Kubernetes 上部署 Tardis 数据采集服务：定时下载与增量更新

概要

システム構成のアーキテクチャ

┌─────────────────────────────────────────────────────────────┐
│                    Kubernetes Cluster                        │
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────────────┐  │
│  │   CronJob   │  │   Pod 1     │  │   Persistent Volume │  │
│  │  (Scheduler)│──│  (Tardis)   │──│   (增量データ保存)   │  │
│  └─────────────┘  └─────────────┘  └─────────────────────┘  │
│         │                │                    ▲              │
│         ▼                ▼                    │              │
│  ┌─────────────┐  ┌─────────────────────────────┐           │
│  │ ConfigMap   │  │   HolySheep API Endpoint    │           │
│  │ (設定管理)  │  │   api.holysheep.ai/v1       │           │
│  └─────────────┘  └─────────────────────────────┘           │
└─────────────────────────────────────────────────────────────┘

向いている人・向いていない人

価格とROI

HolySheepを選ぶ理由

• 85%コスト削減：¥1=$1の為替レートで、公式の¥7.3/$1と比べて大幅節約
• 微秒対応：中国本土の決済方法で、WeChat Pay ・ Alipay に対応
• <50ms 低レイテンシ：アジアリージョン最优で、定期的なデータ更新もスムーズ
• 免费クレジット付き：登録するだけで即座に экспериメントを開始可能
• シンプルなAPI：OpenAI-Compatible形式で既有コードの移行が容易

前提条件と环境構築

# Kubernetes クラスターの確認
kubectl version --client
kubectl cluster-info

必要なツールのインストール
Kind（ローカル開発用）或いはEKS/GKEなどのクラウドクラスター
kind create cluster --name tardis-cluster

Helm のインストール（パッケージマネージャー）
curl -fsSL -o get_helm.sh https://raw.githubusercontent.com/helm/helm/main/scripts/get-helm-3
chmod 700 get_helm.sh
./get_helm.sh

Tardis データ収集サービスの実装

#!/usr/bin/env python3
"""
Tardis Data Collector - Kubernetes CronJob 用
定时下载与增量更新机制の実装
"""

import os
import json
import hashlib
import sqlite3
from datetime import datetime, timedelta
from pathlib import Path
from typing import Optional, Dict, Any, List

import requests

HolySheep API 設定
BASE_URL = "https://api.holysheep.ai/v1"
API_KEY = os.getenv("HOLYSHEEP_API_KEY", "YOUR_HOLYSHEEP_API_KEY")

class TardisDataCollector:
    """Tardis データ収集クラス - 增量更新対応"""
    
    def __init__(self, db_path: str = "/data/tardis.db", checkpoint_path: str = "/data/checkpoint.json"):
        self.db_path = db_path
        self.checkpoint_path = checkpoint_path
        self.base_url = BASE_URL
        self.api_key = API_KEY
        self._init_database()
        self._load_checkpoint()
    
    def _init_database(self):
        """SQLiteデータベースの初期化"""
        os.makedirs(os.path.dirname(self.db_path), exist_ok=True)
        conn = sqlite3.connect(self.db_path)
        cursor = conn.cursor()
        
        # メインレコードテーブル
        cursor.execute('''
            CREATE TABLE IF NOT EXISTS records (
                id TEXT PRIMARY KEY,
                data TEXT NOT NULL,
                hash TEXT NOT NULL,
                created_at TEXT NOT NULL,
                updated_at TEXT NOT NULL,
                version INTEGER DEFAULT 1
            )
        ''')
        
        # 增量更新履歴テーブル
        cursor.execute('''
            CREATE TABLE IF NOT EXISTS change_log (
                id INTEGER PRIMARY KEY AUTOINCREMENT,
                record_id TEXT NOT NULL,
                change_type TEXT NOT NULL,
                old_hash TEXT,
                new_hash TEXT,
                changed_at TEXT NOT NULL,
                FOREIGN KEY (record_id) REFERENCES records(id)
            )
        ''')
        
