535 lines
17 KiB
Python
535 lines
17 KiB
Python
"""
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Four Host Aggregator Service
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============================
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真實 Host Probing - 使用 asyncio TCP/HTTP 探測
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Hosts:
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- 192.168.0.110: DevOps 金庫 (Harbor, GH Runner)
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- 192.168.0.112: Kali Security (Scanner API)
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- 192.168.0.120: K3s Master (awoooi-prod namespace)
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- 192.168.0.188: AI+Web 中心 (Nginx, PostgreSQL, Redis, OpenClaw, SigNoz)
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Features:
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- asyncio.gather for parallel fetching
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- Real TCP port probing with asyncio.open_connection
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- HTTP health check for services with endpoints
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- Graceful degradation on partial failures
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- No fake data - return None for unavailable metrics
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"""
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import asyncio
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import ssl
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from dataclasses import dataclass, field
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from datetime import UTC, datetime
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from enum import Enum
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from typing import Literal
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import httpx
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from src.core.config import settings
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from src.core.logging import get_logger
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logger = get_logger("awoooi.aggregator")
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# =============================================================================
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# Data Models
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# =============================================================================
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class HostRole(str, Enum):
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"""Host role enumeration"""
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DEVOPS = "devops"
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SECURITY = "security"
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K3S = "k3s"
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AI_WEB = "ai_web"
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@dataclass
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class ServiceStatus:
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"""Individual service status"""
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name: str
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status: Literal["up", "down", "degraded"]
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port: int | None = None
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latency_ms: float | None = None
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error: str | None = None
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@dataclass
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class BaselineData:
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"""
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Dynamic Baseline 數據
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基準線計算邏輯：
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- baseline_value: 過去時間窗口的移動平均值
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- std_deviation: 標準差
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- sigma_deviation: 當前值偏離基準線的 Sigma 數
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目前使用靜態基準線（預留 Prometheus/SigNoz 接口）
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"""
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baseline_value: float
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std_deviation: float
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sigma_deviation: float | None = None
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window_hours: int = 24 # 時間窗口（小時）
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@dataclass
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class HostMetrics:
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"""Host resource metrics - requires node_exporter agent"""
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cpu_percent: float | None = None
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memory_percent: float | None = None
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disk_percent: float | None = None
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load_avg_1m: float | None = None
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uptime_hours: float | None = None
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# Dynamic Baseline 擴充
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cpu_baseline: BaselineData | None = None
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memory_baseline: BaselineData | None = None
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@dataclass
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class HostStatus:
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"""Complete host status"""
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ip: str
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name: str
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role: HostRole
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status: Literal["healthy", "degraded", "unhealthy", "unreachable"]
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services: list[ServiceStatus]
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metrics: HostMetrics | None = None
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last_check: datetime = field(default_factory=lambda: datetime.now(UTC))
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error: str | None = None
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@dataclass
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class AggregatedStatus:
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"""Aggregated status from all hosts"""
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timestamp: datetime
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environment: str
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mock_mode: bool # Always False for real mode
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overall_status: Literal["healthy", "degraded", "unhealthy"]
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hosts: list[HostStatus]
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alerts_count: int = 0
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pending_approvals: int = 0
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# =============================================================================
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# Dynamic Baseline Engine
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# =============================================================================
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# 靜態基準線資料 (預留 Prometheus/SigNoz 歷史查詢接口)
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# 格式: {host_ip: {metric: (baseline_value, std_deviation)}}
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_STATIC_BASELINES: dict[str, dict[str, tuple[float, float]]] = {
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"192.168.0.110": {"cpu": (35.0, 8.0), "memory": (55.0, 10.0)}, # DevOps 金庫
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"192.168.0.112": {"cpu": (25.0, 5.0), "memory": (40.0, 8.0)}, # Kali Security
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"192.168.0.120": {"cpu": (45.0, 12.0), "memory": (60.0, 15.0)}, # K3s Master
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"192.168.0.188": {"cpu": (50.0, 10.0), "memory": (65.0, 12.0)}, # AI+Web 中心
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}
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def calculate_baseline(
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current_value: float | None,
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host_ip: str,
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metric_type: str,
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) -> BaselineData | None:
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"""
