delete_after': 365
                            }
                        }]
                    },
                    {
                        'name': 'HourlyBackups',
                        'schedule': 'cron(0 * ? * * *)',
                        'target_vault': 'Critical',
                        'lifecycle': {
                            'delete_after': 7
                        }
                    }
                ]
            },

            'backup_selection': {
                'resources': [
                    'arn:aws:ec2:*:*:instance/*',
                    'arn:aws:rds:*:*:db:*',
                    'arn:aws:efs:*:*:file-system/*',
                    'arn:aws:dynamodb:*:*:table/*'
                ],
                'tags': {
                    'Backup': 'True',
                    'Environment': 'Production'
                }
            },

            'vault_configuration': {
                'encryption': 'aws/backup',
                'access_policy': 'restrict_delete',
                'vault_lock': {
                    'min_retention': 7,
                    'max_retention': 3650,
                    'changeable_for_days': 3
                }
            }
        }

        return backup_configuration

    def implement_aws_drs(self):
        """Implement AWS Disaster Recovery Service"""

        drs_configuration = {
            'replication_settings': {
                'staging_area': {
                    'subnet': 'subnet-dr-staging',
                    'instance_type': 't3.small',
                    'ebs_encryption': 'DEFAULT'
                },

                'replication_config': {
                    'bandwidth_throttling': 100,  # Mbps
                    'create_public_ip': False,
                    'data_plane_routing': 'PRIVATE_IP',
                    'default_large_staging_disk_type': 'GP3',
                    'replication_server_instance_type': 'm5.large',
                    'use_dedicated_replication_server': True
                },

                'launch_settings': {
                    'copy_private_ip': False,
                    'copy_tags': True,
                    'launch_disposition': 'STARTED',
                    'target_instance_type_right_sizing': 'BASIC'
                }
            },

            'recovery_process': '''
# Automated recovery script
import boto3
import time

def initiate_recovery(source_server_id):
    drs = boto3.client('drs')

    # Start recovery job
    response = drs.start_recovery(
        sourceServerIDs=[source_server_id],
        isDrillable=False
    )

    job_id = response['job']['jobID']

    # Monitor recovery progress
    while True:
        job = drs.describe_jobs(jobIDs=[job_id])['jobs'][0]
        if job['status'] == 'COMPLETED':
            print(f"Recovery completed: {job['participatingServers']}")
            break
        elif job['status'] == 'FAILED':
            raise Exception(f"Recovery failed: {job['statusMessage']}")
        time.sleep(30)

    return job['participatingServers']
            '''
        }

        return drs_configuration

azure_dr_solutions:
  azure_site_recovery:
    capabilities:
      - "Azure to Azure replication"
      - "On-premises to Azure"
      - "Automated failover"
      - "Non-disruptive testing"

    configuration:
      recovery_vault:
        name: "company-dr-vault"
        location: "West US 2"
        redundancy: "GeoRedundant"

      replication_policy:
        name: "24hour-retention-policy"
        recovery_point_retention: "24 hours"
        crash_consistent_frequency: "5 minutes"
        app_consistent_frequency: "60 minutes"

      protection:
        source_region: "East US"
        target_region: "West US 2"
        resource_groups:
          - "production-rg"
          - "database-rg"

      network_mapping:
        source_vnet: "/subscriptions/.../prod-vnet"
        target_vnet: "/subscriptions/.../dr-vnet"

      automation:
        recovery_plan:
          name: "ProductionFailover"
          groups:
            - name: "Database Tier"
              machines: ["sql-01", "sql-02"]
              pre_action: "Stop application servers"
              post_action: "Verify database connectivity"

            - name: "Application Tier"
              machines: ["app-01", "app-02", "app-03"]
              pre_action: "Verify database availability"
              post_action: "Start health checks"

            - name: "Web Tier"
              machines: ["web-01", "web-02"]
              pre_action: "Verify app tier"
              post_action: "Update load balancer"

  azure_backup:
    services:
      - "Azure VMs"
      - "SQL databases"
      - "File shares"
      - "Blobs"

    policies:
      critical_daily:
        frequency: "Daily"
        time: "02:00 AM"
        retention:
          daily: 7
          weekly: 4
          monthly: 12
          yearly: 5

      standard_weekly:
        frequency: "Weekly"
        time: "Sunday 02:00 AM"
        retention:
          weekly: 4
          monthly: 6

def implement_gcp_dr():
    """Implement GCP disaster recovery solutions"""

    gcp_dr_config = {
        'backup_and_dr': {
            'service': 'Backup and DR Service',
            'capabilities': [
                'Application-consistent backups',
                'Orchestrated recovery',
                'Cross-region replication',
                'Point-in-time recovery'
            ],

