Designing a Multi-Cloud Database Strategy

# Benchmarking configuration template
apiVersion: v1
kind: ConfigMap
metadata:
  name: db-benchmark-config
data:
  postgres-benchmark.sql: |
    -- TPC-B like benchmark
    CREATE TABLE accounts (
      aid SERIAL PRIMARY KEY,
      bid INTEGER,
      abalance INTEGER,
      filler CHAR(84)
    );
    CREATE TABLE branches (
      bid SERIAL PRIMARY KEY,
      bbalance INTEGER,
      filler CHAR(88)
    );
    CREATE TABLE tellers (
      tid SERIAL PRIMARY KEY,
      bid INTEGER,
      tbalance INTEGER,
      filler CHAR(84)
    );
    CREATE TABLE history (
      tid INTEGER,
      bid INTEGER,
      aid INTEGER,
      delta INTEGER,
      mtime TIMESTAMP,
      filler CHAR(22)
    );

benchmark-script.sh: |
  #!/bin/bash
  # Multi-cloud performance testing
  CLOUDS=("aws" "azure" "gcp")
  REGIONS=("us-east-1" "eastus" "us-central1")
  
  for i in "${!CLOUDS[@]}"; do
    cloud="${CLOUDS[$i]}"
    region="${REGIONS[$i]}"
    echo "Testing ${cloud} in ${region}"
    
    # Initialize benchmark database
    pgbench -i -s 100 -h "${cloud}-postgres.${region}.company.com" -U benchuser benchdb
    
    # Run benchmark tests
    pgbench -c 10 -j 2 -t 1000 -h "${cloud}-postgres.${region}.company.com" -U benchuser benchdb > "${cloud}-${region}-results.txt"
    
    # Extract key metrics
    grep "tps" "${cloud}-${region}-results.txt" | awk '{print $3}' > "${cloud}-${region}-tps.txt"
    grep "latency" "${cloud}-${region}-results.txt" | awk '{print $4}' > "${cloud}-${region}-latency.txt"
  done

class MultiCloudCostAnalyzer:
    def __init__(self):
        self.providers = {
            'aws': {
                'compute': {'m5.large': 0.096, 'm5.xlarge': 0.192},
                'storage': {'gp3': 0.08, 'io2': 0.125},
                'data_transfer': {'out': 0.09, 'cross_az': 0.01}
            },
            'azure': {
                'compute': {'Standard_D2s_v3': 0.096, 'Standard_D4s_v3': 0.192},
                'storage': {'Standard_LRS': 0.045, 'Premium_LRS': 0.135},
                'data_transfer': {'out': 0.087, 'cross_region': 0.02}
            },
            'gcp': {
                'compute': {'n1-standard-2': 0.095, 'n1-standard-4': 0.190},
                'storage': {'pd-standard': 0.04, 'pd-ssd': 0.17},
                'data_transfer': {'out': 0.12, 'cross_region': 0.01}
            }
        }
    
    def calculate_monthly_cost(self, provider, workload_spec):
        pricing = self.providers[provider]
        
        # Compute costs
        compute_hours = workload_spec['compute_hours']
        instance_type = workload_spec['instance_type']
        compute_cost = compute_hours * pricing['compute'][instance_type]
        
        # Storage costs
        storage_gb = workload_spec['storage_gb']
        storage_type = workload_spec['storage_type']
        storage_cost = storage_gb * pricing['storage'][storage_type]
        
        # Data transfer costs
        transfer_gb = workload_spec['data_transfer_gb']
        transfer_cost = transfer_gb * pricing['data_transfer']['out']
        
        return {
            'compute': compute_cost,
            'storage': storage_cost,
            'transfer': transfer_cost,
            'total': compute_cost + storage_cost + transfer_cost
        }
    
    def compare_providers(self, workload_spec):
        results = {}
        for provider in self.providers.keys():
            results[provider] = self.calculate_monthly_cost(provider, workload_spec)
        return results

# Example usage
analyzer = MultiCloudCostAnalyzer()
workload = {
    'compute_hours': 730,  # Full month
    'instance_type': 'm5.large',  # Will map to equivalent
    'storage_gb': 1000,
    'storage_type': 'gp3',  # Will map to equivalent
    'data_transfer_gb': 500
}
cost_comparison = analyzer.compare_providers(workload)

                Central Hub (Primary Cloud)
                           |
      +--------------------+--------------------+
      |                    |                    |
   Spoke 1              Spoke 2              Spoke 3
  (Cloud A)            (Cloud B)            (Cloud C)

Cloud A ←→ Cloud B
   ↑         ↓
   ↓         ↑
Cloud C ←→ Cloud D

Application Layer
        |
   Query Router
        |
+------+------+------+
|      |      |      |
DB-A  DB-B  DB-C  DB-D

