# Cloud Bursting Configuration
architecture:
  name: "E-commerce Cloud Burst"
  components:
    on_premises:
      - web_servers: 10
      - app_servers: 15
      - database: "Oracle RAC"
    cloud_burst:
      trigger:
        - cpu_threshold: 80%
        - response_time: ">2 seconds"
      cloud_resources:
        - auto_scaling_group:
            min: 0
            max: 50
            instance_type: "c5.2xlarge"
      load_balancer:
        type: "Global"
        health_check: "/api/health"

class HybridStorageTier:
    def __init__(self):
        self.tiers = {
            'hot': {
                'location': 'on-premises-ssd',
                'capacity': '100TB',
                'access_pattern': 'frequent',
                'retention': '30 days'
            },
            'warm': {
                'location': 'on-premises-hdd',
                'capacity': '500TB',
                'access_pattern': 'occasional',
                'retention': '90 days'
            },
            'cold': {
                'location': 'aws-s3-ia',
                'capacity': 'unlimited',
                'access_pattern': 'rare',
                'retention': '365 days'
            },
            'archive': {
                'location': 'aws-glacier',
                'capacity': 'unlimited',
                'access_pattern': 'very-rare',
                'retention': '7 years'
            }
        }

    def implement_lifecycle_policy(self):
        policy = {
            'rules': [
                {
                    'name': 'move-to-warm',
                    'condition': 'last_accessed > 30 days',
                    'action': 'move_to_tier(warm)'
                },
                {
                    'name': 'move-to-cloud',
                    'condition': 'last_accessed > 90 days',
                    'action': 'move_to_tier(cold)'
                },
                {
                    'name': 'archive',
                    'condition': 'last_accessed > 365 days',
                    'action': 'move_to_tier(archive)'
                }
            ]
        }
        return policy

// Microservices Distribution Strategy
const hybridAppArchitecture = {
  services: {
    // Core services remain on-premises
    'customer-database': {
      location: 'on-premises',
      reason: 'regulatory-compliance',
      technology: 'Oracle',
      ha: 'active-standby'
    },
    'payment-processor': {
      location: 'on-premises',
      reason: 'pci-compliance',
      technology: 'Java-Spring',
      ha: 'active-active'
    },

    // Scalable services in cloud
    'web-frontend': {
      location: 'aws',
      reason: 'scalability',
      technology: 'React',
      deployment: 'CloudFront + S3'
    },
    'api-gateway': {
      location: 'aws',
      reason: 'global-reach',
      technology: 'API Gateway',
      deployment: 'multi-region'
    },
    'analytics-engine': {
      location: 'aws',
      reason: 'big-data-processing',
      technology: 'EMR + Spark',
      deployment: 'on-demand'
    }
  },

  communication: {
    'on-prem-to-cloud': 'VPN + Direct Connect',
    'service-mesh': 'Istio',
    'api-management': 'Kong'
  }
};

# Deploy VMware Cloud Foundation
$vcfConfig = @{
    ManagementDomain = @{
        Name = "mgmt-domain"
        vCenter = @{
            Hostname = "vcenter.corp.local"
            Version = "7.0"
        }
        NSX = @{
            Manager = "nsxmgr.corp.local"
            Version = "3.2"
        }
        vSAN = @{
            Enabled = $true
            DiskGroups = 2
        }
    }

    WorkloadDomains = @(
        @{
            Name = "prod-workload"
            Clusters = 3
            HostsPerCluster = 4
        }
    )

    CloudIntegration = @{
        AWS = @{
            Enabled = $true
            Region = "us-east-1"
            SDDC = "vmware-cloud-aws"
        }
    }
}

# Deploy hybrid connectivity
Enable-HybridCloudExtension -Config $vcfConfig

# Enable Azure Arc for hybrid management
# Register resource providers
az provider register --namespace Microsoft.HybridCompute
az provider register --namespace Microsoft.GuestConfiguration
az provider register --namespace Microsoft.Kubernetes

# Connect on-premises servers
azcmagent connect \
  --resource-group "HybridRG" \
  --tenant-id $TENANT_ID \
  --location "eastus" \
  --subscription-id $SUBSCRIPTION_ID

# Apply Azure policies to on-premises resources
az policy assignment create \
  --name "HybridCompliance" \
  --scope "/subscriptions/$SUBSCRIPTION_ID/resourceGroups/HybridRG" \
  --policy "/providers/Microsoft.Authorization/policyDefinitions/hybrid-baseline"

