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feat(ai-ops): ADR-013 AIOps 自動修復閉環完整實作
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架構（Exception → Incident → PlayBook → Heal → KM → Telegram）:

新增元件:
- database/autoheal_models.py: Incident/Playbook/HealLog 三張表 + 7 條種子 PlayBook
- migrations/013_autoheal.sql: 建表 DDL + 種子資料（冪等 INSERT）
- services/auto_heal_service.py: 核心引擎 7 步閉環
  - _classify_error: 8 類錯誤自動分類 (DNS_FAIL/DB_UNREACHABLE/OOM/...)
  - _match_playbook: error_type + keyword + 冷卻 + max_retries 保護
  - _execute_playbook: DOCKER_RESTART/SSH_CMD/ALERT_ONLY/WAIT_RETRY
  - _sink_to_km: 修復知識寫入 ai_insights (auto_heal_playbook)
  - SSH 白名單：僅允許 docker restart / compose restart / docker start

修改元件:
- database/manager.py: _init_autoheal_tables() 啟動時建表+種子 PlayBook
- scheduler.py: 3 個核心任務植入 handle_exception
  (run_auto_import_task / run_icaim_analysis_task / run_weekly_strategy_task)
- requirements.txt: paramiko（SSH 跳板；不可用時降級 subprocess+CLI ssh）

安全設計: CMD 白名單 + cooldown + max_retries escalation + DB 冪等 migration

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
This commit is contained in:
ogt
2026-04-19 16:03:49 +08:00
parent 7fbeaaf213
commit 77d3a1da48
8 changed files with 1050 additions and 3 deletions
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CLAUDE.md
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@@ -1,6 +1,6 @@
# EwoooC (MOMO Pro System) — 核心索引
> **版本**: V10.3 | **目標**: AI 驅動 MOMO 商品監控、業績分析與策略自動化
> **版本**: V10.4 | **目標**: AI 驅動 MOMO 商品監控、業績分析、策略自動化與 AIOps 自愈
## 治理
- **憲法**: [CONSTITUTION.md](CONSTITUTION.md) — 所有開發必須遵守
@@ -62,6 +62,7 @@ ssh wooo@192.168.0.110 "ssh ollama@192.168.0.188 \"\
| 憑證對照表 | [docs/memory/credentials_passbook.md](docs/memory/credentials_passbook.md) |
| AIOps 存檔 | [docs/external/aiops_saas.md](docs/external/aiops_saas.md) |
| 跨專案隔離（**必讀**）| [docs/adr/ADR-011-cross-project-resource-isolation.md](docs/adr/ADR-011-cross-project-resource-isolation.md) |
| **AIOps 自動修復（ADR-013）** | [docs/adr/ADR-013-aiops-autoheal.md](docs/adr/ADR-013-aiops-autoheal.md) |
## AI 開發鐵律（Token 優化）

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database/autoheal_models.py Normal file
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@@ -0,0 +1,250 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
AIOps 自動修復資料庫模型 (ADR-013)
三張表：incidents / playbooks / heal_logs
構成「感知 → 匹配 → 執行 → 記錄」的完整閉環資料層
"""
import json
from sqlalchemy import (
Column, Integer, String, Text, Boolean, DateTime, Float, ForeignKey, Index
)
from datetime import datetime
from .models import Base
class Incident(Base):
"""
事件主表 - 紀錄每一個系統異常事件。
status 生命週期：open → healing → resolved / escalated
"""
__tablename__ = "incidents"
id = Column(Integer, primary_key=True)
# 來源資訊
task_name = Column(String(100), nullable=False, index=True) # 如 run_auto_import_task
error_type = Column(String(50), nullable=False, index=True) # DB_UNREACHABLE / DNS_FAIL / OOM / etc.