# Event-driven data synchronization
apiVersion: v1
kind: ConfigMap
metadata:
  name: data-sync-config
data:
  sync-rules.yaml: |
    synchronization:
      tables:
        - name: users
          strategy: real_time
          conflicts: last_write_wins
          destinations:
            - cloud: aws
              region: us-east-1
              database: primary
            - cloud: azure
              region: eastus
              database: replica
            - cloud: gcp
              region: us-central1
              database: analytics
        - name: transactions
          strategy: batch
          batch_size: 1000
          frequency: "*/5 * * * *"
          destinations:
            - cloud: aws
              region: us-east-1
              database: primary
            - cloud: azure
              region: eastus
              database: backup
      conflict_resolution:
        default: timestamp
        custom_rules:
          - table: users
            field: last_modified
            strategy: latest_timestamp
          - table: accounts
            field: version
            strategy: highest_version

class MultiCloudShardingStrategy:
    def __init__(self):
        self.clouds = {
            'aws': {'weight': 0.4, 'regions': ['us-east-1', 'us-west-2']},
            'azure': {'weight': 0.3, 'regions': ['eastus', 'westus2']},
            'gcp': {'weight': 0.3, 'regions': ['us-central1', 'us-west1']}
        }
    
    def route_data(self, partition_key, data_type):
        """Route data based on partition key and type"""
        hash_value = hash(partition_key) % 100
        
        # Geographic-based routing
        if data_type == 'user_data':
            if hash_value < 40:
                return 'aws', 'us-east-1'
            elif hash_value < 70:
                return 'azure', 'eastus'
            else:
                return 'gcp', 'us-central1'
        
        # Compliance-based routing
        elif data_type == 'financial_data':
            # Route sensitive data to specific compliant clouds
            if hash_value < 50:
                return 'aws', 'us-east-1'  # FedRAMP compliant
            else:
                return 'azure', 'eastus'  # FISMA compliant
        
        # Performance-based routing
        elif data_type == 'analytics_data':
            return 'gcp', 'us-central1'  # BigQuery integration
        
        return 'aws', 'us-east-1'  # Default routing
    
    def get_read_replicas(self, partition_key, data_type):
        """Get all read replica locations for a partition"""
        primary_cloud, primary_region = self.route_data(partition_key, data_type)
        replicas = []
        
        for cloud, config in self.clouds.items():
            if cloud != primary_cloud:
                replicas.extend([(cloud, region) for region in config['regions']])
        
        return replicas

# PostgreSQL logical replication across clouds
apiVersion: v1
kind: ConfigMap
metadata:
  name: postgres-replication-config
data:
  master.conf: |
    # Primary database configuration (AWS)
    wal_level = logical
    max_replication_slots = 10
    max_wal_senders = 10
    shared_preload_libraries = 'pg_logical'
    
  setup-replication.sql: |
    -- Create publication on master (AWS)
    CREATE PUBLICATION multi_cloud_pub FOR ALL TABLES;
    
    -- Create replication user
    CREATE USER replicator WITH REPLICATION LOGIN PASSWORD 'secure_password';
    GRANT SELECT ON ALL TABLES IN SCHEMA public TO replicator;
    
    -- On Azure replica
    CREATE SUBSCRIPTION azure_sub 
    CONNECTION 'host=aws-postgres.us-east-1.company.com port=5432 user=replicator dbname=myapp sslmode=require' 
    PUBLICATION multi_cloud_pub;
    
    -- On GCP replica
    CREATE SUBSCRIPTION gcp_sub 
    CONNECTION 'host=aws-postgres.us-east-1.company.com port=5432 user=replicator dbname=myapp sslmode=require' 
    PUBLICATION multi_cloud_pub;

# BDR (Bi-Directional Replication) configuration
apiVersion: v1
kind: ConfigMap
metadata:
  name: bdr-config
data:
  bdr-setup.sql: |
    -- Install BDR extension on all nodes
    CREATE EXTENSION bdr;
    
    -- Configure node groups
    SELECT bdr.bdr_group_create(
      local_node_name := 'aws-node',
      node_external_dsn := 'host=aws-postgres.company.com port=5432 dbname=myapp',
      replication_sets := ARRAY['default']
    );
    
    SELECT bdr.bdr_group_join(
      local_node_name := 'azure-node',
      node_external_dsn := 'host=azure-postgres.company.com port=5432 dbname=myapp',
      join_using_dsn := 'host=aws-postgres.company.com port=5432 dbname=myapp',
      replication_sets := ARRAY['default']
    );
    
    SELECT bdr.bdr_group_join(
      local_node_name := 'gcp-node',
      node_external_dsn := 'host=gcp-postgres.company.com port=5432 dbname=myapp',
      join_using_dsn := 'host=aws-postgres.company.com port=5432 dbname=myapp',
      replication_sets := ARRAY['default']
    );

class ConflictResolver:
    def __init__(self):
        self.resolution_strategies = {
            'last_write_wins': self.last_write_wins,
            'highest_version': self.highest_version,
            'custom_business_logic': self.custom_business_logic
        }
    
    def last_write_wins(self, records):
        """Resolve conflicts based on timestamp"""
        return max(records, key=lambda r: r['modified_at'])
    
    def highest_version(self, records):
        """Resolve conflicts based on version number"""
        return max(records, key=lambda r: r['version'])
    
    def custom_business_logic(self, records):
        """Apply custom business rules for conflict resolution"""
        # Example: For account balances, use the highest value
        if records[0]['table'] == 'accounts':
            return max(records, key=lambda r: r['balance'])
        