# Terraform - Multi-cloud VPN setup
resource "aws_vpn_connection" "hybrid" {
  vpn_gateway_id      = aws_vpn_gateway.main.id
  customer_gateway_id = aws_customer_gateway.onprem.id
  type               = "ipsec.1"
  static_routes_only = false

  tags = {
    Name = "Hybrid-Cloud-VPN"
  }
}

resource "azurerm_virtual_network_gateway_connection" "hybrid" {
  name                = "hybrid-vpn-connection"
  location            = azurerm_resource_group.main.location
  resource_group_name = azurerm_resource_group.main.name

  type                       = "IPsec"
  virtual_network_gateway_id = azurerm_virtual_network_gateway.main.id
  peer_virtual_network_gateway_id = null
  local_network_gateway_id   = azurerm_local_network_gateway.onprem.id

  shared_key = var.vpn_shared_key

  ipsec_policy {
    dh_group         = "DHGroup14"
    ike_encryption   = "AES256"
    ike_integrity    = "SHA256"
    ipsec_encryption = "AES256"
    ipsec_integrity  = "SHA256"
    pfs_group        = "PFS2048"
    sa_lifetime      = 3600
  }
}

# Configure AWS Direct Connect and Azure ExpressRoute
class HybridNetworkManager:
    def __init__(self):
        self.providers = {
            'aws': boto3.client('directconnect'),
            'azure': AzureNetworkClient(),
            'gcp': GoogleInterconnectClient()
        }

    def provision_dedicated_connection(self, provider, bandwidth):
        """Provision dedicated network connection"""

        configs = {
            'aws': {
                'connectionName': 'Hybrid-DX-Connection',
                'bandwidth': bandwidth,  # 1Gbps, 10Gbps, 100Gbps
                'location': 'EqDC2',
                'vlan': 100,
                'BGP': {
                    'asn': 65000,
                    'authKey': self.generate_bgp_key()
                }
            },
            'azure': {
                'name': 'Hybrid-ER-Circuit',
                'serviceProviderName': 'Equinix',
                'peeringLocation': 'Washington DC',
                'bandwidthInMbps': bandwidth * 1000,
                'sku': {
                    'name': 'Standard_MeteredData',
                    'tier': 'Standard',
                    'family': 'MeteredData'
                }
            }
        }

        if provider == 'aws':
            connection = self.providers['aws'].create_connection(
                **configs['aws']
            )
            self.configure_virtual_interfaces(connection['connectionId'])

        elif provider == 'azure':
            circuit = self.providers['azure'].create_express_route_circuit(
                **configs['azure']
            )
            self.configure_peering(circuit.id)

        return connection

# Network topology configuration
network_topology:
  hub:
    name: "central-hub"
    location: "on-premises-datacenter"
    components:
      - firewall: "Palo Alto PA-5220"
      - router: "Cisco ASR-1001"
      - switches: "Cisco Nexus 9000"

    connections:
      aws:
        type: "direct-connect"
        bandwidth: "10Gbps"
        vlan_id: 100
        bgp_asn: 65001

      azure:
        type: "express-route"
        bandwidth: "10Gbps"
        vlan_id: 200
        bgp_asn: 65002

      gcp:
        type: "partner-interconnect"
        bandwidth: "10Gbps"
        vlan_id: 300
        bgp_asn: 65003

  spokes:
    - name: "production"
      vlan_range: "10.1.0.0/16"
      services: ["web", "app", "database"]

    - name: "development"
      vlan_range: "10.2.0.0/16"
      services: ["dev", "test", "staging"]

    - name: "dmz"
      vlan_range: "10.254.0.0/16"
      services: ["proxy", "waf", "ids"]

# Implement Zero Trust for Hybrid Cloud
class ZeroTrustController:
    def __init__(self):
        self.policy_engine = PolicyEngine()
        self.identity_provider = IdentityProvider()
        self.network_controller = NetworkController()

    def enforce_zero_trust(self, request):
        """Enforce zero trust principles for every request"""

        # 1. Verify identity
        identity = self.identity_provider.verify_identity(
            token=request.auth_token,
            mfa_required=True
        )

        if not identity.is_valid:
            raise AuthenticationError("Invalid identity")

