# ダウンタイム計算
downtime_percentage = 100 - availability_percentage
downtime_minutes_per_year = minutes_per_year * (downtime_percentage / 100)

# 各期間でのダウンタイム
downtime_per_month = downtime_minutes_per_year / 12
downtime_per_week = downtime_minutes_per_year / 52.18
downtime_per_day = downtime_minutes_per_year / 365.25

return {
    "availability": f"{availability_percentage}%",
    "nines": availability_percentage.count('9') if isinstance(availability_percentage, str) else None,
    "downtime_per_year": format_duration(downtime_minutes_per_year),
    "downtime_per_month": format_duration(downtime_per_month),
    "downtime_per_week": format_duration(downtime_per_week),
    "downtime_per_day": format_duration(downtime_per_day)
}

def check_primary_health(self):
    """プライマリリージョンの健全性チェック"""
    try:
        # ALBのヘルスチェック
        elb = boto3.client('elbv2', region_name=self.primary_region)
        response = elb.describe_target_health(
            TargetGroupArn=self.primary_target_group_arn
        )
        
        healthy_targets = [
            t for t in response['TargetHealthDescriptions']
            if t['TargetHealth']['State'] == 'healthy'
        ]
        
        if len(healthy_targets) == 0:
            return False, "No healthy targets in primary region"
            
        return True, f"{len(healthy_targets)} healthy targets"
        
    except Exception as e:
        return False, f"Health check failed: {str(e)}"

def activate_dr_site(self):
    """DRサイトのアクティベーション"""
    print(f"[{datetime.now()}] Starting DR activation...")
    
    # 1. RDSレプリカのプロモート
    print("Promoting RDS read replica...")
    self.promote_rds_replica()
    
    # 2. EC2インスタンスの起動
    print("Starting EC2 instances...")
    self.start_dr_instances()
    
    # 3. Auto Scaling Groupの調整
    print("Adjusting Auto Scaling Groups...")
    self.scale_dr_environment()
    
    # 4. Route 53のフェイルオーバー
    print("Updating Route 53 records...")
    self.update_dns_records()
    
    # 5. 監視アラートの更新
    print("Updating monitoring...")
    self.update_monitoring()
    
    print(f"[{datetime.now()}] DR activation completed!")
    
def promote_rds_replica(self):
    """RDSリードレプリカをマスターに昇格"""
    response = self.rds_dr.promote_read_replica(
        DBInstanceIdentifier=self.dr_db_instance_id,
        BackupRetentionPeriod=7
    )
    
    # プロモーション完了を待つ
    waiter = self.rds_dr.get_waiter('db_instance_available')
    waiter.wait(DBInstanceIdentifier=self.dr_db_instance_id)
    
    print(f"RDS replica promoted: {self.dr_db_instance_id}")
    
def start_dr_instances(self):
    """事前に作成されたDRインスタンスを起動"""
    # タグでDRインスタンスを検索
    response = self.ec2_dr.describe_instances(
        Filters=[
            {'Name': 'tag:DR-Role', 'Values': ['standby']},
            {'Name': 'instance-state-name', 'Values': ['stopped']}
        ]
    )
    
    instance_ids = []
    for reservation in response['Reservations']:
        for instance in reservation['Instances']:
            instance_ids.append(instance['InstanceId'])
    
    if instance_ids:
        self.ec2_dr.start_instances(InstanceIds=instance_ids)
        
        # 起動完了を待つ
        waiter = self.ec2_dr.get_waiter('instance_running')
        waiter.wait(InstanceIds=instance_ids)
        
        print(f"Started {len(instance_ids)} DR instances")
        
def scale_dr_environment(self):
    """Auto Scaling Groupを本番相当にスケール"""
    autoscaling = boto3.client('autoscaling', region_name=self.dr_region)
    