        # Example: For user profiles, merge non-null fields
        if records[0]['table'] == 'user_profiles':
            merged_record = records[0].copy()
            for record in records[1:]:
                for field, value in record.items():
                    if value is not None and merged_record.get(field) is None:
                        merged_record[field] = value
            return merged_record
        
        # Default to timestamp-based resolution
        return self.last_write_wins(records)
    
    def resolve_conflict(self, conflicting_records, strategy='last_write_wins'):
        """Resolve conflicts using specified strategy"""
        if strategy in self.resolution_strategies:
            return self.resolution_strategies[strategy](conflicting_records)
        else:
            raise ValueError(f"Unknown resolution strategy: {strategy}")

# Apache Kafka for change data capture
apiVersion: apps/v1
kind: Deployment
metadata:
  name: kafka-connect-multi-cloud
spec:
  replicas: 3
  selector:
    matchLabels:
      app: kafka-connect
  template:
    metadata:
      labels:
        app: kafka-connect
    spec:
      containers:
      - name: kafka-connect
        image: confluentinc/cp-kafka-connect:latest
        env:
        - name: CONNECT_BOOTSTRAP_SERVERS
          value: "kafka-cluster:9092"
        - name: CONNECT_GROUP_ID
          value: "multi-cloud-connect"
        - name: CONNECT_CONFIG_STORAGE_TOPIC
          value: "connect-configs"
        - name: CONNECT_OFFSET_STORAGE_TOPIC
          value: "connect-offsets"
        - name: CONNECT_STATUS_STORAGE_TOPIC
          value: "connect-status"
        ports:
        - containerPort: 8083
        volumeMounts:
        - name: connect-config
          mountPath: /etc/kafka-connect
      volumes:
      - name: connect-config
        configMap:
          name: kafka-connect-config

---
apiVersion: v1
kind: ConfigMap
metadata:
  name: kafka-connect-config
data:
  debezium-postgres-aws.json: |
    {
      "name": "postgres-aws-connector",
      "config": {
        "connector.class": "io.debezium.connector.postgresql.PostgresConnector",
        "database.hostname": "aws-postgres.us-east-1.company.com",
        "database.port": "5432",
        "database.user": "debezium",
        "database.password": "debezium_password",
        "database.dbname": "myapp",
        "database.server.name": "aws-postgres",
        "table.include.list": "public.users,public.orders,public.products",
        "plugin.name": "pgoutput",
        "slot.name": "debezium_aws",
        "transforms": "route",
        "transforms.route.type": "org.apache.kafka.connect.transforms.RegexRouter",
        "transforms.route.regex": "([^.]+)\\.([^.]+)\\.([^.]+)",
        "transforms.route.replacement": "multi-cloud.$3"
      }
    }
    
  debezium-postgres-azure.json: |
    {
      "name": "postgres-azure-connector",
      "config": {
        "connector.class": "io.debezium.connector.postgresql.PostgresConnector",
        "database.hostname": "azure-postgres.eastus.company.com",
        "database.port": "5432",
        "database.user": "debezium",
        "database.password": "debezium_password",
        "database.dbname": "myapp",
        "database.server.name": "azure-postgres",
        "table.include.list": "public.users,public.orders,public.products",
        "plugin.name": "pgoutput",
        "slot.name": "debezium_azure"
      }
    }

# AWS-Azure VPN connection configuration
apiVersion: v1
kind: ConfigMap
metadata:
  name: vpn-config
data:
  aws-azure-vpn.conf: |
    # AWS VPC Configuration
    vpc_cidr: 10.0.0.0/16
    subnet_cidr: 10.0.1.0/24
    
    # Azure VNet Configuration
    vnet_cidr: 10.1.0.0/16
    subnet_cidr: 10.1.1.0/24
    
    # VPN Gateway Configuration
    aws_customer_gateway: 52.12.34.56
    azure_local_gateway: 40.78.90.12
    
    # IPSec Configuration
    pre_shared_key: "secure_pre_shared_key"
    ike_version: 2
    encryption: AES256
    hash: SHA256
    dh_group: 14
    
  routing-rules.conf: |
    # Route database traffic through VPN
    route add -net 10.1.1.0/24 gw 10.0.1.1
    route add -host azure-postgres.company.com gw 10.0.1.1
    
    # Route Azure traffic through VPN gateway
    route add -net 10.0.1.0/24 gw 10.1.1.1
    route add -host aws-postgres.company.com gw 10.1.1.1

# AWS Privatea configuration
apiVersion: v1
kind: ConfigMap
metadata:
  name: privatea-config
data:
  aws-privatea.yaml: |
    # VPC Endpoint for RDS
    VPCEndpoint:
      Type: AWS::EC2::VPCEndpoint
      Properties:
        VpcId: !Ref MyVPC
        ServiceName: com.amazonaws.us-east-1.rds
        VpcEndpointType: Interface
        SubnetIds:
          - !Ref PrivateSubnet1
          - !Ref PrivateSubnet2
        SecurityGroupIds:
          - !Ref DatabaseSecurityGroup
        PrivateDnsEnabled: true
        
  azure-privateendpoint.yaml: |
    # Azure Private Endpoint for PostgreSQL
    resource "azurerm_private_endpoint" "postgres" {
      name                = "postgres-private-endpoint"
      location            = azurerm_resource_group.main.location
      resource_group_name = azurerm_resource_group.main.name
      subnet_id           = azurerm_subnet.database.id
      
      private_service_connection {
        name                           = "postgres-privateserviceconnection"
        private_connection_resource_id = azurerm_postgresql_server.main.id
        subresource_names              = ["postgresqlServer"]
        is_manual_connection           = false
      }
    }

