awoooi/docs/MONITORING_INTEGRATION_ARCHITECTURE.md

AWOOOI 監控自動整合架構

版本: v1.0 建立日期: 2026-03-29 目標: 新服務/功能自動獲得監控，零遺漏

---

核心原則

┌─────────────────────────────────────────────────────────────────┐
│  🎯 監控即代碼 (Monitoring as Code)                              │
│                                                                  │
│  • 所有監控配置存放於 Git                                         │
│  • CI/CD 自動驗證監控覆蓋率                                       │
│  • 新服務必須通過監控檢查才能部署                                  │
│  • 服務註冊表自動同步監控規則                                      │
└─────────────────────────────────────────────────────────────────┘

---

一、服務註冊表 (Service Registry)

1.1 註冊表結構

# /ops/monitoring/service-registry.yaml
# 所有受監控服務的單一事實來源 (Single Source of Truth)

services:
  # === K8s 工作負載 ===
  - name: awoooi-api
    type: k8s-deployment
    namespace: awoooi-prod
    port: 8000
    health_endpoint: /api/v1/health
    monitoring:
      prometheus: true
      sentry: true
      otel: true
      langfuse: true  # 有 LLM 呼叫
    alerts:
      - pod_crash
      - high_error_rate
      - slow_response
    owner: backend-team

  - name: awoooi-web
    type: k8s-deployment
    namespace: awoooi-prod
    port: 3000
    health_endpoint: /
    monitoring:
      prometheus: true
      sentry: true
      otel: true
      langfuse: false
    alerts:
      - pod_crash
      - slow_page_load
    owner: frontend-team

  - name: awoooi-worker
    type: k8s-deployment
    namespace: awoooi-prod
    health_endpoint: /tmp/worker-healthy  # exec probe
    monitoring:
      prometheus: true
      sentry: true
      otel: true
      langfuse: true
    alerts:
      - worker_stuck
      - queue_backlog
    owner: backend-team

  # === Docker 容器 (188) ===
  - name: ollama
    type: docker
    host: 192.168.0.188
    port: 11434
    health_endpoint: /api/tags
    monitoring:
      prometheus: true
      sentry: false  # 外部服務
      otel: false
    alerts:
      - service_down
      - inference_timeout
    owner: ai-team

  - name: openclaw
    type: docker
    host: 192.168.0.188
    port: 8089
    health_endpoint: /health
    monitoring:
      prometheus: true
      sentry: true
      otel: true
      langfuse: true
    alerts:
      - service_down
      - analysis_timeout
    owner: ai-team

  - name: redis
    type: docker
    host: 192.168.0.188
    port: 6380
    health_endpoint: redis-cli ping
    monitoring:
      prometheus: true
    alerts:
      - service_down
      - memory_high
    owner: infra-team

  - name: postgres
    type: docker
    host: 192.168.0.188
    port: 5432
    health_endpoint: pg_isready
    monitoring:
      prometheus: true
    alerts:
      - service_down
      - connection_pool_exhausted
      - slow_query
    owner: infra-team

  # === Docker 容器 (110) ===
  - name: harbor
    type: docker
    host: 192.168.0.110
    port: 5000
    health_endpoint: /api/v2.0/health
    monitoring:
      prometheus: true
    alerts:
      - service_down
      - storage_full
    owner: devops-team

  - name: sentry
    type: docker
    host: 192.168.0.110
    port: 9000
    health_endpoint: /_health/
    monitoring:
      prometheus: true
    alerts:
      - service_down
    owner: devops-team

  - name: langfuse
    type: docker
    host: 192.168.0.110
    port: 3100
    health_endpoint: /api/public/health
    monitoring:
      prometheus: true
    alerts:
      - service_down
    owner: ai-team

  - name: github-runner
    type: systemd
    host: 192.168.0.110
    service_name: actions.runner.owenhytsai-awoooi.awoooi-110.service
    monitoring:
      prometheus: true
    alerts:
      - runner_offline
    owner: devops-team

# === 前端頁面 ===
pages:
  - path: /
    name: Dashboard
    monitoring:
      sentry_session: true
      web_vitals: true
    alerts:
      - slow_page_load
      - js_error

  - path: /authorizations
    name: 授權管理
    monitoring:
      sentry_session: true
      web_vitals: true
    alerts:
      - slow_page_load
      - api_error

  - path: /action-logs
    name: 行動日誌
    monitoring:
      sentry_session: true
    alerts:
      - slow_page_load

