Redmineの設定

🎯 Phase 4: 高度な機能実装¶

概要¶

インフラヘルパーサービスをより強力なツールにするための高度な機能を実装する。

対応期限¶

2025年9月15日（10週間）

実装タスク¶

🔍 4-1. 高度な監視・分析機能¶

メトリクス収集・可視化¶

// Prometheus形式のメトリクスエクスポート
GET /api/v1/metrics/prometheus

// カスタムダッシュボード
POST /api/v1/dashboards
  Body:
    - name: "Production Overview"
    - widgets: [
        {
          type: "graph",
          metric: "cpu_usage",
          containers: ["app1", "app2"],
          timeRange: "1h"
        },
        {
          type: "gauge",
          metric: "memory_usage",
          container: "database"
        }
      ]

// 時系列データ取得
GET /api/v1/metrics/timeseries
  Query:
    - metric: "cpu_usage"
    - containers: ["app1", "app2"]
    - from: "2025-01-01T00:00:00Z"
    - to: "2025-01-02T00:00:00Z"
    - resolution: "1m"

実装詳細¶

// backend/services/metricsCollector.js
class MetricsCollector {
  constructor() {
    this.timeseries = new TimeSeriesDB();
    this.collectors = new Map();
  }
  
  async collectMetrics() {
    const containers = await docker.listContainers();
    
    for (const container of containers) {
      const stats = await docker.getContainer(container.Id).stats({ stream: false });
      
      // CPU使用率計算
      const cpuDelta = stats.cpu_stats.cpu_usage.total_usage - stats.precpu_stats.cpu_usage.total_usage;
      const systemDelta = stats.cpu_stats.system_cpu_usage - stats.precpu_stats.system_cpu_usage;
      const cpuPercent = (cpuDelta / systemDelta) * stats.cpu_stats.online_cpus * 100;
      
      // メモリ使用率計算
      const memoryUsage = stats.memory_stats.usage;
      const memoryLimit = stats.memory_stats.limit;
      const memoryPercent = (memoryUsage / memoryLimit) * 100;
      
      // ネットワーク統計
      const networkRx = stats.networks?.eth0?.rx_bytes || 0;
      const networkTx = stats.networks?.eth0?.tx_bytes || 0;
      
      // 時系列データベースに保存
      await this.timeseries.insert({
        container: container.Names[0],
        timestamp: new Date(),
        metrics: {
          cpu_usage: cpuPercent,
          memory_usage: memoryPercent,
          memory_bytes: memoryUsage,
          network_rx_bytes: networkRx,
          network_tx_bytes: networkTx,
          disk_read_bytes: stats.blkio_stats?.io_service_bytes_recursive?.[0]?.value || 0,
          disk_write_bytes: stats.blkio_stats?.io_service_bytes_recursive?.[1]?.value || 0
        }
      });
    }
  }
  
  async getTimeSeries(query) {
    return this.timeseries.query({
      metric: query.metric,
      containers: query.containers,
      start: query.from,
      end: query.to,
      resolution: query.resolution
    });
  }
}

🚀 4-2. 自動スケーリング・最適化¶

APIエンドポイント設計¶

// スケーリングポリシー設定
POST /api/v1/scaling/policies
  Body:
    - name: "Web App Auto Scaling"
    - target: "web-app"
    - minReplicas: 2
    - maxReplicas: 10
    - metrics: [
        {
          type: "cpu",
          targetValue: 70
        },
        {
          type: "memory",
          targetValue: 80
        },
        {
          type: "requests_per_second",
          targetValue: 1000
        }
      ]

// リソース最適化提案
GET /api/v1/optimization/suggestions
  Response:
    - suggestions: [
        {
          container: "app1",
          current: { cpu: "1000m", memory: "2Gi" },
          recommended: { cpu: "500m", memory: "1Gi" },
          reason: "Average usage is 30% of allocated resources"
        }
      ]

実装詳細¶

// backend/services/autoScaler.js
class AutoScaler {
  async evaluateScaling(policy) {
    const currentReplicas = await this.getCurrentReplicas(policy.target);
    const metrics = await this.getMetrics(policy.target, policy.metrics);
    
    let desiredReplicas = currentReplicas;
    
    for (const metric of metrics) {
      const utilization = metric.current / metric.target;
      
      if (utilization > 1.1) { // 110%を超えたらスケールアップ
        desiredReplicas = Math.ceil(currentReplicas * utilization);
      } else if (utilization < 0.5 && currentReplicas > policy.minReplicas) {
        desiredReplicas = Math.floor(currentReplicas * utilization);
      }
    }
    
    desiredReplicas = Math.max(policy.minReplicas, Math.min(policy.maxReplicas, desiredReplicas));
    
    if (desiredReplicas !== currentReplicas) {
      await this.scale(policy.target, desiredReplicas);
    }
  }
  
  async scale(target, replicas) {
    // Docker Swarmモードの場合
    await execAsync(`docker service scale ${target}=${replicas}`);
    
    // Docker Composeの場合
    await execAsync(`docker-compose up -d --scale ${target}=${replicas}`);
    
    // 通知
    wsManager.broadcast({
      type: 'scaling',
      target,
      replicas,
      timestamp: new Date()
    });
  }
}

🛡️ 4-3. セキュリティ監査・コンプライアンス¶

APIエンドポイント設計¶

// セキュリティスキャン実行
POST /api/v1/security/scan
  Body:
    - targets: ['images', 'containers', 'network', 'volumes']
    - scanType: 'vulnerability' | 'compliance' | 'full'