        # 2. Check device compliance
        device = self.check_device_compliance(request.device_id)
        if not device.is_compliant:
            raise SecurityError("Device not compliant")

        # 3. Verify network location
        network_context = self.network_controller.get_context(
            source_ip=request.source_ip,
            destination=request.destination
        )

        # 4. Apply least privilege access
        permissions = self.policy_engine.get_permissions(
            identity=identity,
            resource=request.resource,
            action=request.action,
            context=network_context
        )

        # 5. Encrypt in transit
        if not request.is_encrypted:
            request = self.encrypt_request(request)

        # 6. Log for audit
        self.audit_logger.log(
            identity=identity,
            action=request.action,
            resource=request.resource,
            result=permissions.decision
        )

        return permissions

# Hybrid Cloud Compliance Configuration
compliance_framework:
  regulations:
    - name: "GDPR"
      requirements:
        - data_residency: "EU"
        - encryption: "AES-256"
        - audit_retention: "3 years"
        - right_to_deletion: true

      implementation:
        on_premises:
          - customer_data: "Frankfurt DC"
          - encryption_keys: "HSM"

        cloud:
          - analytics: "AWS eu-central-1"
          - backups: "Azure Germany Central"

    - name: "HIPAA"
      requirements:
        - encryption_at_rest: true
        - encryption_in_transit: true
        - access_controls: "RBAC"
        - audit_trail: "complete"

      implementation:
        on_premises:
          - phi_data: "Primary DC"
          - access_control: "Active Directory"

        cloud:
          - disaster_recovery: "AWS HIPAA-compliant"
          - analytics: "de-identified data only"

    - name: "PCI-DSS"
      requirements:
        - network_segmentation: true
        - vulnerability_scanning: "quarterly"
        - encryption: "TLS 1.2+"

      implementation:
        on_premises:
          - payment_processing: "Isolated VLAN"
          - key_management: "Hardware HSM"

        cloud:
          - tokenization: "AWS Payment Cryptography"
          - logging: "CloudTrail + SIEM"

// Unified IAM for Hybrid Cloud
const HybridIAMStrategy = {
  identityProviders: {
    primary: {
      type: 'Active Directory',
      location: 'on-premises',
      syncTo: ['AzureAD', 'AWS-SSO', 'GCP-Identity']
    },

    federation: {
      protocol: 'SAML 2.0',
      providers: [
        {
          name: 'AWS',
          endpoint: 'https://signin.aws.amazon.com/saml',
          certificateThumbprint: 'xxx'
        },
        {
          name: 'Azure',
          endpoint: 'https://login.microsoftonline.com/tenant/saml2',
          certificateThumbprint: 'yyy'
        }
      ]
    }
  },

  policies: {
    mfaRequired: ['production', 'administrative'],

    conditionalAccess: [
      {
        name: 'Require MFA for cloud access',
        conditions: {
          locations: ['cloud'],
          userRisk: ['medium', 'high']
        },
        controls: {
          mfa: 'required',
          trustedDevice: 'preferred'
        }
      }
    ],

    privilegedAccess: {
      justInTime: true,
      maxDuration: '8 hours',
      approvalRequired: true,
      breakGlassAccounts: 2
    }
  }
};

class HybridDataManager:
    def __init__(self):
        self.data_catalog = DataCatalog()
        self.sync_engine = DataSyncEngine()
        self.governance = DataGovernance()

    def design_data_architecture(self):
        """Design hybrid data architecture"""

        architecture = {
            'data_sources': {
                'transactional': {
                    'primary': 'on-premises-oracle',
                    'replicas': ['aws-rds-oracle', 'azure-sql-mi'],
                    'sync_method': 'Oracle GoldenGate',
                    'rpo': '5 minutes',
                    'rto': '30 minutes'
                },

                'analytical': {
                    'warehouse': 'on-premises-teradata',
                    'cloud_warehouse': 'snowflake',
                    'data_lake': 'aws-s3',
                    'processing': 'spark-on-emr',
                    'sync_method': 'batch-etl',
                    'frequency': 'hourly'
                },

                'streaming': {
                    'ingestion': 'kafka-on-premises',
                    'processing': 'kinesis-analytics',
                    'storage': 'timestream',
                    'latency': '<1 second'
                }
            },