            'backup_plan': {
                'name': 'production-backup-plan',
                'resources': {
                    'compute_instances': {
                        'include_tags': ['production', 'critical'],
                        'exclude_tags': ['temporary', 'test']
                    },
                    'persistent_disks': {
                        'all_attached': True,
                        'snapshot_schedule': 'hourly'
                    }
                },

                'retention_policy': {
                    'daily': 7,
                    'weekly': 4,
                    'monthly': 12,
                    'yearly': 7
                },

                'replication': {
                    'target_region': 'us-west1',
                    'replication_frequency': 'continuous'
                }
            }
        },

        'regional_replication': {
            'compute_engine': {
                'instance_templates': 'Multi-regional',
                'instance_groups': {
                    'type': 'Regional managed',
                    'auto_healing': True,
                    'auto_scaling': True
                }
            },

            'cloud_sql': {
                'high_availability': True,
                'automated_backups': True,
                'point_in_time_recovery': True,
                'read_replicas': ['us-west1', 'europe-west1']
            },

            'cloud_storage': {
                'storage_class': 'Multi-regional',
                'versioning': True,
                'lifecycle_rules': [{
                    'action': 'SetStorageClass',
                    'storage_class': 'NEARLINE',
                    'age': 30
                }]
            }
        },

        'traffic_management': {
            'cloud_load_balancing': {
                'type': 'Global',
                'backend_services': [
                    {
                        'region': 'us-central1',
                        'capacity': 100,
                        'balancing_mode': 'UTILIZATION'
                    },
                    {
                        'region': 'us-west1',
                        'capacity': 100,
                        'balancing_mode': 'UTILIZATION'
                    }
                ],
                'health_checks': {
                    'interval': 10,
                    'timeout': 5,
                    'unhealthy_threshold': 3
                }
            }
        }
    }

    return gcp_dr_config

data_protection_tiers:
  tier_1_continuous_protection:
    description: "Real-time protection for critical data"
    technologies:
      - database_replication:
          sync_mode: "Synchronous"
          replicas: "Multi-AZ and Cross-Region"

      - change_data_capture:
          latency: "< 1 second"
          destinations: ["Data lake", "DR database"]

      - point_in_time_recovery:
          retention: "35 days"
          granularity: "1 second"

    use_cases:
      - "Transaction databases"
      - "Customer data"
      - "Financial records"

  tier_2_near_real_time:
    description: "Frequent protection with minimal data loss"
    technologies:
      - snapshot_replication:
          frequency: "Every 15 minutes"
          retention: "7 days"
          cross_region: true

      - async_replication:
          lag: "< 5 minutes"
          compression: true

      - backup_solutions:
          frequency: "Hourly"
          incremental: true

    use_cases:
      - "Application data"
      - "User files"
      - "Configuration data"

  tier_3_periodic_protection:
    description: "Regular protection for less critical data"
    technologies:
      - scheduled_backups:
          frequency: "Daily"
          retention: "30 days"

      - archive_storage:
          transition: "After 90 days"
          retrieval_time: "3-5 hours"

    use_cases:
      - "Log files"
      - "Reports"
      - "Development data"

class DatabaseReplication:
    def __init__(self):
        self.replication_configs = {}

    def configure_multi_region_replication(self, database_type):
        """Configure multi-region database replication"""

        if database_type == 'mysql':
            config = {
                'topology': 'master-slave with read replicas',
                'regions': {
                    'primary': {
                        'region': 'us-east-1',
                        'instance': 'db.r5.2xlarge',
                        'storage': 'io1',
                        'iops': 10000
                    },
                    'dr_replica': {
                        'region': 'us-west-2',
                        'instance': 'db.r5.2xlarge',
                        'replication': 'async',
                        'lag_alert': '60 seconds'
                    },
                    'read_replicas': [
                        {
                            'region': 'eu-west-1',
                            'instance': 'db.r5.xlarge',
                            'purpose': 'Read scaling'
                        }
                    ]
                },