// コンプライアンスチェック
GET /api/v1/compliance/check
  Query:
    - standard: 'CIS' | 'PCI-DSS' | 'HIPAA'

// セキュリティレポート
GET /api/v1/security/report
  Query:
    - format: 'json' | 'pdf' | 'html'

実装詳細¶

// backend/services/securityScanner.js
class SecurityScanner {
  async scanImages() {
    const images = await docker.listImages();
    const vulnerabilities = [];
    
    for (const image of images) {
      // Trivyを使用した脆弱性スキャン
      const { stdout } = await execAsync(`trivy image --format json ${image.RepoTags[0]}`);
      const scanResult = JSON.parse(stdout);
      
      vulnerabilities.push({
        image: image.RepoTags[0],
        created: image.Created,
        size: image.Size,
        vulnerabilities: scanResult.Results?.[0]?.Vulnerabilities || [],
        summary: {
          critical: scanResult.Results?.[0]?.Vulnerabilities?.filter(v => v.Severity === 'CRITICAL').length || 0,
          high: scanResult.Results?.[0]?.Vulnerabilities?.filter(v => v.Severity === 'HIGH').length || 0,
          medium: scanResult.Results?.[0]?.Vulnerabilities?.filter(v => v.Severity === 'MEDIUM').length || 0,
          low: scanResult.Results?.[0]?.Vulnerabilities?.filter(v => v.Severity === 'LOW').length || 0
        }
      });
    }
    
    return vulnerabilities;
  }
  
  async checkCompliance(standard) {
    const checks = this.getComplianceChecks(standard);
    const results = [];
    
    for (const check of checks) {
      const result = await this.runComplianceCheck(check);
      results.push({
        id: check.id,
        title: check.title,
        status: result.passed ? 'PASS' : 'FAIL',
        severity: check.severity,
        details: result.details
      });
    }
    
    return {
      standard,
      timestamp: new Date(),
      summary: {
        total: results.length,
        passed: results.filter(r => r.status === 'PASS').length,
        failed: results.filter(r => r.status === 'FAIL').length
      },
      results
    };
  }
}

🔗 4-4. 統合・拡張機能¶

Webhook統合¶

// Webhook設定
POST /api/v1/integrations/webhooks
  Body:
    - name: "Deployment Notification"
    - url: "https://example.com/webhook"
    - events: ["container.start", "container.stop", "alert.triggered"]
    - headers: { "Authorization": "Bearer token" }

// カスタムプラグイン
POST /api/v1/plugins/install
  Body:
    - name: "custom-monitor"
    - source: "https://github.com/user/plugin"
    - config: { /* プラグイン設定 */ }

GraphQL API実装¶

// GraphQLスキーマ
type Query {
  containers(status: ContainerStatus): [Container!]!
  metrics(container: String!, metric: String!, timeRange: TimeRange!): MetricData!
  alerts(status: AlertStatus): [Alert!]!
  backups(limit: Int): [Backup!]!
}

type Mutation {
  startContainer(id: String!): Container!
  stopContainer(id: String!): Container!
  createBackup(options: BackupOptions!): Backup!
  acknowledgeAlert(id: String!): Alert!
}

type Subscription {
  containerEvents: ContainerEvent!
  metricUpdates(containers: [String!]!): MetricUpdate!
  alertTriggered: Alert!
}

📊 4-5. 高度なUI/UX機能¶

React実装の強化¶

// リアルタイムダッシュボード
function RealtimeDashboard() {
  const [metrics, setMetrics] = useState({});
  const [selectedContainers, setSelectedContainers] = useState([]);
  
  useEffect(() => {
    const ws = new WebSocket(`${WS_URL}/metrics`);
    
    ws.onmessage = (event) => {
      const update = JSON.parse(event.data);
      setMetrics(prev => ({
        ...prev,
        [update.container]: update.metrics
      }));
    };
    
    return () => ws.close();
  }, []);
  
  return (
    <div className="grid grid-cols-1 md:grid-cols-2 lg:grid-cols-3 gap-4">
      {selectedContainers.map(container => (
        <MetricCard
          key={container}
          container={container}
          metrics={metrics[container]}
        />
      ))}
    </div>
  );
}

// 3D可視化
function Network3DVisualization() {
  useEffect(() => {
    const scene = new THREE.Scene();
    const camera = new THREE.PerspectiveCamera(75, window.innerWidth / window.innerHeight, 0.1, 1000);
    const renderer = new THREE.WebGLRenderer();
    
    // コンテナをノードとして表示
    containers.forEach((container, index) => {
      const geometry = new THREE.SphereGeometry(1, 32, 32);
      const material = new THREE.MeshBasicMaterial({
        color: container.status === 'running' ? 0x00ff00 : 0xff0000
      });
      const sphere = new THREE.Mesh(geometry, material);
      sphere.position.set(
        Math.cos(index * Math.PI * 2 / containers.length) * 10,
        0,
        Math.sin(index * Math.PI * 2 / containers.length) * 10
      );
      scene.add(sphere);
    });
    
    // ネットワーク接続をラインで表示
    // ... Three.js実装
  }, [containers]);
}

テスト計画¶

• 単体テスト（Jest）: カバレッジ90%以上
• 統合テスト: 全APIエンドポイント
• E2Eテスト（Playwright）: 主要ユーザーフロー
• 負荷テスト: 1000同時接続、10000 req/sec
• セキュリティテスト: OWASP Top 10

成果物¶

• 完全実装された高度な機能セット
• GraphQL APIドキュメント
• プラグイン開発ガイド
• パフォーマンス最適化レポート
• セキュリティ監査レポート