        # メタデータテーブル
        cursor.execute('''
            CREATE TABLE IF NOT EXISTS metadata (
                key TEXT PRIMARY KEY,
                value TEXT NOT NULL,
                updated_at TEXT NOT NULL
            )
        ''')
        
        conn.commit()
        conn.close()
    
    def _load_checkpoint(self):
        """チェックポイント（最終実行状態）の読み込み"""
        if os.path.exists(self.checkpoint_path):
            with open(self.checkpoint_path, 'r') as f:
                self.checkpoint = json.load(f)
        else:
            self.checkpoint = {
                "last_run": None,
                "last_record_id": None,
                "total_collected": 0,
                "total_updated": 0
            }
    
    def _save_checkpoint(self):
        """チェックポイントの保存"""
        with open(self.checkpoint_path, 'w') as f:
            json.dump(self.checkpoint, f, indent=2)
    
    def _compute_hash(self, data: Any) -> str:
        """データの整合性チェック用ハッシュ計算"""
        data_str = json.dumps(data, sort_keys=True, default=str)
        return hashlib.sha256(data_str.encode()).hexdigest()
    
    def _get_api_response(self, prompt: str, model: str = "deepseek-chat") -> Dict[str, Any]:
        """HolySheep API 呼び出し"""
        headers = {
            "Authorization": f"Bearer {self.api_key}",
            "Content-Type": "application/json"
        }
        
        payload = {
            "model": model,
            "messages": [
                {"role": "user", "content": prompt}
            ],
            "temperature": 0.3
        }
        
        response = requests.post(
            f"{self.base_url}/chat/completions",
            headers=headers,
            json=payload,
            timeout=30
        )
        
        if response.status_code != 200:
            raise RuntimeError(f"API Error: {response.status_code} - {response.text}")
        
        return response.json()
    
    def collect_from_source(self, source: str, batch_size: int = 100) -> Dict[str, Any]:
        """外部ソースからのデータ収集（例：EC 商品API）"""
        conn = sqlite3.connect(self.db_path)
        cursor = conn.cursor()
        
        stats = {
            "collected": 0,
            "updated": 0,
            "unchanged": 0,
            "errors": []
        }
        
        # 增量取得の開始位置决定
        start_id = self.checkpoint.get("last_record_id")
        offset = 0
        if start_id:
            cursor.execute("SELECT COUNT(*) FROM records")
            offset = cursor.fetchone()[0]
        
        # バッチ処理でデータ取得
        page = 0
        while True:
            # 實際には here で商品API等呼叫
            # simulate_api_call(source, start_id, batch_size)
            data_batch = self._fetch_data_batch(source, offset + page * batch_size, batch_size)
            
            if not data_batch:
                break
            
            for item in data_batch:
                try:
                    record_id = item.get("id")
                    data_str = json.dumps(item, default=str)
                    new_hash = self._compute_hash(item)
                    
                    # 既存チェック
                    cursor.execute("SELECT hash, version FROM records WHERE id = ?", (record_id,))
                    existing = cursor.fetchone()
                    
                    if existing:
                        old_hash, version = existing
                        if old_hash != new_hash:
                            # 增量更新：変更があるレコードのみ更新
                            cursor.execute('''
                                UPDATE records 
                                SET data = ?, hash = ?, updated_at = ?, version = ?
                                WHERE id = ?
                            ''', (data_str, new_hash, datetime.utcnow().isoformat(), version + 1, record_id))
                            
                            cursor.execute('''
                                INSERT INTO change_log (record_id, change_type, old_hash, new_hash, changed_at)
                                VALUES (?, 'UPDATE', ?, ?, ?)
                            ''', (record_id, old_hash, new_hash, datetime.utcnow().isoformat()))
                            
                            stats["updated"] += 1
                        else:
                            stats["unchanged"] += 1
                    else:
                        # 新規レコード追加
                        cursor.execute('''
                            INSERT INTO records (id, data, hash, created_at, updated_at, version)
                            VALUES (?, ?, ?, ?, ?, 1)
                        ''', (record_id, data_str, new_hash, datetime.utcnow().isoformat(), datetime.utcnow().isoformat()))
                        
                        cursor.execute('''
                            INSERT INTO change_log (record_id, change_type, changed_at)
                            VALUES (?, 'INSERT', ?)
                        ''', (record_id, datetime.utcnow().isoformat()))
                        
                        stats["collected"] += 1
                    
                    self.checkpoint["last_record_id"] = record_id
                    
                except Exception as e:
                    stats["errors"].append({"record_id": item.get("id"), "error": str(e)})
            
            page += 1
            if len(data_batch) < batch_size:
                break
        
        conn.commit()
        conn.close()
        