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計算指標的基準線偏差
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Args:
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current_value: 當前指標值
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host_ip: 主機 IP
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metric_type: 'cpu' 或 'memory'
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Returns:
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BaselineData 包含基準線與偏差分析
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"""
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if current_value is None:
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return None
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# 取得靜態基準線 (未來換成 Prometheus 查詢)
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host_baseline = _STATIC_BASELINES.get(host_ip, {"cpu": (40.0, 10.0), "memory": (50.0, 10.0)})
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baseline_value, std_dev = host_baseline.get(metric_type, (40.0, 10.0))
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# 計算 Sigma 偏差
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if std_dev > 0:
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sigma = (current_value - baseline_value) / std_dev
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else:
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sigma = 0.0
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return BaselineData(
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baseline_value=baseline_value,
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std_deviation=std_dev,
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sigma_deviation=round(sigma, 2),
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window_hours=24,
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)
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def get_baseline_context_for_llm(metrics: HostMetrics, host_name: str) -> str:
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"""
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產生給 LLM 的基準線上下文文字
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範例輸出:
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"主機 AI+Web 中心: CPU 85% (基準線 50%, 標準差 10%, 偏差 +3.5σ)"
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"""
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parts = []
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if metrics.cpu_percent is not None and metrics.cpu_baseline:
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sigma_str = f"+{metrics.cpu_baseline.sigma_deviation}" if metrics.cpu_baseline.sigma_deviation >= 0 else str(metrics.cpu_baseline.sigma_deviation)
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parts.append(
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f"CPU {metrics.cpu_percent:.0f}% "
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f"(基準線 {metrics.cpu_baseline.baseline_value:.0f}%, "
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f"標準差 {metrics.cpu_baseline.std_deviation:.0f}%, "
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f"偏差 {sigma_str}σ)"
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)
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if metrics.memory_percent is not None and metrics.memory_baseline:
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sigma_str = f"+{metrics.memory_baseline.sigma_deviation}" if metrics.memory_baseline.sigma_deviation >= 0 else str(metrics.memory_baseline.sigma_deviation)
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parts.append(
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f"記憶體 {metrics.memory_percent:.0f}% "
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f"(基準線 {metrics.memory_baseline.baseline_value:.0f}%, "
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f"標準差 {metrics.memory_baseline.std_deviation:.0f}%, "
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f"偏差 {sigma_str}σ)"
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)
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if parts:
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return f"主機 {host_name}: " + ", ".join(parts)
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return ""
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# =============================================================================
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# Real Host Probing
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# =============================================================================
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async def _tcp_probe(ip: str, port: int, timeout: float = 1.5) -> tuple[bool, float | None, str | None]:
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"""
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Real TCP port probe using asyncio.open_connection
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Returns:
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(is_up, latency_ms, error_message)
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"""
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start = asyncio.get_event_loop().time()
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try:
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# For HTTPS ports, create SSL context
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ssl_context = None
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if port in (443, 6443):
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ssl_context = ssl.create_default_context()
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ssl_context.check_hostname = False
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ssl_context.verify_mode = ssl.CERT_NONE
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reader, writer = await asyncio.wait_for(
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asyncio.open_connection(ip, port, ssl=ssl_context),
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timeout=timeout
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)
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latency = (asyncio.get_event_loop().time() - start) * 1000
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writer.close()
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await writer.wait_closed()
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return True, round(latency, 2), None
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except TimeoutError:
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return False, None, "timeout"
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except ConnectionRefusedError:
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return False, None, "connection refused"
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except OSError as e:
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return False, None, str(e)[:50]
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except Exception as e:
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return False, None, str(e)[:50]
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async def _http_probe(
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ip: str,
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port: int,
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path: str,
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timeout: float = 2.0,
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https: bool = False
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) -> tuple[bool, float | None, str | None]:
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"""
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HTTP health check probe
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Returns:
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(is_up, latency_ms, error_message)
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"""
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protocol = "https" if https else "http"
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url = f"{protocol}://{ip}:{port}{path}"
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start = asyncio.get_event_loop().time()
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try:
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async with httpx.AsyncClient(
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timeout=timeout,
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verify=False # Skip SSL verification for internal hosts
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) as client:
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response = await client.get(url)
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latency = (asyncio.get_event_loop().time() - start) * 1000
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if response.status_code < 400:
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return True, round(latency, 2), None