            'data_governance': {
                'catalog': 'aws-glue-catalog',
                'lineage': 'apache-atlas',
                'quality': 'great-expectations',
                'security': {
                    'classification': 'automatic',
                    'encryption': 'field-level',
                    'masking': 'dynamic'
                }
            }
        }

        return architecture

    def implement_data_sync(self, source, target, method='cdc'):
        """Implement data synchronization"""

        if method == 'cdc':
            # Change Data Capture implementation
            sync_config = {
                'source': source,
                'target': target,
                'capture_instance': f'{source.db}_{source.table}_CT',
                'retention_period': 72,  # hours
                'sync_frequency': 'real-time',
                'conflict_resolution': 'source-wins'
            }

            # Set up CDC
            self.setup_cdc(source, sync_config)
            self.create_sync_job(sync_config)

        elif method == 'batch':
            # Batch ETL implementation
            etl_config = {
                'source': source,
                'target': target,
                'schedule': '0 */4 * * *',  # Every 4 hours
                'mode': 'incremental',
                'watermark_column': 'last_modified',
                'parallel_threads': 10
            }

            self.create_etl_pipeline(etl_config)

-- Hybrid data lifecycle policies
CREATE OR REPLACE PROCEDURE manage_data_lifecycle()
AS $$
BEGIN
    -- Hot data (0-30 days): Keep on high-performance on-premises storage
    -- Warm data (31-90 days): Move to cloud object storage
    -- Cold data (91-365 days): Move to cloud archive storage
    -- Frozen data (>365 days): Move to glacier/deep archive

    -- Move warm data to cloud
    INSERT INTO cloud_staging.warm_data
    SELECT * FROM on_prem.hot_data
    WHERE last_accessed < CURRENT_DATE - INTERVAL '30 days'
      AND last_accessed >= CURRENT_DATE - INTERVAL '90 days';

    -- Archive cold data
    EXECUTE aws_s3_archive(
        source_table := 'warm_data',
        destination_bucket := 'cold-data-archive',
        storage_class := 'STANDARD_IA',
        where_clause := 'last_accessed < CURRENT_DATE - INTERVAL ''90 days'''
    );

    -- Deep archive frozen data
    EXECUTE aws_s3_archive(
        source_table := 'cold_data',
        destination_bucket := 'frozen-data-archive',
        storage_class := 'GLACIER_DEEP_ARCHIVE',
        where_clause := 'last_accessed < CURRENT_DATE - INTERVAL ''365 days'''
    );

    -- Clean up moved data
    DELETE FROM on_prem.hot_data
    WHERE last_accessed < CURRENT_DATE - INTERVAL '30 days';

END;
$$ LANGUAGE plpgsql;

-- Schedule lifecycle management
CREATE EXTENSION IF NOT EXISTS pg_cron;
SELECT cron.schedule('data-lifecycle', '0 2 * * *', 'CALL manage_data_lifecycle()');

# Application modernization roadmap
modernization_roadmap:
  assessment_criteria:
    - business_value: "high/medium/low"
    - technical_debt: "score 1-10"
    - cloud_readiness: "percentage"
    - dependencies: "count"

  waves:
    wave_1_lift_and_shift:
      timeline: "Q1 2024"
      applications:
        - name: "HR System"
          current: "Windows Server + SQL Server"
          target: "EC2 + RDS SQL Server"
          changes: "minimal"

        - name: "File Server"
          current: "Windows File Server"
          target: "FSx for Windows"
          changes: "configuration only"

    wave_2_replatform:
      timeline: "Q2-Q3 2024"
      applications:
        - name: "Web Portal"
          current: "IIS + .NET Framework"
          target: "App Service + .NET Core"
          changes: "framework upgrade"

        - name: "Inventory System"
          current: "Java 8 + Oracle"
          target: "EKS + Aurora PostgreSQL"
          changes: "containerization + db migration"

    wave_3_refactor:
      timeline: "Q4 2024 - Q1 2025"
      applications:
        - name: "Order Processing"
          current: "Monolithic Java"
          target: "Microservices on Lambda"
          changes: "complete refactoring"

        - name: "Analytics Platform"
          current: "On-prem Hadoop"
          target: "EMR + Athena + QuickSight"
          changes: "architecture redesign"