  - path: /errors
    name: 錯誤追蹤
    monitoring:
      sentry_session: true
    alerts:
      - slow_page_load

# === API 端點 ===
api_endpoints:
  - path: /api/v1/health
    method: GET
    critical: true
    slo_latency_ms: 100
    slo_availability: 99.99

  - path: /api/v1/approvals
    method: GET
    critical: true
    slo_latency_ms: 500
    slo_availability: 99.9

  - path: /api/v1/analyze
    method: POST
    critical: true
    slo_latency_ms: 30000  # 30s (LLM)
    slo_availability: 95

  - path: /api/v1/webhooks/alertmanager
    method: POST
    critical: true
    slo_latency_ms: 5000
    slo_availability: 99.9

1.2 自動生成工具

# /ops/monitoring/generate_monitoring.py
"""
從 service-registry.yaml 自動生成:
1. Prometheus scrape configs
2. Alertmanager alert rules
3. Grafana dashboards
4. Blackbox exporter targets
"""

import yaml
from pathlib import Path

def generate_prometheus_config(registry: dict) -> str:
    """生成 Prometheus scrape_configs"""
    scrape_configs = []

    for service in registry['services']:
        if service['monitoring'].get('prometheus'):
            config = {
                'job_name': service['name'],
                'static_configs': [{
                    'targets': [f"{service['host']}:{service['port']}"]
                }],
                'metrics_path': '/metrics',
                'scrape_interval': '15s',
            }

            # 根據類型調整
            if service['type'] == 'k8s-deployment':
                config['kubernetes_sd_configs'] = [{
                    'role': 'pod',
                    'namespaces': {'names': [service['namespace']]}
                }]
                del config['static_configs']

            scrape_configs.append(config)

    return yaml.dump({'scrape_configs': scrape_configs})


def generate_alert_rules(registry: dict) -> str:
    """生成 Prometheus alert rules"""
    groups = []

    for service in registry['services']:
        rules = []

        for alert in service.get('alerts', []):
            rule = ALERT_TEMPLATES.get(alert, {}).copy()
            rule['labels'] = {
                'service': service['name'],
                'owner': service['owner'],
                'severity': 'critical' if alert in CRITICAL_ALERTS else 'warning',
            }
            rules.append(rule)

        if rules:
            groups.append({
                'name': f"{service['name']}_alerts",
                'rules': rules,
            })

    return yaml.dump({'groups': groups})


def generate_blackbox_targets(registry: dict) -> list:
    """生成 Blackbox Exporter 健康檢查目標"""
    targets = []

    for service in registry['services']:
        if service.get('health_endpoint'):
            if service['type'] in ['docker', 'k8s-deployment']:
                url = f"http://{service['host']}:{service['port']}{service['health_endpoint']}"
                targets.append({
                    'targets': [url],
                    'labels': {
                        'service': service['name'],
                        'type': service['type'],
                    }
                })

    return targets


# 告警模板
ALERT_TEMPLATES = {
    'pod_crash': {
        'alert': 'PodCrashLoopBackOff',
        'expr': 'kube_pod_container_status_waiting_reason{reason="CrashLoopBackOff"} > 0',
        'for': '2m',
        'annotations': {
            'summary': 'Pod {{ $labels.pod }} is crash looping',
            'auto_repair': 'restart_pod',
        }
    },
    'high_error_rate': {
        'alert': 'HighErrorRate',
        'expr': 'rate(http_requests_total{status=~"5.."}[5m]) / rate(http_requests_total[5m]) > 0.01',
        'for': '5m',
        'annotations': {
            'summary': 'High error rate on {{ $labels.service }}',
            'auto_repair': 'restart_pod',
        }
    },
    'service_down': {
        'alert': 'ServiceDown',
        'expr': 'probe_success == 0',
        'for': '1m',
        'annotations': {
            'summary': '{{ $labels.service }} is down',
            'auto_repair': 'restart_container',
        }
    },
    'slow_response': {
        'alert': 'SlowResponse',
        'expr': 'histogram_quantile(0.95, http_request_duration_seconds_bucket) > 2',
        'for': '5m',
        'annotations': {
            'summary': 'Slow response on {{ $labels.service }}',
            'auto_repair': 'scale_up',
        }
    },
    'memory_high': {
        'alert': 'MemoryHigh',
        'expr': 'container_memory_usage_bytes / container_spec_memory_limit_bytes > 0.9',
        'for': '5m',
        'annotations': {
            'summary': 'High memory usage on {{ $labels.service }}',
            'auto_repair': 'analyze_memory_leak',
        }
    },
    'runner_offline': {
        'alert': 'GitHubRunnerOffline',
        'expr': 'github_runner_status == 0',
        'for': '5m',
        'annotations': {
            'summary': 'GitHub Runner is offline',
            'auto_repair': 'restart_runner_service',
        }
    },
}