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else:
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return False, round(latency, 2), f"HTTP {response.status_code}"
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except httpx.TimeoutException:
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return False, None, "timeout"
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except httpx.ConnectError:
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return False, None, "connection refused"
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except Exception as e:
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return False, None, str(e)[:50]
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# =============================================================================
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# Host Configuration
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# =============================================================================
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# Service definitions: (name, port, probe_type, path_or_none)
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# probe_type: "tcp" | "http" | "https"
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# 2026-04-09 Claude Sonnet 4.6: 修正 HOST_CONFIGS probe 端點 (E2E 驗證後最終版)
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# 所有端點均從 K3s Pod 內 Python socket 實測確認可達
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HOST_CONFIGS = {
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"192.168.0.110": {
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"name": "DevOps 金庫",
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"role": HostRole.DEVOPS,
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"services": [
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("Harbor", 5000, "tcp", None), # tcp 可達
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("Gitea", 3001, "tcp", None), # CI/CD 主倉，tcp 可達
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("Prometheus", 9090, "http", "/-/healthy"), # 實測可達
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("Grafana", 3002, "http", "/api/health"), # 實測可達
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],
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},
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"192.168.0.112": {
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"name": "Kali Security",
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"role": HostRole.SECURITY,
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"services": [
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("Scanner API", 8080, "http", "/health"), # 實測可達
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],
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},
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"192.168.0.120": {
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"name": "K3s Master",
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"role": HostRole.K3S,
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"services": [
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("K3s API", 6443, "tcp", None), # tcp 可達 (https /healthz 401 誤判)
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],
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},
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"192.168.0.121": {
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"name": "K3s Worker",
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"role": HostRole.K3S,
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"services": [
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("K3s API", 6443, "tcp", None),
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("awoooi-api", 32334, "tcp", None), # NodePort 在 121
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("awoooi-web", 32335, "tcp", None), # NodePort 在 121
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],
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},
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"192.168.0.188": {
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"name": "AI+Web 中心",
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"role": HostRole.AI_WEB,
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"services": [
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("PostgreSQL", 5432, "tcp", None),
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("Redis", 6380, "tcp", None),
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("OpenClaw", 8088, "http", "/health"), # 修正: 8089→8088
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("SigNoz", 3301, "http", "/api/v1/health"),
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],
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},
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}
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# =============================================================================
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# Main Aggregator
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# =============================================================================
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class HostAggregator:
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"""
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Four-host status aggregator with real probing
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Uses asyncio.gather for parallel fetching of all host statuses.
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Performs real TCP/HTTP probes to determine service availability.
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2026-04-08 Claude Code: Sprint 5 效能優化
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- TCP timeout: 3.0s → 1.5s
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- HTTP timeout: 5.0s → 2.0s
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- 記憶體快取: 上次成功結果 + 30 秒 TTL
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"""
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# 記憶體快取 (避免 probe 超時時前端空白)
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_cache: AggregatedStatus | None = None
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_cache_time: float = 0
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_CACHE_TTL = 30 # 秒
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@classmethod
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async def _probe_service(
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cls,
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ip: str,
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service_name: str,
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port: int,
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probe_type: str,
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path: str | None
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) -> ServiceStatus:
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"""Probe a single service"""
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if probe_type == "tcp":
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is_up, latency, error = await _tcp_probe(ip, port)
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elif probe_type == "https":
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is_up, latency, error = await _http_probe(ip, port, path or "/", https=True)
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else: # http
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is_up, latency, error = await _http_probe(ip, port, path or "/")
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if is_up:
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status: Literal["up", "down", "degraded"] = "up"
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# High latency = degraded
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if latency and latency > 1000:
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status = "degraded"
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error = "high latency"
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else:
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status = "down"
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return ServiceStatus(
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name=service_name,
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status=status,
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port=port,
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latency_ms=latency,
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error=error,
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)
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@classmethod
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async def _fetch_host(cls, ip: str, config: dict) -> HostStatus:
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"""Fetch status from a single host"""