error_message = Column(Text, nullable=False) # 原始 exception 訊息（簡短）
error_traceback = Column(Text) # 完整 traceback（可大）
# 嚴重度與狀態
severity = Column(String(5), default="P2") # P1 / P2 / P3
status = Column(String(20), default="open", index=True) # open / healing / resolved / escalated
# PlayBook 關聯
playbook_id = Column(Integer, ForeignKey("playbooks.id"), nullable=True)
# 計數
retry_count = Column(Integer, default=0)
# 時間
resolved_at = Column(DateTime, nullable=True)
created_at = Column(DateTime, default=datetime.now)
updated_at = Column(DateTime, default=datetime.now, onupdate=datetime.now)
__table_args__ = (
Index("idx_incident_status_created", "status", "created_at"),
Index("idx_incident_task_error", "task_name", "error_type"),
)
def to_dict(self) -> dict:
return {
"id": self.id,
"task_name": self.task_name,
"error_type": self.error_type,
"error_message": self.error_message,
"severity": self.severity,
"status": self.status,
"playbook_id": self.playbook_id,
"retry_count": self.retry_count,
"resolved_at": self.resolved_at.isoformat() if self.resolved_at else None,
"created_at": self.created_at.isoformat() if self.created_at else None,
}
class Playbook(Base):
"""
PlayBook 規則庫 - 每一列是一條「對應到修復動作」的規則。
match_pattern 是 JSON 陣列，ANY 命中即觸發。
action_params 是 JSON 物件，包含執行動作所需的參數。
"""
__tablename__ = "playbooks"
id = Column(Integer, primary_key=True)
# 識別與分類
name = Column(String(200), nullable=False, unique=True) # 人類可讀名稱
error_type = Column(String(50), nullable=False, index=True) # 必須對應 Incident.error_type
match_pattern = Column(Text, nullable=False) # JSON 陣列：["name resolution", "could not translate"]
severity_min = Column(String(5), default="P3") # 最低觸發嚴重度
# 動作定義
action_type = Column(String(30), nullable=False) # SSH_CMD / DOCKER_RESTART / ALERT_ONLY / WAIT_RETRY
action_params = Column(Text) # JSON 物件：{"container": "momo-db", "cmd": "docker restart momo-db"}
# 保護機制
cooldown_min = Column(Integer, default=30) # 冷卻分鐘數
max_retries = Column(Integer, default=3) # 達到上限後 escalate
# 狀態與統計
is_active = Column(Boolean, default=True, index=True)
success_count = Column(Integer, default=0) # 歷史成功次數（自動累計）
fail_count = Column(Integer, default=0) # 歷史失敗次數（自動累計）
km_synced = Column(Boolean, default=False) # 是否已沉澱至 KM
created_at = Column(DateTime, default=datetime.now)
updated_at = Column(DateTime, default=datetime.now, onupdate=datetime.now)
def get_match_patterns(self) -> list:
"""回傳 match_pattern 的 Python list"""
try:
return json.loads(self.match_pattern)
except Exception:
return []
def get_action_params(self) -> dict:
"""回傳 action_params 的 Python dict"""
try:
return json.loads(self.action_params) if self.action_params else {}
except Exception:
return {}
def to_dict(self) -> dict:
return {
"id": self.id,
"name": self.name,
"error_type": self.error_type,
"match_pattern": self.get_match_patterns(),
"action_type": self.action_type,
"action_params": self.get_action_params(),
"cooldown_min": self.cooldown_min,
"max_retries": self.max_retries,
"is_active": self.is_active,