# HAProxy configuration for multi-cloud database load balancing
apiVersion: v1
kind: ConfigMap
metadata:
  name: haproxy-config
data:
  haproxy.cfg: |
    global
      daemon
      maxconn 4096
      log stdout local0
    
    defaults
      mode tcp
      timeout connect 5000ms
      timeout client 50000ms
      timeout server 50000ms
      option tcplog
    
    # Database read load balancing
    frontend db_read
      bind *:5432
      default_backend db_read_servers
    
    backend db_read_servers
      balance roundrobin
      option tcp-check
      tcp-check expect string "accept"
      
      # AWS read replica
      server aws-read-1 aws-postgres-read.us-east-1.company.com:5432 check weight 40
      server aws-read-2 aws-postgres-read.us-west-2.company.com:5432 check weight 30
      
      # Azure read replica
      server azure-read-1 azure-postgres-read.eastus.company.com:5432 check weight 20
      
      # GCP read replica
      server gcp-read-1 gcp-postgres-read.us-central1.company.com:5432 check weight 10
    
    # Database write routing (primary only)
    frontend db_write
      bind *:5433
      default_backend db_write_servers
    
    backend db_write_servers
      # Route writes to primary in AWS
      server aws-primary aws-postgres-primary.us-east-1.company.com:5432 check
    
    # Health check endpoint
    frontend stats
      bind *:8404
      stats enable
      stats uri /
      stats refresh 30s
      stats admin if TRUE

# Multi-cloud DNS configuration
apiVersion: v1
kind: ConfigMap
metadata:
  name: dns-config
data:
  coredns-config: |
    .:53 {
      errors
      health {
        lameduck 5s
      }
      ready
      
      # Multi-cloud database routing
      template IN A db-read.company.com {
        match "^db-read\.company\.com\.$"
        answer "{{ .Name }} 60 IN A {{ if eq .Zone \"us-east\" }}52.12.34.56{{ else if eq .Zone \"us-west\" }}54.67.89.12{{ else }}35.45.67.89{{ end }}"
        fallthrough
      }
      
      template IN A db-write.company.com {
        match "^db-write\.company\.com\.$"
        answer "{{ .Name }} 60 IN A 52.12.34.56" # Always route to primary
        fallthrough
      }
      
      kubernetes cluster.local in-addr.arpa ip6.arpa {
        pods insecure
        fallthrough in-addr.arpa ip6.arpa
        ttl 30
      }
      
      prometheus :9153
      forward . /etc/resolv.conf
      cache 30
      loop
      reload
      loadbalance
    }

# Cross-cloud identity federation
apiVersion: v1
kind: ConfigMap
metadata:
  name: identity-federation-config
data:
  aws-iam-role.json: |
    {
      "Version": "2012-10-17",
      "Statement": [
        {
          "Effect": "Allow",
          "Principal": {
            "Federated": "arn:aws:iam::123456789012:saml-provider/CompanySAML"
          },
          "Action": "sts:AssumeRoleWithSAML",
          "Condition": {
            "StringEquals": {
              "SAML:aud": "https://signin.aws.amazon.com/saml"
            }
          }
        }
      ]
    }
    
  azure-app-registration.json: |
    {
      "displayName": "Multi-Cloud-Database-Access",
      "signInAudience": "AzureADMyOrg",
      "requiredResourceAccess": [
        {
          "resourceAppId": "00000003-0000-0000-c000-000000000000",
          "resourceAccess": [
            {
              "id": "e1fe6dd8-ba31-4d61-89e7-88639da4683d",
              "type": "Scope"
            }
          ]
        }
      ],
      "web": {
        "redirectUris": [
          "https://auth.company.com/callback"
        ]
      }
    }
    
  gcp-service-account.json: |
    {
      "type": "service_account",
      "project_id": "company-multi-cloud",
      "private_key_id": "key-id",
      "client_email": "database-access@company-multi-cloud.iam.gserviceaccount.com",
      "client_id": "client-id",
      "auth_uri": "https://accounts.google.com/o/oauth2/auth",
      "token_uri": "https://oauth2.googleapis.com/token"
    }

# Consistent RBAC across clouds
apiVersion: v1
kind: ConfigMap
metadata:
  name: database-rbac-config
data:
  postgresql-roles.sql: |
    -- Create consistent roles across all cloud instances
    -- Application roles
    CREATE ROLE app_read WITH LOGIN PASSWORD 'secure_password_read';
    CREATE ROLE app_write WITH LOGIN PASSWORD 'secure_password_write';
    CREATE ROLE app_admin WITH LOGIN PASSWORD 'secure_password_admin';
    
    -- Service roles
    CREATE ROLE monitoring_service WITH LOGIN PASSWORD 'monitoring_password';
    CREATE ROLE backup_service WITH LOGIN PASSWORD 'backup_password';
    CREATE ROLE replication_service WITH LOGIN PASSWORD 'replication_password';
    