# Implement common hybrid application patterns
class HybridApplicationPatterns:

    def implement_strangler_fig_pattern(self, legacy_app):
        """Gradually replace legacy app with cloud services"""

        migration_plan = {
            'phase_1': {
                'duration': '3 months',
                'actions': [
                    'Deploy API Gateway in front of legacy app',
                    'Route all traffic through API Gateway',
                    'Implement logging and monitoring'
                ]
            },
            'phase_2': {
                'duration': '6 months',
                'actions': [
                    'Identify bounded contexts',
                    'Extract authentication service to cloud',
                    'Route auth requests to new service',
                    'Keep other functions on-premises'
                ]
            },
            'phase_3': {
                'duration': '9 months',
                'actions': [
                    'Migrate user management to cloud',
                    'Implement cloud-based notifications',
                    'Move reporting to cloud analytics'
                ]
            },
            'phase_4': {
                'duration': '12 months',
                'actions': [
                    'Migrate core business logic',
                    'Decommission legacy components',
                    'Complete cloud transformation'
                ]
            }
        }

        return migration_plan

    def implement_cache_aside_pattern(self):
        """Implement distributed caching across hybrid environment"""

        cache_config = {
            'on_premises': {
                'technology': 'Redis Cluster',
                'nodes': 3,
                'memory': '64GB',
                'eviction_policy': 'LRU'
            },
            'cloud': {
                'technology': 'ElastiCache Redis',
                'nodes': 3,
                'instance_type': 'cache.r6g.xlarge',
                'multi_az': True
            },
            'sync_strategy': {
                'method': 'write-through',
                'consistency': 'eventual',
                'ttl': 3600,
                'invalidation': 'pub-sub'
            }
        }

        return CacheImplementation(cache_config)

class HybridCloudMonitoring:
    def __init__(self):
        self.collectors = {
            'on_prem': PrometheusCollector(),
            'aws': CloudWatchCollector(),
            'azure': AzureMonitorCollector(),
            'gcp': StackdriverCollector()
        }
        self.aggregator = MetricsAggregator()
        self.alerting = AlertingEngine()

    def create_unified_dashboard(self):
        """Create unified monitoring dashboard"""

        dashboard_config = {
            'name': 'Hybrid Cloud Operations',
            'refresh_interval': '30s',
            'panels': [
                {
                    'title': 'Global Application Health',
                    'type': 'heatmap',
                    'queries': [
                        'avg(application_health{environment=~".*"})',
                        'by (datacenter, application)'
                    ]
                },
                {
                    'title': 'Cross-Cloud Network Latency',
                    'type': 'graph',
                    'queries': [
                        'network_latency_ms{source="on-prem", destination="aws"}',
                        'network_latency_ms{source="on-prem", destination="azure"}'
                    ]
                },
                {
                    'title': 'Resource Utilization',
                    'type': 'gauge',
                    'queries': [
                        'sum(cpu_usage{location="on-prem"}) / sum(cpu_capacity{location="on-prem"})',
                        'sum(cpu_usage{location="cloud"}) / sum(cpu_capacity{location="cloud"})'
                    ]
                },
                {
                    'title': 'Cost Tracking',
                    'type': 'stat',
                    'queries': [
                        'sum(daily_cost{location="on-prem"})',
                        'sum(daily_cost{provider="aws"})',
                        'sum(daily_cost{provider="azure"})'
                    ]
                }
            ],
            'alerting_rules': [
                {
                    'name': 'High Latency Alert',
                    'condition': 'network_latency_ms > 100',
                    'duration': '5m',
                    'severity': 'warning'
                },
                {
                    'name': 'Cost Anomaly',
                    'condition': 'daily_cost > avg_over_time(daily_cost[7d]) * 1.5',
                    'duration': '1h',
                    'severity': 'critical'
                }
            ]
        }

        return self.create_dashboard(dashboard_config)

# Hybrid cloud automation workflows
automation_workflows:
  disaster_recovery:
    name: "Automated DR Failover"
    triggers:
      - type: "health_check_failure"
        threshold: 3
        duration: "5m"
      - type: "manual"
        approval_required: true

    steps:
      - name: "Verify Failure"
        actions:
          - check_primary_site_health
          - validate_network_connectivity
          - assess_impact_scope

      - name: "Prepare Failover"
        actions:
          - snapshot_current_state
          - verify_dr_site_readiness
          - update_dns_preparation

      - name: "Execute Failover"
        actions:
          - stop_primary_site_services
          - start_dr_site_services
          - switch_network_routing
          - update_dns_records