CRITICAL_ALERTS = {'pod_crash', 'service_down', 'runner_offline'}

---

二、CI/CD 整合 (自動監控)

2.1 新服務自動監控流程

# .github/workflows/cd.yaml 新增步驟

jobs:
  monitoring-validation:
    name: "🔍 Monitoring Coverage Check"
    runs-on: self-hosted
    steps:
      - name: Checkout
        uses: actions/checkout@v4

      - name: Validate Service Registry
        run: |
          # 檢查所有 K8s Deployment 是否都在 registry 中
          python ops/monitoring/validate_coverage.py

      - name: Generate Monitoring Configs
        run: |
          # 從 registry 生成最新監控配置
          python ops/monitoring/generate_monitoring.py

      - name: Check for Drift
        run: |
          # 檢查生成的配置與現有配置是否一致
          diff -r ops/monitoring/generated/ ops/monitoring/active/

      - name: Apply Monitoring Configs
        if: github.ref == 'refs/heads/main'
        run: |
          # 部署監控配置
          kubectl apply -f ops/monitoring/generated/prometheus-rules.yaml
          kubectl apply -f ops/monitoring/generated/alertmanager-config.yaml

2.2 新服務檢測腳本

# /ops/monitoring/validate_coverage.py
"""
CI 檢查: 確保所有服務都有監控配置
"""

import yaml
import subprocess
import sys

def get_k8s_deployments() -> list[str]:
    """取得所有 K8s Deployments"""
    result = subprocess.run(
        ['kubectl', 'get', 'deployments', '-A', '-o', 'jsonpath={.items[*].metadata.name}'],
        capture_output=True, text=True
    )
    return result.stdout.split()

def get_docker_containers(host: str) -> list[str]:
    """取得主機上的 Docker 容器"""
    result = subprocess.run(
        ['ssh', host, 'docker', 'ps', '--format', '{{.Names}}'],
        capture_output=True, text=True
    )
    return result.stdout.strip().split('\n')

def load_registry() -> dict:
    """載入服務註冊表"""
    with open('ops/monitoring/service-registry.yaml') as f:
        return yaml.safe_load(f)

def main():
    registry = load_registry()
    registered_services = {s['name'] for s in registry['services']}

    errors = []

    # 檢查 K8s Deployments
    k8s_deployments = get_k8s_deployments()
    for deploy in k8s_deployments:
        if deploy not in registered_services and not deploy.startswith('kube-'):
            errors.append(f"❌ K8s Deployment '{deploy}' 未在 service-registry.yaml 中註冊")

    # 檢查 Docker 容器 (188, 110)
    for host in ['192.168.0.188', '192.168.0.110']:
        try:
            containers = get_docker_containers(host)
            for container in containers:
                if container and container not in registered_services:
                    # 忽略系統容器
                    if not any(x in container for x in ['k3s', 'pause', 'coredns']):
                        errors.append(f"⚠️ Docker 容器 '{container}' on {host} 未在 registry 中")
        except Exception as e:
            print(f"Warning: Cannot check {host}: {e}")

    if errors:
        print("\n".join(errors))
        print(f"\n❌ 發現 {len(errors)} 個未監控的服務！")
        print("請更新 ops/monitoring/service-registry.yaml")
        sys.exit(1)

    print("✅ 所有服務都已註冊監控")
    sys.exit(0)

if __name__ == '__main__':
    main()

2.3 新 API 端點自動監控

# /apps/api/src/core/auto_monitoring.py
"""
FastAPI 路由自動監控
- 自動註冊所有端點到 Prometheus
- 自動設置 Sentry 追蹤
- 自動建立健康檢查
"""

from functools import wraps
from fastapi import APIRouter, Request
from prometheus_client import Counter, Histogram
import time

# Prometheus Metrics (自動建立)
REQUEST_COUNT = Counter(
    'http_requests_total',
    'Total HTTP requests',
    ['method', 'path', 'status']
)