                'failover_configuration': {
                    'automatic_failover': True,
                    'failover_timeout': 120,  # seconds
                    'promotion_tier': {
                        'dr_replica': 0,
                        'read_replicas': 1
                    }
                }
            }

        elif database_type == 'postgresql':
            config = {
                'topology': 'streaming replication with hot standby',
                'replication_slots': True,
                'wal_settings': {
                    'wal_level': 'replica',
                    'max_wal_senders': 10,
                    'wal_keep_segments': 64,
                    'hot_standby': True
                },
                'monitoring': {
                    'replication_lag': 'pg_stat_replication',
                    'alert_threshold': '100MB or 60 seconds'
                }
            }

        elif database_type == 'nosql':
            config = {
                'type': 'DynamoDB Global Tables',
                'regions': ['us-east-1', 'us-west-2', 'eu-west-1'],
                'consistency': 'Eventual',
                'conflict_resolution': 'Last writer wins',
                'backup': {
                    'point_in_time': True,
                    'on_demand': True,
                    'continuous': True
                }
            }

        return config

application_recovery:
  discovery_and_mapping:
    automated_discovery:
      - "Application dependencies"
      - "Configuration files"
      - "Database connections"
      - "External services"
      - "API endpoints"

    dependency_mapping:
      tools: ["AWS Application Discovery", "Azure Migrate", "ServiceNow"]
      output: "Recovery order determination"

  recovery_orchestration:
    phases:
      - phase: "Infrastructure Recovery"
        steps:
          - "Provision compute resources"
          - "Configure networking"
          - "Set up security groups"
          - "Mount storage volumes"

      - phase: "Data Recovery"
        steps:
          - "Restore databases"
          - "Verify data integrity"
          - "Sync latest changes"
          - "Update connection strings"

      - phase: "Application Recovery"
        steps:
          - "Deploy application code"
          - "Configure services"
          - "Start applications in order"
          - "Initialize connections"

      - phase: "Validation"
        steps:
          - "Health checks"
          - "Smoke tests"
          - "Performance validation"
          - "Security scans"

  recovery_runbooks:
    format: "Automated scripts with manual checkpoints"
    components:
      - "Pre-flight checks"
      - "Recovery execution"
      - "Validation tests"
      - "Rollback procedures"
      - "Communication templates"

class MicroservicesRecovery:
    def __init__(self):
        self.service_registry = {}
        self.recovery_order = []

    def create_recovery_plan(self):
        """Create recovery plan for microservices architecture"""

        recovery_strategy = {
            'service_categorization': {
                'stateless_services': {
                    'characteristics': 'No persistent state',
                    'recovery_method': 'Simple redeployment',
                    'recovery_time': '< 5 minutes',
                    'examples': ['API Gateway', 'Web Frontend', 'Processors']
                },

                'stateful_services': {
                    'characteristics': 'Maintains state',
                    'recovery_method': 'State restoration + deployment',
                    'recovery_time': '15-30 minutes',
                    'examples': ['Session Service', 'Cache Service', 'Queue Workers']
                },

                'data_services': {
                    'characteristics': 'Database and storage',
                    'recovery_method': 'Restore from replication/backup',
                    'recovery_time': '30-60 minutes',
                    'examples': ['User Database', 'Product Catalog', 'Order Database']
                }
            },

            'recovery_sequence': [
                {
                    'wave': 1,
                    'services': ['Network Infrastructure', 'Service Discovery', 'Configuration Service'],
                    'parallel': False
                },
                {
                    'wave': 2,
                    'services': ['Databases', 'Message Queues', 'Cache Services'],
                    'parallel': True
                },
                {
                    'wave': 3,
                    'services': ['Core Microservices', 'API Services'],
                    'parallel': True
                },
                {
                    'wave': 4,
                    'services': ['Frontend Services', 'Edge Services'],
                    'parallel': True
                }
            ],

            'circuit_breaker_config': {
                'initial_state': 'open',
                'health_check_interval': 30,
                'success_threshold': 3,
                'timeout': 60
            },