    # DRのASGを本番レベルにスケール
    autoscaling.set_desired_capacity(
        AutoScalingGroupName=self.dr_asg_name,
        DesiredCapacity=self.prod_desired_capacity,
        HonorCooldown=False
    )
    
    print(f"Scaled ASG to {self.prod_desired_capacity} instances")
    
def update_dns_records(self):
    """Route 53のレコードをDRサイトに向ける"""
    # ヘルスチェックの作成
    health_check_response = self.route53.create_health_check(
        CallerReference=f"dr-health-{int(time.time())}",
        HealthCheckConfig={
            'Type': 'HTTPS',
            'ResourcePath': '/health',
            'FullyQualifiedDomainName': self.dr_alb_dns_name,
            'Port': 443,
            'RequestInterval': 30,
            'FailureThreshold': 3
        }
    )
    
    # Weighted Routingポリシーの更新
    self.route53.change_resource_record_sets(
        HostedZoneId=self.hosted_zone_id,
        ChangeBatch={
            'Changes': [
                {
                    'Action': 'UPSERT',
                    'ResourceRecordSet': {
                        'Name': self.domain_name,
                        'Type': 'A',
                        'SetIdentifier': 'DR-Site',
                        'Weight': 100,  # 全トラフィックをDRへ
                        'AliasTarget': {
                            'HostedZoneId': self.dr_alb_zone_id,
                            'DNSName': self.dr_alb_dns_name,
                            'EvaluateTargetHealth': True
                        }
                    }
                },
                {
                    'Action': 'UPSERT',
                    'ResourceRecordSet': {
                        'Name': self.domain_name,
                        'Type': 'A',
                        'SetIdentifier': 'Primary-Site',
                        'Weight': 0,  # プライマリへのトラフィックを停止
                        'AliasTarget': {
                            'HostedZoneId': self.primary_alb_zone_id,
                            'DNSName': self.primary_alb_dns_name,
                            'EvaluateTargetHealth': True
                        }
                    }
                }
            ]
        }
    )
    
    print("DNS records updated for DR failover")
    
def generate_runbook(self):
    """DR実行手順書の生成"""
    runbook = {
        "title": "Disaster Recovery Runbook",
        "generated_at": datetime.now().isoformat(),
        "steps": [
            {
                "step": 1,
                "action": "Verify Primary Failure",
                "command": "python dr_manager.py check-health",
                "expected_duration": "2 minutes",
                "rollback": "N/A"
            },
            {
                "step": 2,
                "action": "Initiate DR Failover",
                "command": "python dr_manager.py failover --confirm",
                "expected_duration": "15-20 minutes",
                "rollback": "python dr_manager.py failback"
            },
            {
                "step": 3,
                "action": "Verify DR Site Health",
                "command": "python dr_manager.py verify-dr",
                "expected_duration": "5 minutes",
                "rollback": "Investigate specific failures"
            },
            {
                "step": 4,
                "action": "Update External Dependencies",
                "manual_steps": [
                    "Update CDN origin to DR site",
                    "Notify third-party integrations",
                    "Update monitoring dashboards"
                ],
                "expected_duration": "10 minutes"
            },
            {
                "step": 5,
                "action": "Communication",
                "manual_steps": [
                    "Send notification to stakeholders",
                    "Update status page",
                    "Prepare RCA timeline"
                ],
                "expected_duration": "Ongoing"
            }
        ],
        "contacts": {
            "primary": "oncall@company.com",
            "escalation": "management@company.com",
            "vendor_support": {
                "aws": "enterprise-support-case",
                "datadog": "priority-support"
            }
        }
    }
    
    with open('dr_runbook.json', 'w') as f:
        json.dump(runbook, f, indent=2)
        
    print("DR runbook generated: dr_runbook.json")

# ヘルスチェック
healthy, message = dr_manager.check_primary_health()
if not healthy:
    print(f"Primary site unhealthy: {message}")
    dr_manager.activate_dr_site() `

overrides {
  session_affinity = "none"
  ttl = 30
}   } }

def __init__(self, config):
    self.config = config
    self.aws_client = boto3.client('ec2')
    self.azure_credential = DefaultAzureCredential()
    self.gcp_client = compute_v1.VpnGatewaysClient()
    
def establish_site_to_site_vpn(self, on_premise_config):
    """
    オンプレミスと各クラウドプロバイダー間のVPN接続を確立
    """
    connections = {}
    