REQUEST_LATENCY = Histogram(
    'http_request_duration_seconds',
    'HTTP request latency',
    ['method', 'path'],
    buckets=[0.01, 0.05, 0.1, 0.25, 0.5, 1.0, 2.5, 5.0, 10.0]
)

def auto_monitor(router: APIRouter):
    """
    裝飾器: 為 Router 的所有端點添加監控

    使用方式:
    ```python
    router = APIRouter(prefix="/api/v1/new-feature")
    auto_monitor(router)  # 自動添加監控
    ```
    """
    original_add_api_route = router.add_api_route

    def monitored_add_api_route(path, endpoint, **kwargs):
        @wraps(endpoint)
        async def monitored_endpoint(request: Request, *args, **inner_kwargs):
            start_time = time.time()

            try:
                response = await endpoint(request, *args, **inner_kwargs)
                status = getattr(response, 'status_code', 200)
            except Exception as e:
                status = 500
                raise
            finally:
                # 記錄指標
                REQUEST_COUNT.labels(
                    method=request.method,
                    path=path,
                    status=status
                ).inc()

                REQUEST_LATENCY.labels(
                    method=request.method,
                    path=path
                ).observe(time.time() - start_time)

            return response

        return original_add_api_route(path, monitored_endpoint, **kwargs)

    router.add_api_route = monitored_add_api_route
    return router

---

三、前端自動監控

3.1 頁面自動埋點

// /apps/web/src/lib/auto-monitoring.ts
/**
 * 前端頁面自動監控
 * - Web Vitals 自動收集
 * - 頁面錯誤自動上報
 * - API 呼叫自動追蹤
 */

import * as Sentry from '@sentry/nextjs';

// 自動初始化 (在 _app.tsx 中調用)
export function initAutoMonitoring() {
  // 1. Web Vitals
  if (typeof window !== 'undefined') {
    import('web-vitals').then(({ onCLS, onFID, onLCP, onTTFB, onINP }) => {
      onCLS(sendToAnalytics);
      onFID(sendToAnalytics);
      onLCP(sendToAnalytics);
      onTTFB(sendToAnalytics);
      onINP(sendToAnalytics);
    });
  }

  // 2. 全局錯誤處理
  if (typeof window !== 'undefined') {
    window.addEventListener('error', (event) => {
      Sentry.captureException(event.error);
    });

    window.addEventListener('unhandledrejection', (event) => {
      Sentry.captureException(event.reason);
    });
  }

  // 3. API 呼叫自動追蹤
  patchFetch();
}

function sendToAnalytics(metric: any) {
  // 發送到 Sentry Performance
  Sentry.metrics.distribution(
    `web_vitals.${metric.name}`,
    metric.value,
    {
      tags: {
        page: window.location.pathname,
      },
    }
  );
}

function patchFetch() {
  const originalFetch = window.fetch;

  window.fetch = async function(input, init) {
    const url = typeof input === 'string' ? input : input.url;
    const method = init?.method || 'GET';

    const span = Sentry.startSpan({
      name: `${method} ${url}`,
      op: 'http.client',
    });

    try {
      const response = await originalFetch(input, init);

      // 記錄 API 錯誤
      if (!response.ok) {
        Sentry.captureMessage(`API Error: ${method} ${url} - ${response.status}`, {
          level: response.status >= 500 ? 'error' : 'warning',
          extra: {
            status: response.status,
            statusText: response.statusText,
          },
        });
      }

      return response;
    } catch (error) {
      Sentry.captureException(error);
      throw error;
    } finally {
      span?.end();
    }
  };
}

3.2 新頁面自動檢測

// /apps/web/src/middleware.ts
import { NextResponse } from 'next/server';
import type { NextRequest } from 'next/server';

// 已知頁面清單 (從 service-registry 同步)
const KNOWN_PAGES = new Set([
  '/',
  '/authorizations',
  '/action-logs',
  '/errors',
  '/settings',
  '/knowledge-base',
]);

export function middleware(request: NextRequest) {
  const path = request.nextUrl.pathname;

  // 檢測新頁面
  if (!KNOWN_PAGES.has(path) && !path.startsWith('/api') && !path.startsWith('/_next')) {
    // 發送到監控系統
    console.warn(`[MONITORING] 新頁面被訪問但未註冊: ${path}`);