            'progressive_recovery': {
                'canary_percentage': 10,
                'validation_period': 300,  # seconds
                'auto_promotion': True,
                'rollback_on_error': True
            }
        }

        return recovery_strategy

    def implement_recovery_automation(self):
        """Implement automated recovery for microservices"""

        automation_code = '''
import asyncio
from kubernetes import client, config

class MicroserviceRecoveryOrchestrator:
    def __init__(self):
        config.load_incluster_config()
        self.k8s_apps_v1 = client.AppsV1Api()
        self.k8s_core_v1 = client.CoreV1Api()

    async def recover_services(self, recovery_plan):
        """Execute recovery plan for microservices"""

        for wave in recovery_plan['recovery_sequence']:
            if wave['parallel']:
                # Recover services in parallel
                tasks = [
                    self.recover_service(service)
                    for service in wave['services']
                ]
                await asyncio.gather(*tasks)
            else:
                # Recover services sequentially
                for service in wave['services']:
                    await self.recover_service(service)

            # Validate wave completion
            await self.validate_wave(wave['services'])

    async def recover_service(self, service_name):
        """Recover individual microservice"""

        # Scale up deployment
        await self.scale_deployment(service_name, replicas=3)

        # Wait for pods to be ready
        await self.wait_for_ready(service_name)

        # Perform health check
        if not await self.health_check(service_name):
            raise Exception(f"Service {service_name} failed health check")

        return True
        '''

        return automation_code

dr_testing_framework:
  test_types:
    tabletop_exercise:
      frequency: "Quarterly"
      participants: ["IT", "Business", "Leadership"]
      duration: "2-4 hours"
      scenarios:
        - "Region failure"
        - "Cyber attack"
        - "Data corruption"
        - "Human error"

    component_testing:
      frequency: "Monthly"
      scope: "Individual components"
      tests:
        - "Backup restoration"
        - "Replication verification"
        - "Failover mechanisms"
        - "Network connectivity"

    integrated_testing:
      frequency: "Semi-annually"
      scope: "End-to-end application"
      tests:
        - "Full application failover"
        - "Data consistency validation"
        - "Performance benchmarking"
        - "User acceptance testing"

    full_dr_drill:
      frequency: "Annually"
      scope: "Complete environment"
      duration: "1-2 days"
      validation:
        - "RTO achievement"
        - "RPO compliance"
        - "Process effectiveness"
        - "Team readiness"

  testing_automation:
    chaos_engineering:
      tools: ["Chaos Monkey", "Gremlin", "Litmus"]
      scenarios:
        - "Random instance termination"
        - "Network partitioning"
        - "Resource exhaustion"
        - "Clock skew"

    automated_validation:
      health_checks:
        - endpoint: "/health"
          expected_status: 200
          timeout: 30

      data_validation:
        - "Row count comparison"
        - "Checksum verification"
        - "Business rule validation"
        - "Referential integrity"

      performance_validation:
        - metric: "Response time"
          threshold: "< 500ms p95"
        - metric: "Throughput"
          threshold: "> 1000 TPS"
        - metric: "Error rate"
          threshold: "< 0.1%"

class DRTestExecutor:
    def __init__(self):
        self.test_results = {}
        self.validators = {}

    def execute_dr_test(self, test_type):
        """Execute DR test and generate report"""

        test_execution = {
            'pre_test': {
                'checklist': [
                    'Notify stakeholders',
                    'Document current state',
                    'Prepare rollback plan',
                    'Set up monitoring'
                ],
                'baseline_metrics': self.capture_baseline_metrics()
            },

            'test_execution': {
                'steps': self.get_test_steps(test_type),
                'timing': self.record_timing(),
                'issues': self.track_issues(),
                'observations': self.capture_observations()
            },

            'validation': {
                'functional_tests': {
                    'login_functionality': self.test_login(),
                    'core_transactions': self.test_transactions(),
                    'api_endpoints': self.test_apis(),
                    'data_integrity': self.verify_data_integrity()
                },

                'performance_tests': {
                    'response_time': self.measure_response_time(),
                    'throughput': self.measure_throughput(),
                    'resource_utilization': self.check_resource_usage()
                },

                'recovery_metrics': {
                    'actual_rto': self.calculate_rto(),
                    'actual_rpo': self.calculate_rpo(),
                    'data_loss': self.assess_data_loss()
                }
            },