"success_count": self.success_count,
"fail_count": self.fail_count,
}
class HealLog(Base):
"""
修復執行紀錄 - 每次 AutoHeal 嘗試都會寫一筆。
result：success / failed / skipped（冷卻中）
"""
__tablename__ = "heal_logs"
id = Column(Integer, primary_key=True)
incident_id = Column(Integer, ForeignKey("incidents.id"), nullable=False, index=True)
playbook_id = Column(Integer, ForeignKey("playbooks.id"), nullable=True)
# 執行內容
action_type = Column(String(30))
action_detail = Column(Text) # 實際執行的指令 / 說明
result = Column(String(20), default="pending", index=True) # success / failed / skipped
result_output = Column(Text) # 指令輸出 / 錯誤訊息
duration_ms = Column(Float, default=0) # 執行耗時（ms）
created_at = Column(DateTime, default=datetime.now)
__table_args__ = (
Index("idx_heal_log_incident", "incident_id", "created_at"),
)
def to_dict(self) -> dict:
return {
"id": self.id,
"incident_id": self.incident_id,
"playbook_id": self.playbook_id,
"action_type": self.action_type,
"action_detail": self.action_detail,
"result": self.result,
"result_output": self.result_output,
"duration_ms": self.duration_ms,
"created_at": self.created_at.isoformat() if self.created_at else None,
}
# ─────────────────────────────────────────────────
# 預設種子 PlayBook 資料（首次啟動植入）
# ─────────────────────────────────────────────────
SEED_PLAYBOOKS = [
{
"name": "Docker DNS 解析失敗修復",
"error_type": "DNS_FAIL",
"match_pattern": json.dumps(["name resolution", "could not translate host name",
"Temporary failure in name resolution"]),
"severity_min": "P2",
"action_type": "DOCKER_RESTART",
"action_params": json.dumps({"container": "momo-db"}),
"cooldown_min": 30,
"max_retries": 3,
},
{
"name": "DB 連線被拒修復",
"error_type": "DB_UNREACHABLE",
"match_pattern": json.dumps(["connection refused", "Connection reset by peer",
"could not connect to server"]),
"severity_min": "P2",
"action_type": "DOCKER_RESTART",
"action_params": json.dumps({"container": "momo-db", "compose": True}),
"cooldown_min": 30,
"max_retries": 3,
},
{
"name": "App OOM 自動重啟",
"error_type": "OOM",
"match_pattern": json.dumps(["SIGKILL", "out of memory", "Worker was sent SIGKILL",
"MemoryError"]),
"severity_min": "P1",
"action_type": "DOCKER_RESTART",
"action_params": json.dumps({"container": "momo-pro-system"}),
"cooldown_min": 60,
"max_retries": 2,
},
{
"name": "Scheduler OOM 自動重啟",
"error_type": "OOM",
"match_pattern": json.dumps(["SIGKILL", "Worker was sent SIGKILL", "MemoryError"]),
"severity_min": "P1",
"action_type": "DOCKER_RESTART",
"action_params": json.dumps({"container": "momo-scheduler"}),
"cooldown_min": 60,
"max_retries": 2,
},
{
"name": "PostgreSQL SSL 連線中斷",
"error_type": "SSL_FAIL",
"match_pattern": json.dumps(["SSL connection has been closed unexpectedly",
"SSL SYSCALL error"]),
"severity_min": "P2",
"action_type": "DOCKER_RESTART",
"action_params": json.dumps({"container": "momo-pro-system"}),
"cooldown_min": 15,
"max_retries": 3,
},
{
"name": "Google Drive 認證失敗告警",
"error_type": "AUTH_FAIL",
"match_pattern": json.dumps(["invalid_grant", "google_token.pickle",