    # AWS Site-to-Site VPN
    aws_vpn = self.create_aws_vpn(on_premise_config)
    connections['aws'] = aws_vpn
    
    # Azure VPN Gateway
    azure_vpn = self.create_azure_vpn(on_premise_config)
    connections['azure'] = azure_vpn
    
    # GCP Cloud VPN
    gcp_vpn = self.create_gcp_vpn(on_premise_config)
    connections['gcp'] = gcp_vpn
    
    # BGPルーティングの設定
    self.configure_bgp_routing(connections)
    
    return connections

def create_aws_vpn(self, on_premise_config):
    """AWS Site-to-Site VPNの作成"""
    # カスタマーゲートウェイの作成
    cgw_response = self.aws_client.create_customer_gateway(
        BgpAsn=on_premise_config['bgp_asn'],
        PublicIp=on_premise_config['public_ip'],
        Type='ipsec.1',
        TagSpecifications=[{
            'ResourceType': 'customer-gateway',
            'Tags': [
                {'Key': 'Name', 'Value': f"{self.config['project']}-on-premise-cgw"}
            ]
        }]
    )
    
    # VPN接続の作成
    vpn_response = self.aws_client.create_vpn_connection(
        CustomerGatewayId=cgw_response['CustomerGateway']['CustomerGatewayId'],
        Type='ipsec.1',
        VpnGatewayId=self.config['aws_vpn_gateway_id'],
        Options={
            'StaticRoutesOnly': False,  # BGPを使用
            'TunnelOptions': [
                {
                    'TunnelInsideCidr': '169.254.10.0/30',
                    'PreSharedKey': self.generate_psk()
                },
                {
                    'TunnelInsideCidr': '169.254.11.0/30',
                    'PreSharedKey': self.generate_psk()
                }
            ]
        }
    )
    
    return {
        'vpn_connection_id': vpn_response['VpnConnection']['VpnConnectionId'],
        'tunnel_1_address': vpn_response['VpnConnection']['Options']['TunnelOptions'][0]['TunnelInsideCidr'],
        'tunnel_2_address': vpn_response['VpnConnection']['Options']['TunnelOptions'][1]['TunnelInsideCidr']
    }

def configure_hybrid_dns(self):
    """
    ハイブリッド環境でのDNS解決設定
    """
    # Route 53 Resolverエンドポイントの作成
    route53resolver = boto3.client('route53resolver')
    
    # インバウンドエンドポイント（オンプレミス→AWS）
    inbound_endpoint = route53resolver.create_resolver_endpoint(
        CreatorRequestId=f"{self.config['project']}-inbound",
        Name=f"{self.config['project']}-inbound-endpoint",
        SecurityGroupIds=self.config['resolver_security_groups'],
        Direction='INBOUND',
        IpAddresses=[
            {'SubnetId': subnet_id}
            for subnet_id in self.config['resolver_subnet_ids']
        ]
    )
    
    # アウトバウンドエンドポイント（AWS→オンプレミス）
    outbound_endpoint = route53resolver.create_resolver_endpoint(
        CreatorRequestId=f"{self.config['project']}-outbound",
        Name=f"{self.config['project']}-outbound-endpoint",
        SecurityGroupIds=self.config['resolver_security_groups'],
        Direction='OUTBOUND',
        IpAddresses=[
            {'SubnetId': subnet_id}
            for subnet_id in self.config['resolver_subnet_ids']
        ]
    )
    
    # フォワーディングルールの作成
    route53resolver.create_resolver_rule(
        CreatorRequestId=f"{self.config['project']}-forward-rule",
        Name="on-premise-forward",
        RuleType='FORWARD',
        DomainName=self.config['on_premise_domain'],
        TargetIps=[
            {'Ip': ip, 'Port': 53}
            for ip in self.config['on_premise_dns_servers']
        ],
        ResolverEndpointId=outbound_endpoint['ResolverEndpoint']['Id']
    )
    
def implement_data_sync(self):
    """
    ハイブリッド環境でのデータ同期実装
    """
    # AWS DataSyncタスクの作成
    datasync = boto3.client('datasync')
    