    -- Grant appropriate permissions
    GRANT SELECT ON ALL TABLES IN SCHEMA public TO app_read;
    GRANT SELECT, INSERT, UPDATE, DELETE ON ALL TABLES IN SCHEMA public TO app_write;
    GRANT ALL PRIVILEGES ON ALL TABLES IN SCHEMA public TO app_admin;
    
    -- Monitoring permissions
    GRANT SELECT ON pg_stat_database, pg_stat_user_tables, pg_stat_activity TO monitoring_service;
    
    -- Backup permissions
    GRANT SELECT ON ALL TABLES IN SCHEMA public TO backup_service;
    
    -- Replication permissions
    GRANT REPLICATION TO replication_service;
    GRANT SELECT ON ALL TABLES IN SCHEMA public TO replication_service;
    
  access-policy.yaml: |
    # Unified access policy definition
    access_policies:
      read_only:
        permissions:
          - SELECT
        tables:
          - users
          - products
          - orders
        conditions:
          - time_based: "09:00-17:00"
          - ip_whitelist: ["10.0.0.0/8", "172.16.0.0/12"]
      
      read_write:
        permissions:
          - SELECT
          - INSERT
          - UPDATE
          - DELETE
        tables:
          - users
          - products
          - orders
        conditions:
          - mfa_required: true
          - session_timeout: 3600
      
      admin_access:
        permissions:
          - ALL
        tables:
          - "*"
        conditions:
          - approval_required: true
          - audit_logging: true
          - privileged_session: true

# Encryption configuration across clouds
apiVersion: v1
kind: ConfigMap
metadata:
  name: encryption-config
data:
  tls-config.conf: |
    # TLS configuration for database connections
    ssl_cert_file = '/etc/ssl/certs/database.crt'
    ssl_key_file = '/etc/ssl/private/database.key'
    ssl_ca_file = '/etc/ssl/certs/ca.crt'
    ssl_crl_file = '/etc/ssl/certs/database.crl'
    
    # Encryption settings
    ssl_ciphers = 'ECDHE-RSA-AES256-GCM-SHA384:ECDHE-RSA-AES128-GCM-SHA256'
    ssl_prefer_server_ciphers = on
    ssl_protocols = TLSv1.2,TLSv1.3
    
    # Client certificate authentication
    ssl_cert_auth = on
    ssl_client_cert_auth = require
    
  column-encryption.sql: |
    -- Column-level encryption for sensitive data
    CREATE EXTENSION IF NOT EXISTS pgcrypto;
    
    -- Create encrypted columns
    ALTER TABLE users ADD COLUMN email_encrypted BYTEA;
    ALTER TABLE users ADD COLUMN phone_encrypted BYTEA;
    
    -- Create encryption functions
    CREATE OR REPLACE FUNCTION encrypt_pii(data TEXT, key TEXT)
    RETURNS BYTEA AS $$
    BEGIN
      RETURN pgp_sym_encrypt(data, key);
    END;
    $$ LANGUAGE plpgsql;
    
    CREATE OR REPLACE FUNCTION decrypt_pii(encrypted_data BYTEA, key TEXT)
    RETURNS TEXT AS $$
    BEGIN
      RETURN pgp_sym_decrypt(encrypted_data, key);
    END;
    $$ LANGUAGE plpgsql;
    
    -- Encrypt existing data
    UPDATE users SET email_encrypted = encrypt_pii(email, current_setting('app.encryption_key'));
    UPDATE users SET phone_encrypted = encrypt_pii(phone, current_setting('app.encryption_key'));

# Prometheus federation for multi-cloud monitoring
apiVersion: v1
kind: ConfigMap
metadata:
  name: prometheus-federation-config
data:
  prometheus.yml: |
    global:
      scrape_interval: 15s
      evaluation_interval: 15s
    
    rule_files:
      - "database_rules.yml"
      - "multi_cloud_rules.yml"
    
    scrape_configs:
      # AWS RDS monitoring
      - job_name: 'aws-rds'
        ec2_sd_configs:
          - region: us-east-1
            port: 9042
            filters:
              - name: tag:Name
                values: [rds-exporter]
        relabel_configs:
          - source_labels: [__meta_ec2_tag_Environment]
            target_label: environment
          - source_labels: [__meta_ec2_tag_Cloud]
            target_label: cloud_provider
            replacement: aws
      
      # Azure Database monitoring
      - job_name: 'azure-postgres'
        static_configs:
          - targets: ['azure-postgres-exporter.eastus.company.com:9187']
        metric_relabel_configs:
          - source_labels: [__name__]
            target_label: cloud_provider
            replacement: azure
      
      # GCP Cloud SQL monitoring
      - job_name: 'gcp-cloudsql'
        static_configs:
          - targets: ['gcp-postgres-exporter.us-central1.company.com:9187']
        metric_relabel_configs:
          - source_labels: [__name__]
            target_label: cloud_provider
            replacement: gcp
      