        # チェックポイント更新
        self.checkpoint["last_run"] = datetime.utcnow().isoformat()
        self.checkpoint["total_collected"] += stats["collected"]
        self.checkpoint["total_updated"] += stats["updated"]
        self._save_checkpoint()
        
        return stats
    
    def _fetch_data_batch(self, source: str, offset: int, limit: int) -> List[Dict]:
        """ダミーデータ取得（実際はAPI呼叫に置き換え）"""
        # EC 商品データを模擬
        return [
            {
                "id": f"PROD-{offset + i:06d}",
                "name": f"商品 {offset + i}",
                "price": 1000 + i * 100,
                "stock": 50 - (i % 10),
                "category": ["電子機器", "衣類", "食品"][i % 3]
            }
            for i in range(min(limit, 10))  # 実際はAPI応答数
        ]
    
    def get_changes_since(self, since: str) -> List[Dict]:
        """特定日時以降の变更履歷を取得（RAG용）"""
        conn = sqlite3.connect(self.db_path)
        cursor = conn.cursor()
        
        cursor.execute('''
            SELECT r.id, r.data, r.updated_at, cl.change_type
            FROM records r
            JOIN change_log cl ON r.id = cl.record_id
            WHERE cl.changed_at > ?
            ORDER BY cl.changed_at ASC
        ''', (since,))
        
        results = [
            {
                "id": row[0],
                "data": json.loads(row[1]),
                "updated_at": row[2],
                "change_type": row[3]
            }
            for row in cursor.fetchall()
        ]
        
        conn.close()
        return results
    
    def sync_to_ai_service(self, records: List[Dict]) -> bool:
        """AI 服务への同期処理"""
        for record in records:
            try:
                # HolySheep API でベクトル化して保存
                prompt = f"""以下の商品データを简潔に説明してください:
商品ID: {record['id']}
商品名: {record['data']['name']}
価格: {record['data']['price']}円
カテゴリ: {record['data']['category']}"""
                
                response = self._get_api_response(
                    prompt, 
                    model="deepseek-chat"
                )
                
                embedding = response["choices"][0]["message"]["content"]
                
                # here でベクトルDBに保存
                # save_to_vector_db(record['id'], embedding)
                print(f"Synced: {record['id']}")
                
            except Exception as e:
                print(f"Sync error for {record['id']}: {e}")
                return False
        
        return True


def main():
    collector = TardisDataCollector()
    
    # 定时実行のメイン処理
    source = os.getenv("DATA_SOURCE", "ec-products-api")
    stats = collector.collect_from_source(source)
    
    print(f"収集完了: 新規={stats['collected']}, 更新={stats['updated']}, 不変={stats['unchanged']}")
    
    # 错误がある場合
    if stats['errors']:
        print(f"エラー: {len(stats['errors'])}件")
        for err in stats['errors'][:5]:
            print(f"  - {err}")


if __name__ == "__main__":
    main()

Kubernetes CronJob マニフェスト

# tardis-cronjob.yaml
apiVersion: batch/v1
kind: CronJob
metadata:
  name: tardis-data-collector
  namespace: data-platform
  labels:
    app: tardis
    component: collector
spec:
  # 深夜2時に実行（ECピーク時間帯外）
  schedule: "0 2 * * *"
  concurrencyPolicy: Forbid
  successfulJobsHistoryLimit: 3
  failedJobsHistoryLimit: 2
  startingDeadlineSeconds: 300
  jobTemplate:
    spec:
      backoffLimit: 3
      ttlSecondsAfterFinished: 3600
      template:
        metadata:
          labels:
            app: tardis
            component: collector
        spec:
          restartPolicy: OnFailure
          containers:
          - name: tardis-collector
            image: tardis-collector:v1.2.0
            imagePullPolicy: Always
            env:
            - name: HOLYSHEEP_API_KEY
              valueFrom:
                secretKeyRef:
                  name: holysheep-credentials
                  key: api-key
            - name: DATA_SOURCE
              value: "ec-products-api"
            - name: TZ
              value: "Asia/Shanghai"
            resources:
              requests:
                memory: "256Mi"
                cpu: "250m"
              limits:
                memory: "512Mi"
                cpu: "500m"
            volumeMounts:
            - name: tardis-data
              mountPath: /data
            livenessProbe:
              exec:
                command: ["cat", "/tmp/healthy"]
              initialDelaySeconds: 10
              periodSeconds: 60
          volumes:
          - name: tardis-data
            persistentVolumeClaim:
              claimName: tardis-data-pvc
          nodeSelector:
            workload-type: batch
          tolerations:
          - key: "batch-only"
            operator: "Exists"
            effect: "NoSchedule"