            'post_test': {
                'cleanup': [
                    'Failback procedures',
                    'Resource cleanup',
                    'Documentation update',
                    'Lessons learned'
                ]
            }
        }

        return self.generate_test_report(test_execution)

    def generate_test_report(self, test_data):
        """Generate comprehensive DR test report"""

        report_template = {
            'executive_summary': {
                'test_date': test_data['timestamp'],
                'test_type': test_data['type'],
                'overall_result': 'PASS/FAIL',
                'rto_achieved': test_data['validation']['recovery_metrics']['actual_rto'],
                'rpo_achieved': test_data['validation']['recovery_metrics']['actual_rpo'],
                'key_findings': self.summarize_findings(test_data)
            },

            'detailed_results': {
                'timeline': self.create_timeline(test_data),
                'metrics_comparison': {
                    'target_vs_actual': self.compare_metrics(test_data),
                    'performance_impact': self.analyze_performance(test_data)
                },
                'issues_encountered': test_data['test_execution']['issues'],
                'resolutions': self.document_resolutions(test_data)
            },

            'recommendations': {
                'immediate_actions': self.identify_immediate_actions(test_data),
                'process_improvements': self.suggest_improvements(test_data),
                'infrastructure_changes': self.recommend_changes(test_data),
                'training_needs': self.identify_training_gaps(test_data)
            },

            'appendices': {
                'detailed_logs': 'Link to detailed logs',
                'screenshots': 'Evidence collection',
                'participant_feedback': 'Team observations',
                'metrics_data': 'Raw performance data'
            }
        }

        return report_template

dr_automation_platform:
  orchestration_engine:
    tools:
      - aws: "AWS Systems Manager"
      - azure: "Azure Automation"
      - gcp: "Cloud Composer"
      - multi_cloud: "Terraform + Ansible"

    capabilities:
      - "Automated failover execution"
      - "Runbook automation"
      - "Health check monitoring"
      - "Notification management"
      - "Audit logging"

  automation_workflows:
    detection:
      monitoring_sources:
        - "CloudWatch/Azure Monitor/Stackdriver"
        - "Application health endpoints"
        - "Synthetic monitoring"
        - "User reports"

      alert_correlation:
        - "Multiple signal validation"
        - "False positive filtering"
        - "Severity assessment"
        - "Blast radius calculation"

    decision:
      automated_decisions:
        - condition: "Single AZ failure"
          action: "Automatic failover to healthy AZ"

        - condition: "Region-wide outage"
          action: "Initiate DR with manual approval"

        - condition: "Data corruption detected"
          action: "Stop replication, alert team"

      approval_workflow:
        - "Incident commander notification"
        - "Impact assessment"
        - "Stakeholder approval"
        - "Execution authorization"

    execution:
      parallel_tasks:
        - "Infrastructure provisioning"
        - "Data restoration"
        - "Application deployment"
        - "Configuration updates"

      sequential_tasks:
        - "Pre-flight validation"
        - "Service startup order"
        - "Health verification"
        - "Traffic cutover"

    validation:
      automated_tests:
        - "Connectivity tests"
        - "Application health checks"
        - "Data integrity verification"
        - "Performance benchmarks"

      manual_checkpoints:
        - "Business validation"
        - "Security review"
        - "Go/No-go decision"
        - "Final approval"

def create_dr_infrastructure_code():
    """Create IaC templates for DR infrastructure"""

    terraform_dr_module = '''
# DR Infrastructure Module
module "dr_infrastructure" {
  source = "./modules/dr-infrastructure"

  primary_region = var.primary_region
  dr_region      = var.dr_region

  # Network Configuration
  dr_vpc_cidr = "10.100.0.0/16"

  dr_subnets = {
    public  = ["10.100.1.0/24", "10.100.2.0/24"]
    private = ["10.100.10.0/24", "10.100.11.0/24"]
    data    = ["10.100.20.0/24", "10.100.21.0/24"]
  }

  # Cross-region networking
  enable_vpc_peering        = true
  enable_transit_gateway    = true

  # Database replication
  enable_rds_read_replica   = true
  enable_dynamodb_global    = true

  # Compute resources (Pilot Light mode)
  dr_instance_count = 0  # Will be scaled during failover
  dr_instance_type  = "t3.medium"