"Token has been expired or revoked"]),
"severity_min": "P2",
"action_type": "ALERT_ONLY",
"action_params": json.dumps({"message": "Google Drive OAuth Token 已過期，請人工重新認證。參閱 docs/guides/google_drive_setup.md"}),
"cooldown_min": 240,
"max_retries": 1,
},
{
"name": "爬蟲 HTTP 429 限流等待",
"error_type": "CRAWLER_FAIL",
"match_pattern": json.dumps(["429 Too Many Requests", "rate limit", "Retry-After"]),
"severity_min": "P3",
"action_type": "WAIT_RETRY",
"action_params": json.dumps({"wait_minutes": 30}),
"cooldown_min": 30,
"max_retries": 2,
},
]

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database/manager.py
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@@ -8,6 +8,7 @@ from .user_models import User, LoginHistory # noqa: F401 - 必須在 trend_mode
from .edm_models import PromoProduct # V-Fix: 確保 EDM 模型被註冊，以便自動建表
from .trend_models import TrendRecord, TrendKeyword, TrendAnalysis, WebSearchCache, TelegramUser # noqa: F401 - 趨勢資料表
from .ai_models import AIGenerationHistory, AIInsight, AIUsageTracking, AIPromptTemplate # AI 記憶體與洞察模型
from .autoheal_models import Incident, Playbook, HealLog # noqa: F401 - ADR-013 AIOps 自動修復表
# 🚩 導入優化後的日誌管理模組
from services.logger_manager import SystemLogger
@@ -60,6 +61,8 @@ class DatabaseManager:
)
self.Session = sessionmaker(bind=self.engine)
sys_log.info(f"[Database] ✅ 使用 PostgreSQL 資料庫 (連線池已優化)")
# ADR-013: 確保 AIOps 自動修復表存在並植入種子 PlayBook
self._init_autoheal_tables()
else:
# SQLite 模式 - 向後相容
if db_path is None:
@@ -111,7 +114,44 @@ class DatabaseManager:
sys_log.error(f"❌ 資料庫結構檢查失敗: {e}")
finally:
session.close()
def _init_autoheal_tables(self):
"""
ADR-013: 在 PostgreSQL 模式下，確保 AIOps 三張表存在並植入種子 PlayBook。
使用 Base.metadata.create_all 以 checkfirst=True 確保冪等執行。
"""
try:
# 建立表（已存在則略過）
from .autoheal_models import Incident, Playbook, HealLog, SEED_PLAYBOOKS
from sqlalchemy import inspect as sa_inspect
inspector = sa_inspect(self.engine)
existing_tables = inspector.get_table_names()
for model in [Incident, Playbook, HealLog]:
if model.__tablename__ not in existing_tables:
model.__table__.create(self.engine, checkfirst=True)
sys_log.info(f"[Database] ✅ 建立 AIOps 表: {model.__tablename__}")
# 植入種子 PlayBook（首次）
session = self.get_session()
try:
count = session.query(Playbook).count()
if count == 0:
for seed in SEED_PLAYBOOKS:
session.add(Playbook(**seed))
session.commit()
sys_log.info(f"[Database] ✅ 植入 {len(SEED_PLAYBOOKS)} 筆種子 PlayBook")
else:
sys_log.info(f"[Database] PlayBook 已有 {count} 筆，略過種子植入")
except Exception as e:
session.rollback()
sys_log.warning(f"[Database] 種子 PlayBook 植入失敗: {e}")
finally:
session.close()
except Exception as e:
sys_log.error(f"[Database] _init_autoheal_tables 失敗 (不影響主程序): {e}")
def get_session(self):
"""
提供外部調用的 Session 實例。

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# ADR-013: AIOps 自動修復閉環架構
**狀態**: Accepted
**日期**: 2026-04-19
**提案者**: Antigravity
---
## 背景與問題
EwoooC 系統已有 L1 Hermes 告警派發，但告警只能「通知」，無法「自癒」。