    # オンプレミスNFSロケーション
    on_premise_location = datasync.create_location_nfs(
        ServerHostname=self.config['nfs_server'],
        Subdirectory=self.config['nfs_path'],
        OnPremConfig={
            'AgentArns': [self.config['datasync_agent_arn']]
        }
    )
    
    # S3ロケーション
    s3_location = datasync.create_location_s3(
        S3BucketArn=f"arn:aws:s3:::{self.config['s3_bucket']}",
        Subdirectory=self.config['s3_prefix'],
        S3Config={
            'BucketAccessRoleArn': self.config['datasync_role_arn']
        }
    )
    
    # 同期タスクの作成
    sync_task = datasync.create_task(
        SourceLocationArn=on_premise_location['LocationArn'],
        DestinationLocationArn=s3_location['LocationArn'],
        Name=f"{self.config['project']}-hybrid-sync",
        Options={
            'VerifyMode': 'ONLY_FILES_TRANSFERRED',
            'OverwriteMode': 'ALWAYS',
            'Atime': 'NONE',
            'Mtime': 'PRESERVE',
            'PreserveDeletedFiles': 'PRESERVE',
            'PreserveDevices': 'NONE',
            'PosixPermissions': 'PRESERVE',
            'TaskQueueing': 'ENABLED'
        },
        Schedule={
            'ScheduleExpression': 'rate(1 hour)'
        }
    )
    
    return sync_task `

order_service:
  responsibilities:
    - 注文処理
    - 在庫確認
    - 決済連携
  data_ownership:
    - orders テーブル
    - order_items テーブル
  dependencies:
    - user_service（認証）
    - inventory_service（在庫）
    - payment_service（決済）
    
inventory_service:
  responsibilities:
    - 在庫管理
    - 在庫予約
    - 補充管理
  data_ownership:
    - products テーブル
    - inventory テーブル
    - reservations テーブル
  event_publishing:
    - InventoryUpdated
    - LowStockAlert `

def to_dict(self) -> Dict[str, Any]:
    data = asdict(self)
    data['occurred_at'] = self.occurred_at.isoformat()
    return data

async def publish(self, event: DomainEvent):
    """イベントをEventBridgeに発行"""
    async with self.session.client('events') as events:
        response = await events.put_events(
            Entries=[{
                'Source': f'com.example.{event.event_type}',
                'DetailType': event.__class__.__name__,
                'Detail': json.dumps(event.to_dict()),
                'EventBusName': self.event_bus_name
            }]
        )
        
        if response['FailedEntryCount'] > 0:
            raise Exception(f"Failed to publish event: {response['Entries']}")

@abstractmethod
async def handle(self, event: Dict[str, Any]):
    pass

def __init__(self, inventory_service):
    self.inventory_service = inventory_service
    
async def handle(self, event: Dict[str, Any]):
    """注文作成イベントを受けて在庫を予約"""
    order_data = json.loads(event['detail'])
    
    try:
        # 各商品の在庫を予約
        reservations = []
        for item in order_data['items']:
            reservation = await self.inventory_service.reserve_stock(
                product_id=item['product_id'],
                quantity=item['quantity'],
                order_id=order_data['order_id']
            )
            reservations.append(reservation)
        
        # 在庫予約完了イベントを発行
        await self.publish_reservation_completed(
            order_id=order_data['order_id'],
            reservations=reservations
        )
        
    except InsufficientStockError as e:
        # 在庫不足イベントを発行
        await self.publish_insufficient_stock(
            order_id=order_data['order_id'],
            product_id=e.product_id,
            requested=e.requested,
            available=e.available
        )

def __init__(self, state_machine_arn: str):
    self.state_machine_arn = state_machine_arn
    self.session = aioboto3.Session()
    