  # Backup configuration
  backup_retention_days = 30
  enable_cross_region_backup = true

  # Monitoring and alerting
  enable_dr_monitoring = true
  alert_email = var.ops_team_email

  tags = {
    Environment = "DR"
    ManagedBy   = "Terraform"
    CostCenter  = "Operations"
  }
}

# DR Activation Script
resource "local_file" "dr_activation" {
  filename = "${path.module}/scripts/activate_dr.sh"

  content = <<-EOT
    #!/bin/bash
    # DR Activation Script

    echo "Starting DR activation..."

    # Scale up DR instances
    terraform apply -var="dr_instance_count=10" -auto-approve

    # Update DNS records
    aws route53 change-resource-record-sets \
      --hosted-zone-id ${var.hosted_zone_id} \
      --change-batch file://dns-failover.json

    # Verify health checks
    ./scripts/verify_dr_health.sh

    echo "DR activation complete"
  EOT
}
    '''

    return terraform_dr_module

dr_cost_optimization:
  strategies:
    pilot_light_optimization:
      description: "Minimize standby costs"
      techniques:
        - "Use smallest instance sizes for standby"
        - "Stop non-critical instances"
        - "Use spot instances for testing"
        - "Implement automated start/stop"

      savings: "60-80% vs always-on"

    backup_optimization:
      lifecycle_policies:
        - hot_storage: "7 days"
          warm_storage: "30 days"  
          cold_storage: "365 days"

      compression: "Enable for all backups"
      deduplication: "Block-level dedup"
      incremental: "After initial full"

      savings: "40-60% storage costs"

    replication_optimization:
      techniques:
        - "Compress replication traffic"
        - "Use dedicated network connections"
        - "Replicate only critical data"
        - "Adjust replication frequency"

      network_savings: "30-50% bandwidth costs"

    testing_cost_management:
      approaches:
        - "Use isolated test environments"
        - "Automated environment teardown"
        - "Spot instances for testing"
        - "Time-boxed test windows"

      budget_controls:
        - "Cost alerts at 80% threshold"
        - "Auto-shutdown after tests"
        - "Resource tagging for tracking"

  cost_models:
    backup_and_restore:
      monthly_cost:
        storage: "$500-2000"
        compute: "$0 (on-demand during recovery)"
        network: "$100-500"
        total: "$600-2500"

    pilot_light:
      monthly_cost:
        storage: "$500-2000"
        compute: "$500-2000 (minimal instances)"
        network: "$200-1000"
        database: "$500-1500"
        total: "$1700-6500"

    warm_standby:
      monthly_cost:
        storage: "$1000-3000"
        compute: "$2000-8000 (scaled down)"
        network: "$500-2000"
        database: "$1000-3000"
        total: "$4500-16000"

    multi_site_active:
      monthly_cost:
        storage: "$2000-5000"
        compute: "$8000-20000 (full capacity)"
        network: "$2000-5000"
        database: "$3000-8000"
        total: "$15000-38000"

class DRCostOptimizer:
    def __init__(self):
        self.cost_models = {}

    def calculate_dr_costs(self, strategy, workload):
        """Calculate DR costs for different strategies"""

        cost_calculation = {
            'infrastructure_costs': {
                'compute': self.calculate_compute_costs(strategy, workload),
                'storage': self.calculate_storage_costs(strategy, workload),
                'network': self.calculate_network_costs(strategy, workload),
                'database': self.calculate_database_costs(strategy, workload)
            },

            'operational_costs': {
                'monitoring': 100,  # Fixed monthly
                'testing': self.calculate_testing_costs(strategy),
                'management': self.calculate_management_overhead(strategy)
            },

            'optimization_opportunities': {
                'reserved_instances': {
                    'applicable': strategy in ['warm_standby', 'multi_site'],
                    'savings': '30-70%',
                    'recommendation': 'Use RIs for predictable DR capacity'
                },

                'spot_instances': {
                    'applicable': strategy in ['backup_restore', 'pilot_light'],
                    'savings': '60-90%',
                    'recommendation': 'Use for non-critical DR testing'
                },