當 `psycopg2.OperationalError: could not translate host name "momo-postgres"` 這類明確的基礎設施問題發生時，仍需人工 SSH 登入修復，缺乏自動化閉環。
---
## 決策
建立三層 AIOps 閉環架構：
```
Exception → Incident(DB) → PlayBook 匹配 → Auto-Heal 執行 → HealLog(DB) → KM 沉澱(ai_insights) → Telegram 通知
```
### 新增元件
| 元件 | 類型 | 說明 |
|------|------|------|
| `database/autoheal_models.py` | Model | Incident / Playbook / HealLog 三張表 |
| `migrations/013_autoheal.sql` | Migration | 建表 + 種子 PlayBook 植入 |
| `services/auto_heal_service.py` | Service | 核心引擎（分類、匹配、執行、沉澱） |
| `database/manager.py` | 修改 | 加入 `_init_autoheal_tables()` |
| `scheduler.py` | 修改 | 三個核心任務植入 `handle_exception` |
| `requirements.txt` | 修改 | 加入 `paramiko` |
### PlayBook 動作類型
| action_type | 說明 |
|---|---|
| `DOCKER_RESTART` | 透過 SSH 跳板 restart 指定容器 |
| `SSH_CMD` | 執行白名單內的任意 SSH 指令 |
| `ALERT_ONLY` | 僅發 Telegram 告警，人工介入 |
| `WAIT_RETRY` | 紀錄後等待排程重試 |
### 安全設計
- SSH 指令白名單：僅允許 `docker restart *`, `docker compose restart *`, `docker start *`
- 冷卻機制：同 PlayBook 在 `cooldown_min` 內不重複觸發
- 升級機制：達到 `max_retries` 後 incident.status = `escalated` 並通知人工
### KM 沉澱格式
每次修復後寫入 `ai_insights`：
- `insight_type = "auto_heal_playbook"`
- 包含事件、症狀、行動、結果、教訓五要素
- 自動排入 `embedding_retry_queue` 完成 RAG 向量化
---
## 取捨
**優先使用 paramiko** 而非 subprocess + CLI ssh，原因是在容器內環境控制更精準，且支援跳板機 ProxyJump。若 paramiko 未安裝則自動降級到 CLI ssh（向後相容）。
---
## 結果
- P1/P2 等級的 DB_UNREACHABLE / DNS_FAIL 類問題可在 30 秒內完成自動修復
- 所有修復知識自動沉澱至 RAG KM，提升未來 AI 的判斷品質
- 覆蓋任務：`run_auto_import_task` / `run_icaim_analysis_task` / `run_weekly_strategy_task`

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-- Migration 013: AIOps 自動修復三張表
-- incidents / playbooks / heal_logs
-- 建立日期：2026-04-19
-- ─────────────────────────────────────────────────
-- 表 1: incidents (事件主表)
-- ─────────────────────────────────────────────────
CREATE TABLE IF NOT EXISTS incidents (
id SERIAL PRIMARY KEY,
task_name VARCHAR(100) NOT NULL,
error_type VARCHAR(50) NOT NULL,
error_message TEXT NOT NULL,
error_traceback TEXT,
severity VARCHAR(5) NOT NULL DEFAULT 'P2',
status VARCHAR(20) NOT NULL DEFAULT 'open',
playbook_id INTEGER REFERENCES playbooks(id),
retry_count INTEGER DEFAULT 0,
resolved_at TIMESTAMP,
created_at TIMESTAMP NOT NULL DEFAULT NOW(),
updated_at TIMESTAMP NOT NULL DEFAULT NOW()
);
CREATE INDEX IF NOT EXISTS idx_incident_status_created ON incidents(status, created_at);
CREATE INDEX IF NOT EXISTS idx_incident_task_error ON incidents(task_name, error_type);
-- ─────────────────────────────────────────────────
-- 表 2: playbooks (PlayBook 規則庫)
-- ─────────────────────────────────────────────────
CREATE TABLE IF NOT EXISTS playbooks (
id SERIAL PRIMARY KEY,
name VARCHAR(200) NOT NULL UNIQUE,
error_type VARCHAR(50) NOT NULL,
match_pattern TEXT NOT NULL, -- JSON 陣列
severity_min VARCHAR(5) DEFAULT 'P3',
action_type VARCHAR(30) NOT NULL, -- SSH_CMD / DOCKER_RESTART / ALERT_ONLY / WAIT_RETRY
action_params TEXT, -- JSON 物件
cooldown_min INTEGER DEFAULT 30,
max_retries INTEGER DEFAULT 3,
is_active BOOLEAN DEFAULT TRUE,
success_count INTEGER DEFAULT 0,