async def start_order_saga(self, order_data: Dict[str, Any]):
    """注文処理のSagaを開始"""
    async with self.session.client('stepfunctions') as sfn:
        response = await sfn.start_execution(
            stateMachineArn=self.state_machine_arn,
            name=f"order-saga-{order_data['order_id']}",
            input=json.dumps({
                'orderId': order_data['order_id'],
                'customerId': order_data['customer_id'],
                'items': order_data['items'],
                'totalAmount': order_data['total_amount'],
                'sagaStatus': 'STARTED'
            })
        )
        
        return response['executionArn']

def __init__(self, write_db, event_store):
    self.write_db = write_db
    self.event_store = event_store
    
async def handle_create_order(self, command: CreateOrderCommand) -> str:
    """注文作成コマンドの処理"""
    # ビジネスロジックの実行
    order = Order(
        customer_id=command.customer_id,
        items=command.items,
        shipping_address=command.shipping_address,
        status=OrderStatus.PENDING
    )
    
    # 書き込みDBに保存
    await self.write_db.save_order(order)
    
    # イベントストアにイベントを保存
    event = OrderCreatedEvent(
        order_id=order.id,
        customer_id=order.customer_id,
        occurred_at=datetime.utcnow()
    )
    await self.event_store.append(event)
    
    # 読み取りモデルの更新を非同期で実行
    await self.publish_event_for_projection(event)
    
    return order.id

def __init__(self, read_db):
    self.read_db = read_db
    
async def get_order_by_id(self, order_id: str) -> Optional[Dict[str, Any]]:
    """注文IDによる検索（読み取り最適化されたビュー）"""
    return await self.read_db.find_order_view(order_id)
    
async def get_customer_orders(
    self,
    customer_id: str,
    status: Optional[str] = None,
    from_date: Optional[datetime] = None,
    to_date: Optional[datetime] = None,
    limit: int = 100
) -> List[Dict[str, Any]]:
    """顧客の注文履歴検索（複雑なクエリに最適化）"""
    query = {
        'customer_id': customer_id
    }
    
    if status:
        query['status'] = status
        
    if from_date or to_date:
        query['created_at'] = {}
        if from_date:
            query['created_at']['$gte'] = from_date
        if to_date:
            query['created_at']['$lte'] = to_date
            
    return await self.read_db.find_orders(query, limit=limit)

def __init__(self, read_db, cache):
    self.read_db = read_db
    self.cache = cache
    
async def handle_order_created(self, event: OrderCreatedEvent):
    """注文作成イベントから読み取りビューを更新"""
    # 詳細な注文ビューを作成
    order_view = {
        'order_id': event.order_id,
        'customer_id': event.customer_id,
        'created_at': event.occurred_at,
        'status': 'PENDING',
        'total_amount': self.calculate_total(event.items),
        'item_count': len(event.items),
        # 検索用の非正規化データ
        'customer_name': await self.get_customer_name(event.customer_id),
        'product_names': await self.get_product_names(event.items)
    }
    
    # 読み取りDBに保存
    await self.read_db.save_order_view(order_view)
    
    # キャッシュも更新
    await self.cache.set(
        f"order:{event.order_id}",
        order_view,
        expire=3600  # 1時間
    )
    
    # 顧客別の集計ビューも更新
    await self.update_customer_statistics(event.customer_id) `

def __init__(self):
    self.cloudwatch = boto3.client('cloudwatch')
    self.logs = boto3.client('logs')
    self.xray = boto3.client('xray')
    
async def diagnose(self, symptom: Symptom) -> Dict[str, Any]:
    """症状から問題を診断"""
    
    # 1. データ収集
    data = await self.collect_diagnostic_data(symptom)
    
    # 2. 仮説生成
    hypotheses = self.generate_hypotheses(symptom, data)
    
    # 3. 仮説検証
    verified_hypotheses = await self.verify_hypotheses(hypotheses, data)
    
    # 4. 根本原因分析
    root_cause = self.identify_root_cause(verified_hypotheses)
    
    # 5. 解決策の提案
    solutions = self.propose_solutions(root_cause)
    
    return {
        'symptom': symptom,
        'collected_data': data,
        'hypotheses': hypotheses,
        'verified_hypotheses': verified_hypotheses,
        'root_cause': root_cause,
        'proposed_solutions': solutions,
        'diagnosis_timestamp': datetime.utcnow()
    }

async def collect_diagnostic_data(self, symptom: Symptom) -> Dict[str, Any]:
    """診断に必要なデータを収集"""
    
    data = {}
    time_range = self.determine_time_range(symptom)
    