      - name: "Validate"
        actions:
          - run_smoke_tests
          - verify_data_integrity
          - check_application_health
          - notify_stakeholders

  scaling_automation:
    name: "Hybrid Auto-Scaling"
    triggers:
      - metric: "cpu_utilization"
        threshold: 75
        duration: "3m"
        action: "scale_out"

      - metric: "response_time"
        threshold: "2000ms"
        duration: "5m"
        action: "scale_out"

    rules:
      - name: "Prefer On-Premises"
        condition: "available_on_prem_capacity > 0"
        action: "scale_on_premises_first"

      - name: "Burst to Cloud"
        condition: "on_prem_at_capacity"
        action: "scale_to_cloud"
        preferences:
          - "aws_spot_instances"
          - "azure_spot_vms"
          - "gcp_preemptible"

class HybridCostOptimizer:
    def __init__(self):
        self.cost_analyzers = {
            'on_prem': OnPremCostAnalyzer(),
            'aws': AWSCostExplorer(),
            'azure': AzureCostManagement(),
            'gcp': GCPBillingAnalyzer()
        }

    def optimize_workload_placement(self, workload):
        """Determine optimal placement based on cost"""

        # Calculate costs for each option
        cost_analysis = {
            'on_premises': self.calculate_on_prem_cost(workload),
            'aws': self.calculate_aws_cost(workload),
            'azure': self.calculate_azure_cost(workload),
            'gcp': self.calculate_gcp_cost(workload)
        }

        # Factor in data transfer costs
        for location in cost_analysis:
            cost_analysis[location]['data_transfer'] = \
                self.calculate_data_transfer_cost(workload, location)

        # Consider compliance requirements
        valid_locations = self.filter_by_compliance(
            workload.compliance_requirements,
            cost_analysis.keys()
        )

        # Recommend optimal placement
        recommendations = []
        for location in valid_locations:
            total_cost = (
                cost_analysis[location]['compute'] +
                cost_analysis[location]['storage'] +
                cost_analysis[location]['data_transfer']
            )

            recommendations.append({
                'location': location,
                'monthly_cost': total_cost,
                'annual_cost': total_cost * 12,
                'cost_breakdown': cost_analysis[location]
            })

        return sorted(recommendations, key=lambda x: x['monthly_cost'])

    def implement_cost_allocation(self):
        """Implement cost allocation and chargeback"""

        allocation_model = {
            'method': 'activity_based_costing',
            'dimensions': [
                'department',
                'project',
                'environment',
                'application'
            ],
            'rules': {
                'shared_services': {
                    'allocation_method': 'usage_based',
                    'metrics': ['cpu_hours', 'storage_gb', 'network_gb']
                },
                'dedicated_resources': {
                    'allocation_method': 'direct_assignment',
                    'tagging_required': True
                },
                'cloud_services': {
                    'allocation_method': 'tag_based',
                    'required_tags': ['cost-center', 'project', 'owner']
                }
            }
        }

        return ChagebackSystem(allocation_model)

# FinOps practices for hybrid cloud
finops_framework:
  principles:
    - "Teams need to collaborate"
    - "Everyone takes ownership"
    - "Accessible real-time reports"
    - "Decisions driven by business value"
    - "Take advantage of the variable cost model"
    - "Continuous optimization"

  lifecycle:
    inform:
      activities:
        - cost_visibility:
            dashboards: ["executive", "engineering", "finance"]
            granularity: "hourly"
            allocation: "tag-based"

        - benchmarking:
            internal: "compare across teams"
            external: "industry standards"
            metrics: ["cost per transaction", "cost per user"]

      tools:
        - "CloudHealth"
        - "Cloudability" 
        - "Azure Cost Management"
        - "Custom BI Dashboards"

    optimize:
      activities:
        - rightsizing:
            frequency: "weekly"
            automation: "recommendations + approval"
            savings_target: "20%"

        - reserved_capacity:
            on_premises: "3-year hardware refresh"
            cloud: "1-year and 3-year commitments"
            coverage_target: "70%"

        - spot_usage:
            workloads: ["batch", "dev/test", "stateless"]
            interruption_handling: "automatic"
            savings_target: "60-80%"

    operate:
      activities:
        - continuous_improvement:
            reviews: "monthly"
            optimization_sprints: "quarterly"