fail_count INTEGER DEFAULT 0,
km_synced BOOLEAN DEFAULT FALSE,
created_at TIMESTAMP NOT NULL DEFAULT NOW(),
updated_at TIMESTAMP NOT NULL DEFAULT NOW()
);
CREATE INDEX IF NOT EXISTS idx_playbook_error_type ON playbooks(error_type, is_active);
-- ─────────────────────────────────────────────────
-- 表 3: heal_logs (修復執行紀錄)
-- ─────────────────────────────────────────────────
CREATE TABLE IF NOT EXISTS heal_logs (
id SERIAL PRIMARY KEY,
incident_id INTEGER NOT NULL REFERENCES incidents(id),
playbook_id INTEGER REFERENCES playbooks(id),
action_type VARCHAR(30),
action_detail TEXT,
result VARCHAR(20) DEFAULT 'pending', -- success / failed / skipped
result_output TEXT,
duration_ms FLOAT DEFAULT 0,
created_at TIMESTAMP NOT NULL DEFAULT NOW()
);
CREATE INDEX IF NOT EXISTS idx_heal_log_incident ON heal_logs(incident_id, created_at);
CREATE INDEX IF NOT EXISTS idx_heal_log_result ON heal_logs(result, created_at);
-- ─────────────────────────────────────────────────
-- 種子 PlayBook 資料（首次初始化，已存在則略過）
-- ─────────────────────────────────────────────────
INSERT INTO playbooks (name, error_type, match_pattern, severity_min, action_type, action_params, cooldown_min, max_retries)
SELECT * FROM (VALUES
(
'Docker DNS 解析失敗修復',
'DNS_FAIL',
'["name resolution", "could not translate host name", "Temporary failure in name resolution"]',
'P2', 'DOCKER_RESTART',
'{"container": "momo-db"}',
30, 3
),
(
'DB 連線被拒修復',
'DB_UNREACHABLE',
'["connection refused", "Connection reset by peer", "could not connect to server"]',
'P2', 'DOCKER_RESTART',
'{"container": "momo-db", "compose": true}',
30, 3
),
(
'App OOM 自動重啟',
'OOM',
'["SIGKILL", "out of memory", "Worker was sent SIGKILL", "MemoryError"]',
'P1', 'DOCKER_RESTART',
'{"container": "momo-pro-system"}',
60, 2
),
(
'Scheduler OOM 自動重啟',
'OOM',
'["SIGKILL", "Worker was sent SIGKILL"]',
'P1', 'DOCKER_RESTART',
'{"container": "momo-scheduler"}',
60, 2
),
(
'PostgreSQL SSL 連線中斷',
'SSL_FAIL',
'["SSL connection has been closed unexpectedly", "SSL SYSCALL error"]',
'P2', 'DOCKER_RESTART',
'{"container": "momo-pro-system"}',
15, 3
),
(
'Google Drive 認證失敗告警',
'AUTH_FAIL',
'["invalid_grant", "google_token.pickle", "Token has been expired or revoked"]',
'P2', 'ALERT_ONLY',
'{"message": "Google Drive OAuth Token 已過期，請人工重新認證。參閱 docs/guides/google_drive_setup.md"}',
240, 1
),
(
'爬蟲 HTTP 429 限流等待',
'CRAWLER_FAIL',
'["429 Too Many Requests", "rate limit", "Retry-After"]',
'P3', 'WAIT_RETRY',
'{"wait_minutes": 30}',
30, 2
)
) AS v(name, error_type, match_pattern, severity_min, action_type, action_params, cooldown_min, max_retries)
WHERE NOT EXISTS (SELECT 1 FROM playbooks WHERE playbooks.name = v.name);

3
requirements.txt
View File

@@ -21,4 +21,5 @@ feedparser
beautifulsoup4
lxml
prometheus-client
python-telegram-bot
python-telegram-bot
paramiko # ADR-013: AIOps SSH 跳板修復

33
scheduler.py
View File

@@ -1574,6 +1574,17 @@ def run_auto_import_task():
except Exception as notify_error:
logging.error(f"[Scheduler] [AutoImport] ❌ LINE 通知失敗 | Error: {notify_error}")