    # メトリクスデータの収集
    for component in symptom.affected_components:
        metrics = await self.collect_metrics(component, time_range)
        data[f'{component}_metrics'] = metrics
        
    # ログデータの収集
    logs = await self.collect_logs(symptom.affected_components, time_range)
    data['logs'] = logs
    
    # トレースデータの収集
    traces = await self.collect_traces(time_range)
    data['traces'] = traces
    
    # 関連イベントの収集
    events = await self.collect_events(time_range)
    data['events'] = events
    
    return data

def generate_hypotheses(self, symptom: Symptom, data: Dict[str, Any]) -> List[Hypothesis]:
    """症状とデータから仮説を生成"""
    
    hypotheses = []
    
    # パフォーマンス劣化の場合
    if "slow" in symptom.description.lower() or "latency" in symptom.description.lower():
        hypotheses.extend([
            Hypothesis(
                description="CPU使用率の上昇によるパフォーマンス劣化",
                probability=self.calculate_cpu_hypothesis_probability(data),
                test_method="CPU使用率とレスポンスタイムの相関分析",
                required_data=["cpu_utilization", "response_time"]
            ),
            Hypothesis(
                description="データベースのスロークエリによる遅延",
                probability=self.calculate_db_hypothesis_probability(data),
                test_method="データベースクエリログの分析",
                required_data=["db_query_logs", "db_cpu_utilization"]
            ),
            Hypothesis(
                description="ネットワーク遅延による影響",
                probability=self.calculate_network_hypothesis_probability(data),
                test_method="ネットワークレイテンシの測定",
                required_data=["network_latency", "packet_loss"]
            )
        ])
    
    # エラー増加の場合
    if "error" in symptom.description.lower() or "fail" in symptom.description.lower():
        hypotheses.extend([
            Hypothesis(
                description="依存サービスの障害",
                probability=self.calculate_dependency_hypothesis_probability(data),
                test_method="依存サービスのヘルスチェック",
                required_data=["dependency_health", "circuit_breaker_status"]
            ),
            Hypothesis(
                description="リソース枯渇によるエラー",
                probability=self.calculate_resource_hypothesis_probability(data),
                test_method="リソース使用状況の分析",
                required_data=["memory_utilization", "disk_space", "connection_pool"]
            )
        ])
    
    # 確率でソート
    hypotheses.sort(key=lambda h: h.probability, reverse=True)
    
    return hypotheses

async def verify_hypotheses(
    self,
    hypotheses: List[Hypothesis],
    data: Dict[str, Any]
) -> List[Tuple[Hypothesis, bool, Dict[str, Any]]]:
    """仮説を検証"""
    
    verified = []
    
    for hypothesis in hypotheses:
        # 必要なデータが揃っているか確認
        if all(key in data for key in hypothesis.required_data):
            # 仮説に応じた検証を実行
            if "CPU" in hypothesis.description:
                result = self.verify_cpu_hypothesis(data)
            elif "データベース" in hypothesis.description:
                result = await self.verify_database_hypothesis(data)
            elif "ネットワーク" in hypothesis.description:
                result = self.verify_network_hypothesis(data)
            elif "依存サービス" in hypothesis.description:
                result = await self.verify_dependency_hypothesis(data)
            else:
                result = (False, {})
            
            verified.append((hypothesis, result[0], result[1]))
    
    return verified

def identify_root_cause(
    self,
    verified_hypotheses: List[Tuple[Hypothesis, bool, Dict[str, Any]]]
) -> Optional[Dict[str, Any]]:
    """根本原因を特定"""
    