                'storage_tiering': {
                    'applicable': True,
                    'savings': '50-80%',
                    'recommendation': 'Move old backups to archive storage'
                },

                'network_optimization': {
                    'applicable': True,
                    'savings': '20-40%',
                    'recommendation': 'Use private connectivity and compression'
                }
            },

            'total_monthly_cost': sum([
                sum(self.infrastructure_costs.values()),
                sum(self.operational_costs.values())
            ]),

            'annual_cost': self.total_monthly_cost * 12,

            'cost_per_protected_gb': self.total_monthly_cost / workload['data_size_gb'],

            'roi_analysis': {
                'downtime_cost_per_hour': workload['hourly_downtime_cost'],
                'expected_outages_per_year': 2,
                'potential_loss_without_dr': self.calculate_potential_loss(workload),
                'dr_investment_payback': self.calculate_payback_period(workload)
            }
        }

        return cost_calculation

    def optimize_dr_spending(self, current_config):
        """Provide recommendations to optimize DR spending"""

        optimization_plan = {
            'immediate_savings': [
                {
                    'action': 'Right-size DR instances',
                    'effort': 'Low',
                    'savings': '20-40%',
                    'implementation': 'Analyze utilization and downsize'
                },
                {
                    'action': 'Implement lifecycle policies',
                    'effort': 'Low',
                    'savings': '30-60%',
                    'implementation': 'Move old backups to cold storage'
                },
                {
                    'action': 'Schedule resource shutdown',
                    'effort': 'Medium',
                    'savings': '40-70%',
                    'implementation': 'Stop non-critical DR resources outside business hours'
                }
            ],

            'medium_term_optimization': [
                {
                    'action': 'Negotiate committed use discounts',
                    'effort': 'Medium',
                    'savings': '20-50%',
                    'implementation': 'Commit to 1-3 year terms for steady-state DR'
                },
                {
                    'action': 'Implement incremental backups',
                    'effort': 'Medium',
                    'savings': '40-60%',
                    'implementation': 'Reduce full backup frequency'
                },
                {
                    'action': 'Optimize replication traffic',
                    'effort': 'High',
                    'savings': '30-50%',
                    'implementation': 'Implement compression and deduplication'
                }
            ],

            'strategic_optimization': [
                {
                    'action': 'Re-evaluate DR strategy by tier',
                    'effort': 'High',
                    'savings': '40-60%',
                    'implementation': 'Match DR strategy to actual business requirements'
                },
                {
                    'action': 'Implement automated testing',
                    'effort': 'High',
                    'savings': '20-30%',
                    'implementation': 'Reduce manual testing costs'
                }
            ]
        }

        return optimization_plan

implementation_phases:
  phase_1_assessment:
    duration: "2-4 weeks"
    activities:
      - business_impact_analysis:
          deliverable: "Application criticality matrix"

      - current_state_assessment:
          deliverable: "Infrastructure inventory"

      - risk_assessment:
          deliverable: "Risk register and mitigation plan"

      - requirements_gathering:
          deliverable: "RTO/RPO requirements document"

    outputs:
      - "DR strategy recommendation"
      - "High-level design"
      - "Budget estimation"
      - "Project timeline"

  phase_2_design:
    duration: "3-4 weeks"
    activities:
      - architecture_design:
          components:
            - "Network topology"
            - "Compute architecture"
            - "Storage design"
            - "Database strategy"

      - security_design:
          components:
            - "Access controls"
            - "Encryption strategy"
            - "Network security"
            - "Compliance mapping"

      - operational_design:
          components:
            - "Monitoring strategy"
            - "Automation framework"
            - "Testing procedures"
            - "Runbook templates"

    outputs:
      - "Detailed design documents"
      - "Implementation runbooks"
      - "Test plans"
      - "Training materials"

  phase_3_implementation:
    duration: "8-12 weeks"
    activities:
      - infrastructure_setup:
          week_1_2:
            - "Provision DR environment"
            - "Configure networking"
            - "Set up security"

          week_3_4:
            - "Implement backup solutions"
            - "Configure replication"
            - "Deploy monitoring"

      - application_configuration:
          week_5_6:
            - "Install applications"
            - "Configure databases"
            - "Set up data sync"

          week_7_8:
            - "Implement automation"
            - "Configure orchestration"
            - "Document procedures"