# ADR-013: AIOps 自動修復 — PlayBook 匹配 + KM 沉澱
try:
from services.auto_heal_service import auto_heal_service
auto_heal_service.handle_exception(
task_name="run_auto_import_task",
exception=e,
traceback_str=_tb.format_exc(),
)
except Exception as _heal_e:
logging.error(f"[Scheduler] [AutoImport] auto_heal_service 失敗: {_heal_e}")
def run_competitor_price_feeder_task():
"""
競品價格補給線排程任務（每 4 小時執行一次）
@@ -1679,8 +1690,19 @@ def run_icaim_analysis_task():
_save_stats('icaim_dispatch', {**dispatch_result, "status": "Success"})
except Exception as e:
import traceback as _tb
logging.error(f"[Scheduler] [ICAIM] 🚨 任務異常 | Error: {e}")
_save_stats('icaim_analysis', {"status": "Failed", "error": str(e)})
# ADR-013: AIOps 自動修復
try:
from services.auto_heal_service import auto_heal_service
auto_heal_service.handle_exception(
task_name="run_icaim_analysis_task",
exception=e,
traceback_str=_tb.format_exc(),
)
except Exception as _heal_e:
logging.error(f"[Scheduler] [ICAIM] auto_heal_service 失敗: {_heal_e}")
def run_weekly_strategy_task():
@@ -1694,8 +1716,19 @@ def run_weekly_strategy_task():
generate_weekly_strategy_report(force_tg_alert=True)
logging.info("[Scheduler] [Strategy] ✅ Gemini 策略師週報任務完成")
except Exception as e:
import traceback as _tb
logging.error(f"[Scheduler] [Strategy] 🚨 任務異常 | Error: {e}")
_save_stats('weekly_strategy', {"status": "Failed", "error": str(e)})
# ADR-013: AIOps 自動修復
try:
from services.auto_heal_service import auto_heal_service
auto_heal_service.handle_exception(
task_name="run_weekly_strategy_task",
exception=e,
traceback_str=_tb.format_exc(),
)
except Exception as _heal_e:
logging.error(f"[Scheduler] [Strategy] auto_heal_service 失敗: {_heal_e}")
def run_db_backup_task():

524
services/auto_heal_service.py Normal file
View File

@@ -0,0 +1,524 @@
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
"""
auto_heal_service.py - EwoooC AIOps 自動修復引擎 (ADR-013)
完整閉環：
Exception 觸發
→ create_incident() : 寫入 incidents 表
→ classify_error() : 識別 error_type
→ match_playbook() : 比對 playbooks 規則庫
→ execute_playbook() : 執行修復動作
→ _write_heal_log() : 寫入 heal_logs 表
→ sink_to_km() : store_insight → KM RAG 沉澱
→ notify_telegram() : 推播修復結果
"""
import json
import os
import time
import traceback as tb
from datetime import datetime, timedelta
from typing import Optional, Tuple
import requests
from dotenv import load_dotenv
from database.manager import get_session
from database.autoheal_models import Incident, Playbook, HealLog, SEED_PLAYBOOKS
from services.logger_manager import SystemLogger
load_dotenv()
sys_log = SystemLogger("AutoHeal").get_logger()
# ─── Telegram 設定 ───────────────────────────────────────
_BOT_TOKEN = os.getenv("TELEGRAM_BOT_TOKEN") or os.getenv("OPENCLAW_BOT_TOKEN", "")
_CHAT_ID = os.getenv("OPENCLAW_GROUP_ID", "-1003940688311")
# ─── SSH 跳板機設定 ──────────────────────────────────────
_JUMP_HOST = os.getenv("SSH_JUMP_HOST", "192.168.0.110")
_JUMP_USER = os.getenv("SSH_JUMP_USER", "wooo")