---
PVC（永続ボリューム要求）
apiVersion: v1
kind: PersistentVolumeClaim
metadata:
  name: tardis-data-pvc
  namespace: data-platform
spec:
  accessModes:
    - ReadWriteOnce
  storageClassName: standard-ssd
  resources:
    requests:
      storage: 10Gi

---
ConfigMap（スケジュール設定）
apiVersion: v1
kind: ConfigMap
metadata:
  name: tardis-config
  namespace: data-platform
data:
  schedule.conf: |
    default_interval: "0 2 * * *"
    ec_peak_hours: "10:00-22:00"
    batch_size: "100"
    retry_attempts: "3"
  sources.yaml: |
    ec-products-api:
      endpoint: "https://api.example-ec.com/products"
      auth_type: "oauth2"
      rate_limit: 100
    inventory-sync:
      endpoint: "https://api.example-ec.com/inventory"
      auth_type: "api_key"

---
Secret（API認証情報）
apiVersion: v1
kind: Secret
metadata:
  name: holysheep-credentials
  namespace: data-platform
type: Opaque
stringData:
  api-key: "YOUR_HOLYSHEEP_API_KEY"

Kubernetes Deployment（常駐サービス版）

# tardis-deployment.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: tardis-api-server
  namespace: data-platform
  labels:
    app: tardis
    component: api-server
spec:
  replicas: 2
  selector:
    matchLabels:
      app: tardis
      component: api-server
  strategy:
    type: RollingUpdate
    rollingUpdate:
      maxSurge: 1
      maxUnavailable: 0
  template:
    metadata:
      labels:
        app: tardis
        component: api-server
    spec:
      containers:
      - name: tardis-api
        image: tardis-api:v1.2.0
        ports:
        - containerPort: 8080
          name: http
        env:
        - name: HOLYSHEEP_API_KEY
          valueFrom:
            secretKeyRef:
              name: holysheep-credentials
              key: api-key
        - name: DATABASE_PATH
          value: "/data/tardis.db"
        - name: CHECKPOINT_PATH
          value: "/data/checkpoint.json"
        resources:
          requests:
            memory: "512Mi"
            cpu: "500m"
          limits:
            memory: "1Gi"
            cpu: "1000m"
        volumeMounts:
        - name: tardis-data
          mountPath: /data
        readinessProbe:
          httpGet:
            path: /health
            port: 8080
          initialDelaySeconds: 5
          periodSeconds: 10
        livenessProbe:
          httpGet:
            path: /health
            port: 8080
          initialDelaySeconds: 15
          periodSeconds: 30
      volumes:
      - name: tardis-data
        persistentVolumeClaim:
          claimName: tardis-data-pvc

---
Service
apiVersion: v1
kind: Service
metadata:
  name: tardis-api-service
  namespace: data-platform
spec:
  type: ClusterIP
  selector:
    app: tardis
    component: api-server
  ports:
  - port: 80
    targetPort: 8080
    protocol: TCP
    name: http

---
HorizontalPodAutoscaler
apiVersion: autoscaling/v2
kind: HorizontalPodAutoscaler
metadata:
  name: tardis-api-hpa
  namespace: data-platform
spec:
  scaleTargetRef:
    apiVersion: apps/v1
    kind: Deployment
    name: tardis-api-server
  minReplicas: 2
  maxReplicas: 10
  metrics:
  - type: Resource
    resource:
      name: cpu
      target:
        type: Utilization
        averageUtilization: 70
  - type: Resource
    resource:
      name: memory
      target:
        type: Utilization
        averageUtilization: 80

デプロイと実行

# 1. 名前空間とリソースの作成
kubectl apply -f tardis-cronjob.yaml
kubectl apply -f tardis-deployment.yaml

2. Pod の状態確認
kubectl get pods -n data-platform -l app=tardis

3. CronJob の手動実行（テスト用）
kubectl create job --from=cronjob/tardis-data-collector tardis-manual-run -n data-platform

4. ログの確認
kubectl logs -n data-platform -l app=tardis -f

5. PersistentVolume の状態確認
kubectl get pvc -n data-platform

6. スケジュール执行结果の確認
kubectl get cronjob -n data-platform
kubectl describe cronjob tardis-data-collector -n data-platform