      # Federation configuration
      - job_name: 'federate-aws'
        scrape_interval: 30s
        honor_labels: true
        metrics_path: '/federate'
        params:
          'match[]':
            - '{job=~"aws-.*"}'
            - '{__name__=~"postgres_.*"}'
        static_configs:
          - targets:
            - 'prometheus-aws.us-east-1.company.com:9090'
      
      - job_name: 'federate-azure'
        scrape_interval: 30s
        honor_labels: true
        metrics_path: '/federate'
        params:
          'match[]':
            - '{job=~"azure-.*"}'
            - '{__name__=~"postgres_.*"}'
        static_configs:
          - targets:
            - 'prometheus-azure.eastus.company.com:9090'

apiVersion: v1
kind: ConfigMap
metadata:
  name: multi-cloud-alerting-rules
data:
  database_rules.yml: |
    groups:
    - name: multi-cloud-database.rules
      rules:
      # Cross-cloud replication lag
      - alert: MultiCloudReplicationLag
        expr: |
          (
            postgres_replication_lag_seconds{cloud_provider="aws"} -
            postgres_replication_lag_seconds{cloud_provider="azure"}
          ) > 300
        for: 5m
        labels:
          severity: warning
          component: replication
        annotations:
          summary: "High replication lag between AWS and Azure"
          description: "Replication lag between AWS and Azure is {{ $value }} seconds"
      
      # Cloud-specific database down
      - alert: DatabaseDownInCloud
        expr: up{job=~".*-postgres"} == 0
        for: 2m
        labels:
          severity: critical
          component: database
        annotations:
          summary: "Database is down in {{ $labels.cloud_provider }}"
          description: "PostgreSQL instance in {{ $labels.cloud_provider }} has been down for more than 2 minutes"
      
      # Cross-cloud connection failures
      - alert: CrossCloudConnectivityIssue
        expr: |
          rate(postgres_connection_errors_total[5m]) > 0.1
        for: 3m
        labels:
          severity: warning
          component: connectivity
        annotations:
          summary: "High connection error rate for {{ $labels.cloud_provider }}"
          description: "Connection error rate is {{ $value }} per second"
      
      # Performance degradation across clouds
      - alert: MultiCloudPerformanceDegradation
        expr: |
          (
            avg_over_time(postgres_query_duration_seconds{cloud_provider="aws"}[10m]) /
            avg_over_time(postgres_query_duration_seconds{cloud_provider="aws"}[1h])
          ) > 2
        for: 5m
        labels:
          severity: warning
          component: performance
        annotations:
          summary: "Performance degradation detected in {{ $labels.cloud_provider }}"
          description: "Query performance has degraded by {{ $value }}x compared to baseline"

# Logstash configuration for multi-cloud log aggregation
apiVersion: v1
kind: ConfigMap
metadata:
  name: logstash-multi-cloud-config
data:
  logstash.conf: |
    input {
      # AWS CloudWatch Logs
      cloudwatch_logs {
        log_group => "/aws/rds/instance/postgres-primary/postgresql"
        region => "us-east-1"
        access_key_id => "${AWS_ACCESS_KEY}"
        secret_access_key => "${AWS_SECRET_KEY}"
        codec => "json"
        add_field => { "cloud_provider" => "aws" }
        add_field => { "region" => "us-east-1" }
      }
      
      # Azure Monitor Logs
      http {
        port => 8081
        codec => "json"
        additional_codecs => {
          "application/json" => "json"
        }
        add_field => { "cloud_provider" => "azure" }
      }
      
      # GCP Stackdriver Logs
      google_cloud_storage {
        bucket => "gcp-database-logs"
        json_key_file => "/etc/gcp/service-account.json"
        codec => "json"
        add_field => { "cloud_provider" => "gcp" }
        add_field => { "region" => "us-central1" }
      }
    }
    
    filter {
      # Parse PostgreSQL logs
      if [cloud_provider] {
        grok {
          match => { 
            "message" => "%{TIMESTAMP_ISO8601:timestamp} %{WORD:timezone} \[%{NUMBER:pid}\] %{WORD:level}: %{GREEDYDATA:log_message}"
          }
        }
        
        # Extract query information
        if [log_message] =~ /^statement:/ {
          grok {
            match => { "log_message" => "statement: %{GREEDYDATA:sql_query}" }
          }
          mutate {
            add_field => { "log_type" => "query" }
          }
        }
        
        # Extract connection information
        if [log_message] =~ /connection/ {
          mutate {
            add_field => { "log_type" => "connection" }
          }
        }
        
        # Add geographic information
        if [cloud_provider] == "aws" {
          if [region] == "us-east-1" {
            mutate {
              add_field => { "geographic_region" => "north_america_east" }
            }
          }
        }
        
        # Normalize timestamps
        date {
          match => [ "timestamp", "yyyy-MM-dd HH:mm:ss.SSS" ]
          timezone => "UTC"
        }
      }
    }
    
    output {
      # Send to Elasticsearch
      elasticsearch {
        hosts => ["elasticsearch-cluster:9200"]
        index => "database-logs-%{+YYYY.MM.dd}"
        template_name => "database-logs"
        template_pattern => "database-logs-*"
        template => "/etc/logstash/templates/database-logs-template.json"
      }
      