      - testing_and_validation:
          week_9_10:
            - "Component testing"
            - "Integration testing"
            - "Performance testing"

          week_11_12:
            - "Full DR drill"
            - "Issue remediation"
            - "Final validation"

  phase_4_operationalization:
    duration: "2-3 weeks"
    activities:
      - knowledge_transfer:
          - "Team training"
          - "Runbook walkthroughs"
          - "Escalation procedures"

      - process_integration:
          - "Incident management"
          - "Change management"
          - "Testing schedules"

      - continuous_improvement:
          - "Metrics tracking"
          - "Regular reviews"
          - "Optimization planning"

def generate_implementation_checklist():
    """Generate comprehensive DR implementation checklist"""

    checklist = {
        'pre_implementation': [
            {
                'task': 'Executive sponsorship secured',
                'owner': 'Project Manager',
                'status': 'checkbox'
            },
            {
                'task': 'Budget approved',
                'owner': 'Finance',
                'status': 'checkbox'
            },
            {
                'task': 'Team resources allocated',
                'owner': 'IT Management',
                'status': 'checkbox'
            },
            {
                'task': 'Compliance requirements identified',
                'owner': 'Compliance Team',
                'status': 'checkbox'
            }
        ],

        'technical_implementation': [
            {
                'category': 'Infrastructure',
                'tasks': [
                    'DR region selected',
                    'Network connectivity established',
                    'Security groups configured',
                    'IAM roles created',
                    'Monitoring enabled'
                ]
            },
            {
                'category': 'Data Protection',
                'tasks': [
                    'Backup policies configured',
                    'Replication enabled',
                    'Retention policies set',
                    'Encryption configured',
                    'Cross-region copy enabled'
                ]
            },
            {
                'category': 'Applications',
                'tasks': [
                    'Application inventory completed',
                    'Dependencies mapped',
                    'DR configurations applied',
                    'Automation scripts created',
                    'Health checks configured'
                ]
            }
        ],

        'operational_readiness': [
            {
                'category': 'Documentation',
                'tasks': [
                    'Runbooks created',
                    'Architecture diagrams updated',
                    'Contact lists current',
                    'Escalation procedures defined',
                    'Recovery procedures documented'
                ]
            },
            {
                'category': 'Testing',
                'tasks': [
                    'Test plan approved',
                    'Test environment ready',
                    'Test data prepared',
                    'Success criteria defined',
                    'Rollback procedures tested'
                ]
            },
            {
                'category': 'Training',
                'tasks': [
                    'Team training completed',
                    'Tabletop exercises conducted',
                    'Technical drills performed',
                    'Lessons learned documented',
                    'Knowledge base updated'
                ]
            }
        ],

        'go_live_criteria': [
            'All critical systems protected',
            'RTO/RPO targets validated',
            'Monitoring alerts configured',
            'Team trained and ready',
            'Management approval received'
        ]
    }

    return checklist

dr_best_practices:
  planning:
    - "Start with business requirements, not technology"
    - "Document everything, automate everything possible"
    - "Plan for partial failures, not just complete disasters"
    - "Consider regulatory and compliance requirements"
    - "Include all stakeholders in planning"

  design:
    - "Keep it simple - complexity is the enemy of reliability"
    - "Design for automation from the start"
    - "Use cloud-native services where possible"
    - "Implement defense in depth"
    - "Plan for data gravity and transfer costs"

  implementation:
    - "Start with pilot applications"
    - "Implement in phases, validate each phase"
    - "Use infrastructure as code"
    - "Implement comprehensive monitoring"
    - "Document all procedures and decisions"

  testing:
    - "Test regularly and automatically"
    - "Test partial failures, not just complete disasters"
    - "Include business validation in tests"
    - "Document and fix all issues found"
    - "Gradually increase test complexity"

  operations:
    - "Monitor continuously, alert intelligently"
    - "Keep runbooks current"
    - "Regular training and drills"
    - "Track metrics and improve continuously"
    - "Stay current with cloud provider features"

  common_mistakes:
    - "Focusing only on technology, ignoring people and process"
    - "Not testing regularly or realistically"
    - "Underestimating data transfer time and costs"
    - "Ignoring application dependencies"
    - "Not updating DR plans as systems change"