7. AI服务の同期状态確認
kubectl exec -it $(kubectl get pod -n data-platform -l app=tardis -o jsonpath='{.items[0].metadata.name}') -n data-platform -- python -c "
from tardis_collector import TardisDataCollector
collector = TardisDataCollector()
since = '2024-01-01T00:00:00'
changes = collector.get_changes_since(since)
print(f'変更レコード数: {len(changes)}')
"

データの流れ（EC AI客服の例）

[EC商品DB]
    ↓ 深夜CronJob実行
[Tardis Collector - K8s CronJob]
    ↓ 增量データ抽出
[SQLite + Checkpoint]
    ↓ 增量更新のみ通知
[HolySheep API - DeepSeek V3.2]
    ↓ 構造化データ生成
[Vector DB (Pinecone/Milvus)]
    ↓ リアルタイム検索
[AI Chatbot - 客服応答]

よくあるエラーと対処法

# Secretの確認と更新
kubectl get secret holysheep-credentials -n data-platform -o yaml
kubectl create secret generic holysheep-credentials \
  --from-literal=api-key='YOUR_HOLYSHEEP_API_KEY' \
  --dry-run=client -o yaml | kubectl apply -f -

# CronJob の再開
kubectl cronjob resume tardis-data-collector -n data-platform

或いはスケジュールを一時的に変更
kubectl patch cronjob tardis-data-collector -n data-platform \
  -p '{"spec":{"suspend":false}}'

# StatefulSetへの変更（PVCのバインド维持）
或いは PVC の accessModes を ReadWriteOnce から変更
Deployment の strategy を Recreate に変更
kubectl patch deployment tardis-api-server -n data-platform \
  -p '{"spec":{"strategy":{"type":"Recreate"}}}'

# ConfigMap で rate_limit を设定
或いはリクエスト間に retry + backoff を実装
import time
def api_call_with_retry(prompt, max_retries=3):
    for i in range(max_retries):
        try:
            return get_api_response(prompt)
        except RateLimitError:
            wait = (2 ** i) * 10  # 指数バックオフ
            time.sleep(wait)
    raise Exception("Max retries exceeded")

# Metrics Server のインストール
kubectl apply -f https://github.com/kubernetes-sigs/metrics-server/releases/latest/download/components.yaml

或いはkube-state-metrics + custom metricsで扩展
kubectl get apiservices | grep metrics

# 解决方案1: WAL モード有效化
cursor.execute('PRAGMA journal_mode=WAL')
cursor.execute('PRAGMA busy_timeout=5000')

解决方案2: Redis 等外部ロックサーバーを使用
或いは Kubernetes の leader lock を使用

監視とログ管理

# Prometheus + Grafana による監視設定
apiVersion: v1
kind: ConfigMap
metadata:
  name: tardis-monitoring
  namespace: data-platform
data:
  prometheus.yml: |
    global:
      scrape_interval: 15s
    scrape_configs:
    - job_name: 'tardis'
      kubernetes_sd_configs:
      - role: pod
      relabel_configs:
      - source_labels: [__meta_kubernetes_pod_label_app]
        action: keep
        regex: tardis

---
Fluentd によるログ収集
apiVersion: v1
kind: ConfigMap
metadata:
  name: fluentd-config
  namespace: data-platform
data:
  fluent.conf: |
    <source>
      @type tail
      path /var/log/containers/tardis*.log
      pos_file /var/log/tardis.log.pos
      tag tardis.*
      <parse>
        @type json
      </parse>
    </source>
    <match tardis.**>
      @type elasticsearch
      host elasticsearch.logging
      port 9200
      logstash_format true
    </match>

まとめと次のステップ

• 自動化された增量更新：変更があったレコードのみを効率的に処理
• コスト最適化：HolySheep API の ¥1=$1 レートで85%コスト削減
• スケーラビリティ：HPA による自動スケーリングでトラフィック 대응
• 信頼性：CronJob による定时実行とエラーハンドリング
• 简单的な統合：OpenAI-Compatible API で既有システムと顺畅連携

導入提案