      # Send alerts to external systems
      if [level] in ["ERROR", "FATAL", "PANIC"] {
        http {
          url => "https://alerts.company.com/webhook"
          http_method => "post"
          content_type => "application/json"
          format => "json"
          mapping => {
            "alert_type" => "database_error"
            "cloud_provider" => "%{cloud_provider}"
            "region" => "%{region}"
            "level" => "%{level}"
            "message" => "%{log_message}"
            "timestamp" => "%{@timestamp}"
          }
        }
      }
    }

class MultiCloudCostOptimizer:
    def __init__(self):
        self.cloud_apis = {
            'aws': self.setup_aws_client(),
            'azure': self.setup_azure_client(),
            'gcp': self.setup_gcp_client()
        }
        self.cost_thresholds = {
            'aws': {'hourly_max': 50, 'monthly_max': 10000},
            'azure': {'hourly_max': 45, 'monthly_max': 9500},
            'gcp': {'hourly_max': 40, 'monthly_max': 9000}
        }
    
    def optimize_instance_sizing(self, metrics):
        """Optimize instance sizes based on usage metrics"""
        recommendations = {}
        
        for cloud, usage in metrics.items():
            current_cost = usage['current_hourly_cost']
            cpu_utilization = usage['avg_cpu_utilization']
            memory_utilization = usage['avg_memory_utilization']
            
            # Downsize if consistently underutilized
            if cpu_utilization < 30 and memory_utilization < 40:
                recommendations[cloud] = {
                    'action': 'downsize',
                    'target_instance': self.get_smaller_instance(usage['instance_type']),
                    'estimated_savings': current_cost * 0.5
                }
            
            # Upsize if consistently overutilized
            elif cpu_utilization > 80 or memory_utilization > 85:
                recommendations[cloud] = {
                    'action': 'upsize',
                    'target_instance': self.get_larger_instance(usage['instance_type']),
                    'estimated_cost_increase': current_cost * 0.5
                }
            
            # Consider spot instances for non-critical workloads
            elif usage['workload_type'] == 'development':
                recommendations[cloud] = {
                    'action': 'spot_instance',
                    'estimated_savings': current_cost * 0.7
                }
        
        return recommendations
    
    def schedule_workloads(self, workload_patterns):
        """Schedule workloads based on cloud pricing patterns"""
        schedules = {}
        
        for workload_id, pattern in workload_patterns.items():
            best_cloud = None
            min_cost = float('inf')
            
            for cloud in self.cloud_apis.keys():
                # Calculate cost for this time period
                cost = self.calculate_time_based_cost(cloud, pattern)
                if cost < min_cost:
                    min_cost = cost
                    best_cloud = cloud
            
            schedules[workload_id] = {
                'recommended_cloud': best_cloud,
                'estimated_cost': min_cost,
                'schedule': self.generate_schedule(best_cloud, pattern)
            }
        
        return schedules
    
    def implement_data_lifecycle_policies(self):
        """Implement automated data lifecycle management"""
        policies = {
            'hot_data': {
                'retention_days': 30,
                'storage_class': 'high_performance',
                'replication_factor': 3
            },
            'warm_data': {
                'retention_days': 365,
                'storage_class': 'standard',
                'replication_factor': 2
            },
            'cold_data': {
                'retention_days': 2555,  # 7 years
                'storage_class': 'archive',
                'replication_factor': 1
            }
        }
        
        return policies

# Reserved instance planning configuration
apiVersion: v1
kind: ConfigMap
metadata:
  name: reserved-instance-strategy
data:
  ri-planning.yaml: |
    # Reserved instance strategy across clouds
    aws:
      commitment_level: "3_year"
      payment_option: "partial_upfront"
      instance_types:
        - type: "db.r5.xlarge"
          quantity: 2
          estimated_savings: "45%"
          usage_pattern: "production"
        - type: "db.t3.medium"
          quantity: 5
          estimated_savings: "35%"
          usage_pattern: "development"
    
    azure:
      commitment_level: "3_year"
      payment_option: "upfront"
      instance_types:
        - type: "Standard_D4s_v3"
          quantity: 1
          estimated_savings: "42%"
          usage_pattern: "production"
        - type: "Standard_B2s"
          quantity: 3
          estimated_savings: "30%"
          usage_pattern: "testing"
    
    gcp:
      commitment_level: "3_year"
      payment_option: "monthly"
      instance_types:
        - type: "db-n1-standard-4"
          quantity: 1
          estimated_savings: "40%"
          usage_pattern: "analytics"
  
  cost-allocation.yaml: |
    # Cost allocation and chargeback strategy
    cost_centers:
      engineering:
        clouds: ["aws", "azure"]
        allocation_method: "usage_based"
        budget_monthly: 15000
      
      data_science:
        clouds: ["gcp"]
        allocation_method: "project_based"
        budget_monthly: 8000
      
      operations:
        clouds: ["aws", "azure", "gcp"]
        allocation_method: "resource_tagging"
        budget_monthly: 5000
    
    tagging_strategy:
      required_tags:
        - environment
        - cost_center
        - project
        - owner
        - data_classification
      
      automated_tagging:
        - rule: "environment=production"
          condition: "instance_size > large"
        - rule: "cost_center=engineering"
          condition: "created_by in engineering_team"