    // TODO: 發送到 Sentry 或後端 API
  }

  return NextResponse.next();
}

---

四、自動發現機制

4.1 K8s 服務自動發現

# /ops/monitoring/prometheus/kubernetes-sd.yaml
# Prometheus 自動發現 K8s 服務

scrape_configs:
  # 自動發現所有 Pod
  - job_name: 'kubernetes-pods'
    kubernetes_sd_configs:
      - role: pod
    relabel_configs:
      # 只抓有 prometheus.io/scrape: "true" 標籤的 Pod
      - source_labels: [__meta_kubernetes_pod_annotation_prometheus_io_scrape]
        action: keep
        regex: true
      # 使用 Pod 標籤作為 job name
      - source_labels: [__meta_kubernetes_pod_label_app]
        target_label: job
      # 使用 namespace 標籤
      - source_labels: [__meta_kubernetes_namespace]
        target_label: namespace

4.2 Docker 容器自動發現

# /ops/monitoring/discover_docker.py
"""
定期掃描 Docker 容器，發現未監控的新服務
"""

import subprocess
import json
from datetime import datetime

HOSTS = ['192.168.0.188', '192.168.0.110']

def discover_containers():
    """發現所有 Docker 容器"""
    all_containers = []

    for host in HOSTS:
        try:
            result = subprocess.run(
                ['ssh', host, 'docker', 'ps', '--format', '{{json .}}'],
                capture_output=True, text=True, timeout=10
            )

            for line in result.stdout.strip().split('\n'):
                if line:
                    container = json.loads(line)
                    container['host'] = host
                    all_containers.append(container)
        except Exception as e:
            print(f"Error scanning {host}: {e}")

    return all_containers

def check_new_containers(containers: list, registry: dict):
    """檢查是否有新容器未在 registry 中"""
    registered = {s['name'] for s in registry['services']}

    new_containers = []
    for c in containers:
        name = c['Names']
        if name not in registered:
            new_containers.append({
                'name': name,
                'host': c['host'],
                'image': c['Image'],
                'created': c['CreatedAt'],
            })

    return new_containers

def alert_new_containers(new_containers: list):
    """發送新容器告警"""
    if new_containers:
        message = f"""🆕 發現 {len(new_containers)} 個未監控的容器:

"""
        for c in new_containers:
            message += f"• {c['name']} on {c['host']} ({c['image']})\n"

        message += "\n請更新 service-registry.yaml"

        # TODO: 發送 Telegram 告警
        print(message)

if __name__ == '__main__':
    # 作為 cron job 每小時執行
    import yaml

    with open('ops/monitoring/service-registry.yaml') as f:
        registry = yaml.safe_load(f)

    containers = discover_containers()
    new_containers = check_new_containers(containers, registry)

    if new_containers:
        alert_new_containers(new_containers)

---

五、監控覆蓋率儀表板

5.1 覆蓋率計算

# /ops/monitoring/coverage_report.py
"""
計算監控覆蓋率並生成報告
"""

def calculate_coverage(registry: dict) -> dict:
    """計算各維度的監控覆蓋率"""
    services = registry['services']

    total = len(services)

    coverage = {
        'prometheus': sum(1 for s in services if s['monitoring'].get('prometheus')) / total,
        'sentry': sum(1 for s in services if s['monitoring'].get('sentry')) / total,
        'otel': sum(1 for s in services if s['monitoring'].get('otel')) / total,
        'langfuse': sum(1 for s in services if s['monitoring'].get('langfuse')) / total,
        'alerts': sum(1 for s in services if s.get('alerts')) / total,
    }

    # 頁面覆蓋率
    pages = registry.get('pages', [])
    if pages:
        coverage['page_sentry'] = sum(1 for p in pages if p['monitoring'].get('sentry_session')) / len(pages)
        coverage['page_vitals'] = sum(1 for p in pages if p['monitoring'].get('web_vitals')) / len(pages)

    # API SLO 覆蓋率
    endpoints = registry.get('api_endpoints', [])
    if endpoints:
        coverage['api_slo'] = sum(1 for e in endpoints if e.get('slo_latency_ms')) / len(endpoints)

    return coverage

def generate_report(coverage: dict) -> str:
    """生成覆蓋率報告"""
    report = """
# AWOOOI 監控覆蓋率報告
生成時間: {timestamp}

## 服務監控覆蓋率

| 監控類型 | 覆蓋率 | 狀態 |
|----------|--------|------|
| Prometheus Metrics | {prometheus:.0%} | {prometheus_status} |
| Sentry 錯誤追蹤 | {sentry:.0%} | {sentry_status} |
| OTEL Traces | {otel:.0%} | {otel_status} |
| Langfuse LLM | {langfuse:.0%} | {langfuse_status} |
| Alert Rules | {alerts:.0%} | {alerts_status} |