    # 検証された仮説から最も可能性の高いものを選択
    confirmed = [(h, evidence) for h, verified, evidence in verified_hypotheses if verified]
    
    if not confirmed:
        return None
    
    # 因果関係を分析
    root_cause = {
        'primary_cause': confirmed[0][0].description,
        'evidence': confirmed[0][1],
        'confidence': self.calculate_confidence(confirmed),
        'contributing_factors': [h.description for h, _ in confirmed[1:]]
    }
    
    return root_cause

def propose_solutions(self, root_cause: Optional[Dict[str, Any]]) -> List[Dict[str, Any]]:
    """解決策を提案"""
    
    if not root_cause:
        return [{
            'action': '追加調査',
            'description': '根本原因を特定できませんでした。より詳細なログとメトリクスの収集が必要です。',
            'priority': 'HIGH'
        }]
    
    solutions = []
    
    # 原因に応じた解決策
    if "CPU" in root_cause['primary_cause']:
        solutions.extend([
            {
                'action': 'スケールアウト',
                'description': 'インスタンス数を増やしてCPU負荷を分散',
                'priority': 'HIGH',
                'implementation': 'aws autoscaling set-desired-capacity --desired-capacity +2'
            },
            {
                'action': 'コード最適化',
                'description': 'CPU使用率の高い処理を特定し最適化',
                'priority': 'MEDIUM',
                'implementation': 'プロファイリングツールで特定後、アルゴリズム改善'
            }
        ])
    
    elif "データベース" in root_cause['primary_cause']:
        solutions.extend([
            {
                'action': 'クエリ最適化',
                'description': 'スロークエリを特定し、インデックスを追加',
                'priority': 'HIGH',
                'implementation': 'EXPLAIN ANALYZEで実行計画を確認し、適切なインデックスを作成'
            },
            {
                'action': 'リードレプリカ追加',
                'description': '読み取り負荷を分散',
                'priority': 'MEDIUM',
                'implementation': 'RDSリードレプリカを作成し、読み取りクエリを振り分け'
            }
        ])
    
    return solutions

engine = TroubleshootingEngine()

# 観測された症状
symptom = Symptom(
    description="APIレスポンスタイムが通常の3倍に増加",
    severity="HIGH",
    first_observed=datetime.utcnow() - timedelta(hours=2),
    frequency="CONSTANT",
    affected_components=["api-gateway", "app-server", "database"]
)

# 診断実行
diagnosis = await engine.diagnose(symptom)

# 結果のレポート生成
report = generate_diagnosis_report(diagnosis)

# Slackに通知
await notify_slack(report)

# 自動修復可能な場合は実行
if diagnosis['proposed_solutions']:
    auto_remediation_solutions = [
        s for s in diagnosis['proposed_solutions']
        if s.get('auto_remediation', False)
    ]
    
    for solution in auto_remediation_solutions:
        await execute_remediation(solution) `

def setup_cdc(self):
    """Change Data Captureのセットアップ"""
    # AWS DMS を使用したリアルタイムレプリケーション
    dms = boto3.client('dms')
    
    # レプリケーションインスタンスの作成
    replication_instance = dms.create_replication_instance(
        ReplicationInstanceIdentifier='finance-hybrid-sync',
        ReplicationInstanceClass='dms.r5.large',
        MultiAZ=True,
        PubliclyAccessible=False,
        VpcSecurityGroupIds=['sg-secure-dms']
    )
    
    # ソースとターゲットのエンドポイント作成
    source_endpoint = dms.create_endpoint(
        EndpointIdentifier='on-premise-oracle',
        EndpointType='source',
        EngineName='oracle',
        ServerName='10.0.1.100',
        Port=1521,
        DatabaseName='FINCORE',
        SslMode='require'
    )
    
    target_endpoint = dms.create_endpoint(
        EndpointIdentifier='cloud-aurora',
        EndpointType='target',
        EngineName='aurora-postgresql',
        ServerName='finance-aurora.cluster-xxx.amazonaws.com',
        Port=5432,
        DatabaseName='fincore'
    )
    
    return dms `