        - automation:
            auto_shutdown: "non-production"
            auto_scaling: "production"
            policy_enforcement: "preventive"

class FutureProofingStrategy:
    def __init__(self):
        self.emerging_tech = {
            'edge_computing': EdgeComputingIntegration(),
            'ai_ml': AIMLPlatform(),
            'quantum_ready': QuantumReadiness(),
            'blockchain': BlockchainIntegration()
        }

    def prepare_for_edge_computing(self):
        """Prepare hybrid cloud for edge computing"""

        edge_architecture = {
            'edge_locations': [
                {
                    'type': 'retail_stores',
                    'count': 500,
                    'compute': 'nvidia_jetson',
                    'connectivity': '5G',
                    'workloads': ['inventory_tracking', 'customer_analytics']
                },
                {
                    'type': 'manufacturing_floor',
                    'count': 50,
                    'compute': 'industrial_pc',
                    'connectivity': 'private_5G',
                    'workloads': ['quality_inspection', 'predictive_maintenance']
                }
            ],

            'edge_cloud_sync': {
                'protocol': 'mqtt',
                'frequency': 'event_driven',
                'data_filtering': 'edge_ml_models',
                'backup': 'store_and_forward'
            },

            'management': {
                'deployment': 'kubernetes_edge',
                'updates': 'over_the_air',
                'monitoring': 'centralized',
                'security': 'zero_trust_edge'
            }
        }

        return edge_architecture

    def implement_ai_ml_platform(self):
        """Implement distributed AI/ML platform"""

        ml_platform = {
            'training': {
                'location': 'cloud',
                'frameworks': ['tensorflow', 'pytorch', 'sagemaker'],
                'data_sources': ['on_prem_warehouse', 'cloud_data_lake'],
                'compute': 'gpu_clusters'
            },

            'inference': {
                'edge': {
                    'models': 'quantized',
                    'hardware': 'edge_tpu',
                    'latency': '<10ms'
                },
                'on_premises': {
                    'models': 'optimized',
                    'hardware': 'gpu_servers',
                    'latency': '<50ms'
                },
                'cloud': {
                    'models': 'full_precision',
                    'hardware': 'elastic_inference',
                    'latency': '<200ms'
                }
            },

            'mlops': {
                'pipeline': 'kubeflow',
                'model_registry': 'mlflow',
                'monitoring': 'model_drift_detection',
                'governance': 'model_lineage_tracking'
            }
        }

        return ml_platform

# Continuous evolution framework
evolution_strategy:
  assessment_cycle: "quarterly"

  evaluation_criteria:
    - technology_trends:
        sources: ["gartner", "forrester", "vendor_roadmaps"]
        relevance_scoring: "business_impact"

    - cost_efficiency:
        benchmark: "industry_standards"
        optimization_target: "10% year-over-year"

    - security_posture:
        assessments: "continuous"
        compliance_updates: "real-time"

    - performance_metrics:
        sla_achievement: ">99.9%"
        user_satisfaction: ">4.5/5"

  innovation_pipeline:
    proof_of_concepts:
      budget: "5% of IT budget"
      duration: "30-90 days"
      success_criteria: "defined_per_project"

    pilot_programs:
      selection: "poc_graduates"
      scale: "10% of workload"
      duration: "6 months"

    production_rollout:
      approach: "gradual"
      rollback_plan: "mandatory"
      success_metrics: "predefined"

  skills_development:
    training_budget: "3% of IT budget"
    certifications: ["cloud", "security", "emerging_tech"]
    hands_on_labs: "monthly"
    innovation_time: "20% for engineers"

gantt
    title Hybrid Cloud Implementation Roadmap
    dateFormat  YYYY-MM-DD
    section Foundation
    Network Connectivity     :2024-01-01, 60d
    Security Framework      :2024-02-01, 45d
    Identity Federation     :2024-02-15, 30d

    section Migration Wave 1
    Assessment & Planning   :2024-03-01, 30d
    Non-Critical Apps      :2024-04-01, 60d
    Testing & Validation   :2024-05-15, 15d

    section Migration Wave 2
    Business Applications  :2024-06-01, 90d
    Data Synchronization   :2024-07-01, 60d
    Disaster Recovery      :2024-08-01, 30d

    section Optimization
    Cost Optimization      :2024-09-01, 30d
    Performance Tuning     :2024-09-15, 30d
    Automation Rollout     :2024-10-01, 60d

    section Innovation
    Edge Computing Pilot   :2024-11-01, 60d
    AI/ML Platform        :2024-11-15, 45d