## 前端監控覆蓋率

| 監控類型 | 覆蓋率 | 狀態 |
|----------|--------|------|
| Sentry Session | {page_sentry:.0%} | {page_sentry_status} |
| Web Vitals | {page_vitals:.0%} | {page_vitals_status} |

## API SLO 覆蓋率

| 類型 | 覆蓋率 | 狀態 |
|------|--------|------|
| SLO 定義 | {api_slo:.0%} | {api_slo_status} |

---
總體健康度: **{overall:.0%}**
""".format(
        timestamp=datetime.now().isoformat(),
        **coverage,
        **{f"{k}_status": "✅" if v >= 0.9 else "⚠️" if v >= 0.7 else "❌" for k, v in coverage.items()},
        overall=sum(coverage.values()) / len(coverage),
    )

    return report

---

六、整合流程圖

┌─────────────────────────────────────────────────────────────────────┐
│                         開發者新增服務                               │
│  (新 K8s Deployment / Docker 容器 / API 端點 / 前端頁面)             │
└────────────────────────────┬────────────────────────────────────────┘
                             │
                             ▼
┌─────────────────────────────────────────────────────────────────────┐
│  Step 1: 更新 service-registry.yaml                                 │
│  ┌───────────────────────────────────────────────────────────────┐  │
│  │ services:                                                      │  │
│  │   - name: new-service                                          │  │
│  │     type: k8s-deployment                                       │  │
│  │     monitoring:                                                │  │
│  │       prometheus: true                                         │  │
│  │       sentry: true                                             │  │
│  │     alerts:                                                    │  │
│  │       - pod_crash                                              │  │
│  │       - high_error_rate                                        │  │
│  └───────────────────────────────────────────────────────────────┘  │
└────────────────────────────┬────────────────────────────────────────┘
                             │
                             ▼
┌─────────────────────────────────────────────────────────────────────┐
│  Step 2: git push → CI/CD Pipeline                                  │
│  ┌───────────────────────────────────────────────────────────────┐  │
│  │ 1. validate_coverage.py → 檢查所有服務都在 registry            │  │
│  │ 2. generate_monitoring.py → 生成 Prometheus/Alertmanager 配置 │  │
│  │ 3. kubectl apply → 部署監控配置                                │  │
│  │ 4. 部署新服務                                                  │  │
│  └───────────────────────────────────────────────────────────────┘  │
└────────────────────────────┬────────────────────────────────────────┘
                             │
                             ▼
┌─────────────────────────────────────────────────────────────────────┐
│  Step 3: 監控自動生效                                                │
│  ┌─────────────┐  ┌─────────────┐  ┌─────────────┐  ┌────────────┐ │
│  │ Prometheus  │  │ Alertmanager│  │  Sentry     │  │  SignOz    │ │
│  │ 開始抓 Metrics│ │ 開始監控告警 │  │ 開始追蹤錯誤│  │ 開始收 Traces│ │
│  └─────────────┘  └─────────────┘  └─────────────┘  └────────────┘ │
└────────────────────────────┬────────────────────────────────────────┘
                             │
                             ▼
┌─────────────────────────────────────────────────────────────────────┐
│  Step 4: 異常發生 → AI 自動修復                                      │
│  ┌───────────────────────────────────────────────────────────────┐  │
│  │ 1. Prometheus 觸發告警                                         │  │
│  │ 2. Alertmanager → AWOOOI Webhook                              │  │
│  │ 3. OpenClaw AI 分析                                            │  │
│  │ 4. 自動/人工修復                                                │  │
│  │ 5. 結果回饋 → Playbook 更新                                     │  │
│  └───────────────────────────────────────────────────────────────┘  │
└─────────────────────────────────────────────────────────────────────┘

---

七、實作清單

7.1 需要建立的檔案

檔案	用途	優先級
ops/monitoring/service-registry.yaml	服務註冊表	P0
ops/monitoring/generate_monitoring.py	配置生成器	P0
ops/monitoring/validate_coverage.py	覆蓋率檢查	P0
ops/monitoring/discover_docker.py	容器發現	P1
apps/api/src/core/auto_monitoring.py	API 自動監控	P1
apps/web/src/lib/auto-monitoring.ts	前端自動監控	P1

7.2 CI/CD 修改

修改	用途	優先級
新增 monitoring-validation job	檢查覆蓋率	P0
新增 monitoring-deploy job	部署配置	P0

7.3 Cron Jobs

任務	頻率	用途
discover_docker.py	每小時	發現新容器
coverage_report.py	每日	生成報告

---

文件結束