# Assessment checklist
assessment_areas:
  infrastructure:
    - current_database_inventory
    - performance_baselines
    - capacity_utilization
    - cost_analysis
  
  applications:
    - database_dependencies
    - data_flow_mapping
    - integration_points
    - performance_requirements
  
  operations:
    - backup_procedures
    - monitoring_capabilities
    - incident_response
    - maintenance_windows
  
  compliance:
    - regulatory_requirements
    - data_classification
    - audit_procedures
    - security_controls

deliverables:
  - current_state_documentation
  - gap_analysis_report
  - risk_assessment
  - business_case_document
  - implementation_roadmap

# Pilot configuration
pilot_scope:
  workloads:
    - development_environment
    - testing_environment
    - low_risk_applications
  
  clouds:
    - primary: aws
    - secondary: azure
  
  success_criteria:
    - zero_data_loss
    - performance_baseline_maintained
    - automated_failover_working
    - monitoring_coverage_complete
    - cost_within_budget

pilot_architecture:
  aws:
    region: us-east-1
    instance_type: db.r5.large
    storage_type: gp3
    backup_retention: 7_days
  
  azure:
    region: eastus
    sku: Standard_D4s_v3
    storage_type: Premium_LRS
    backup_retention: 7_days
  
  replication:
    type: logical
    lag_threshold: 10_seconds
    conflict_resolution: last_write_wins

# Production migration plan
migration_waves:
  wave_1:
    scope: "read_replicas"
    timeline: "month_5"
    risk_level: low
    rollback_time: "2_hours"
  
  wave_2:
    scope: "non_critical_applications"
    timeline: "month_6"
    risk_level: medium
    rollback_time: "4_hours"
  
  wave_3:
    scope: "critical_applications"
    timeline: "month_7-8"
    risk_level: high
    rollback_time: "1_hour"

migration_procedures:
  pre_migration:
    - performance_baseline_capture
    - backup_verification
    - rollback_plan_testing
    - stakeholder_communication
  
  during_migration:
    - real_time_monitoring
    - data_validation
    - performance_verification
    - incident_response_readiness
  
  post_migration:
    - performance_comparison
    - data_integrity_verification
    - user_acceptance_testing
    - lessons_learned_documentation

optimization_initiatives:
  performance:
    - query_optimization
    - index_tuning
    - connection_pooling
    - caching_strategies
  
  cost:
    - right_sizing
    - reserved_instances
    - storage_optimization
    - automated_scaling
  
  operational:
    - automation_enhancement
    - monitoring_improvement
    - alerting_refinement
    - runbook_development
  
  security:
    - access_control_review
    - encryption_enhancement
    - compliance_validation
    - vulnerability_assessment

# Global database distribution
regions:
  north_america:
    primary_cloud: aws
    primary_region: us-east-1
    secondary_cloud: azure
    secondary_region: eastus
    data_residency: "us_canada"
  
  europe:
    primary_cloud: azure
    primary_region: westeurope
    secondary_cloud: gcp
    secondary_region: europe-west1
    data_residency: "eu_only"
  
  asia_pacific:
    primary_cloud: gcp
    primary_region: asia-southeast1
    secondary_cloud: aws
    secondary_region: ap-southeast-1
    data_residency: "apac_only"

class GlobalDataRouter:
    def __init__(self):
        self.region_configs = {
            'north_america': {
                'primary': {'cloud': 'aws', 'region': 'us-east-1'},
                'secondary': {'cloud': 'azure', 'region': 'eastus'},
                'compliance': ['SOC2', 'PCI_DSS']
            },
            'europe': {
                'primary': {'cloud': 'azure', 'region': 'westeurope'},
                'secondary': {'cloud': 'gcp', 'region': 'europe-west1'},
                'compliance': ['GDPR', 'SOC2']
            },
            'asia_pacific': {
                'primary': {'cloud': 'gcp', 'region': 'asia-southeast1'},
                'secondary': {'cloud': 'aws', 'region': 'ap-southeast-1'},
                'compliance': ['PDPA', 'SOC2']
            }
        }
    
    def route_request(self, user_location, data_type, operation):
        """Route database requests based on user location and data requirements"""
        region = self.determine_region(user_location)
        config = self.region_configs[region]
        
        # Determine target based on operation type
        if operation == 'write':
            target = config['primary']
        else:
            # Load balance reads between primary and secondary
            target = self.select_read_target(config, data_type)
        
        return {
            'cloud': target['cloud'],
            'region': target['region'],
            'endpoint': f"{target['cloud']}-db.{target['region']}.company.com",
            'compliance_tags': config['compliance']
        }
    
    def determine_region(self, user_location):
        """Determine appropriate region based on user location"""
        lat, lon = user_location
        
        # Simple geographic routing logic
        if -180 <= lon <= -30:  # Americas
            return 'north_america'
        elif -30 < lon <= 60:   # Europe/Africa
            return 'europe'
        else:                   # Asia/Pacific
            return 'asia_pacific'
    
    def select_read_target(self, config, data_type):
        """Select optimal read target based on data type and performance"""
        # Route analytics queries to secondary (often better for large scans)
        if data_type == 'analytics':
            return config['secondary']
        
        # Route real-time queries to primary (lower latency)
        return config['primary']