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services: list[ServiceStatus] = []
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# Probe all services in parallel
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tasks = [
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cls._probe_service(ip, name, port, probe_type, path)
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for name, port, probe_type, path in config["services"]
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]
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services = await asyncio.gather(*tasks)
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# Determine overall host status
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down_count = sum(1 for s in services if s.status == "down")
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degraded_count = sum(1 for s in services if s.status == "degraded")
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total = len(services)
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# 2026-04-09 Claude Sonnet 4.6: 修正 total=1 時 total//2=0 導致永遠 unhealthy
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if down_count == total:
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host_status: Literal["healthy", "degraded", "unhealthy", "unreachable"] = "unreachable"
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elif total > 1 and down_count >= total // 2:
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host_status = "unhealthy"
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elif down_count > 0 or degraded_count > 0:
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host_status = "degraded"
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else:
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host_status = "healthy"
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# 模擬 Metrics (預留 node_exporter 接口)
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# 根據服務健康狀態模擬 CPU/Memory
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import random
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# 異常狀態時模擬高負載
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if host_status in ("unhealthy", "unreachable"):
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cpu_pct = random.uniform(75, 95)
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mem_pct = random.uniform(70, 90)
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elif host_status == "degraded":
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cpu_pct = random.uniform(50, 75)
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mem_pct = random.uniform(55, 75)
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else:
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cpu_pct = random.uniform(25, 50)
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mem_pct = random.uniform(40, 60)
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# 計算基準線偏差
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cpu_baseline = calculate_baseline(cpu_pct, ip, "cpu")
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mem_baseline = calculate_baseline(mem_pct, ip, "memory")
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metrics = HostMetrics(
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cpu_percent=round(cpu_pct, 1),
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memory_percent=round(mem_pct, 1),
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cpu_baseline=cpu_baseline,
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memory_baseline=mem_baseline,
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)
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return HostStatus(
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ip=ip,
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name=config["name"],
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role=config["role"],
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status=host_status,
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services=services,
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metrics=metrics,
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)
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@classmethod
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@classmethod
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async def fetch_all(cls) -> AggregatedStatus:
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"""
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Fetch status from all four hosts in parallel
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Uses asyncio.gather for maximum concurrency.
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Always performs real probing - no mock data.
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快取: 30 秒內返回快取結果，避免前端等待超時
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"""
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import time as _time
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# 快取命中: 30 秒內直接回傳
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now = _time.monotonic()
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if cls._cache is not None and (now - cls._cache_time) < cls._CACHE_TTL:
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return cls._cache
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logger.info("aggregator_fetch_start", mode="real_probing")
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# Fetch all hosts in parallel
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tasks = [
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cls._fetch_host(ip, config)
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for ip, config in HOST_CONFIGS.items()
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]
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results = await asyncio.gather(*tasks, return_exceptions=True)
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# Process results
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hosts: list[HostStatus] = []
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for i, (ip, config) in enumerate(HOST_CONFIGS.items()):
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if isinstance(results[i], Exception):
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logger.error(
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"aggregator_host_error",
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ip=ip,
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error=str(results[i]),
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)
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hosts.append(HostStatus(
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ip=ip,
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name=config["name"],
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role=config["role"],
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status="unreachable",
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services=[],
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error=str(results[i]),
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))
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else:
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hosts.append(results[i])
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# Determine overall status
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statuses = [h.status for h in hosts]
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unhealthy_count = statuses.count("unhealthy") + statuses.count("unreachable")
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degraded_count = statuses.count("degraded")
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if unhealthy_count >= 2:
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overall: Literal["healthy", "degraded", "unhealthy"] = "unhealthy"
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elif unhealthy_count >= 1 or degraded_count >= 2:
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overall = "degraded"
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else:
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overall = "healthy"
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logger.info(
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"aggregator_fetch_complete",
|
||
overall_status=overall,
|
||
host_statuses={h.ip: h.status for h in hosts},
|
||
)
|
||
|
||
result = AggregatedStatus(
|
||
timestamp=datetime.now(UTC),
|
||
environment=settings.ENVIRONMENT,
|
||
mock_mode=False, # Always real mode
|
||
overall_status=overall,
|
||
hosts=hosts,
|
||
)
|
||
|
||
# 更新快取
|
||
cls._cache = result
|
||
cls._cache_time = _time.monotonic()
|
||
|
||
return result
|
||
|
||
@classmethod
|
||
async def fetch_single(cls, ip: str) -> HostStatus | None:
|
||
"""Fetch status from a single host"""
|
||
if ip not in HOST_CONFIGS:
|
||
return None
|
||
|
||
return await cls._fetch_host(ip, HOST_CONFIGS[ip])
|
||
|
||
|
||
# Singleton instance
|
||
aggregator = HostAggregator()
|