_TARGET_HOST = os.getenv("SSH_TARGET_HOST", "192.168.0.188")
_TARGET_USER = os.getenv("SSH_TARGET_USER", "ollama")
# ─── 白名單允許執行的指令前綴 ────────────────────────────
_CMD_WHITELIST = [
"docker restart ",
"docker compose restart ",
"docker start ",
]
# ─── 錯誤分類對照表（keyword → error_type）──────────────
_ERROR_CLASSIFY_MAP = {
"DNS_FAIL": ["name resolution", "could not translate host name",
"Temporary failure in name resolution"],
"DB_UNREACHABLE": ["connection refused", "Connection reset by peer",
"could not connect to server", "psycopg2.OperationalError"],
"OOM": ["SIGKILL", "out of memory", "Worker was sent SIGKILL", "MemoryError"],
"SSL_FAIL": ["SSL connection has been closed unexpectedly", "SSL SYSCALL error"],
"AUTH_FAIL": ["invalid_grant", "google_token.pickle", "Token has been expired"],
"CRAWLER_FAIL": ["429 Too Many Requests", "rate limit", "Retry-After",
"CloudflareCaptcha", "webdriver"],
"IMPORT_FAIL": ["import_service", "ImportError", "sync_daily_sales"],
"TIMEOUT": ["Timeout", "timed out", "TimeoutError"],
}
_SEVERITY_MAP = {
"P1": ["OOM", "SSL_FAIL"],
"P2": ["DNS_FAIL", "DB_UNREACHABLE", "AUTH_FAIL"],
"P3": ["CRAWLER_FAIL", "IMPORT_FAIL", "TIMEOUT"],
}
# ──────────────────────────────────────────────────────────
# 工具函數
# ──────────────────────────────────────────────────────────
def _classify_error(error_msg: str) -> Tuple[str, str]:
"""回傳 (error_type, severity)"""
lower = error_msg.lower()
for etype, keywords in _ERROR_CLASSIFY_MAP.items():
if any(k.lower() in lower for k in keywords):
for sev, etypes in _SEVERITY_MAP.items():
if etype in etypes:
return etype, sev
return etype, "P3"
return "UNKNOWN", "P3"
def _is_cmd_allowed(cmd: str) -> bool:
"""白名單驗證：防止任意 RCE"""
c = cmd.strip()
return any(c.startswith(prefix) for prefix in _CMD_WHITELIST)
def _send_telegram(msg: str) -> None:
"""推播訊息至 Telegram 群組"""
if not _BOT_TOKEN:
sys_log.warning("[AutoHeal] TELEGRAM_BOT_TOKEN 未設定，略過推播")
return
try:
requests.post(
f"https://api.telegram.org/bot{_BOT_TOKEN}/sendMessage",
json={"chat_id": _CHAT_ID, "text": msg, "parse_mode": "HTML"},
timeout=10,
)
except Exception as e:
sys_log.error(f"[AutoHeal] Telegram 推播失敗: {e}")
def _execute_ssh_cmd(cmd: str) -> Tuple[bool, str]:
"""
透過 paramiko 執行 SSH 跳板指令。
若 paramiko 不可用則降級為 subprocess + CLI ssh。
"""
if not _is_cmd_allowed(cmd):
return False, f"指令不在白名單中，拒絕執行: {cmd}"
try:
import paramiko
jump = paramiko.SSHClient()
jump.set_missing_host_key_policy(paramiko.AutoAddPolicy())
jump.connect(_JUMP_HOST, username=_JUMP_USER, timeout=10)
# 透過跳板機建立隧道
transport = jump.get_transport()
dest_addr = (_TARGET_HOST, 22)
src_addr = (_JUMP_HOST, 0)
chan = transport.open_channel("direct-tcpip", dest_addr, src_addr)
target = paramiko.SSHClient()
target.set_missing_host_key_policy(paramiko.AutoAddPolicy())
target.connect(_TARGET_HOST, username=_TARGET_USER, sock=chan, timeout=15)
_stdin, stdout, stderr = target.exec_command(cmd, timeout=60)
out = stdout.read().decode("utf-8", errors="replace").strip()
err = stderr.read().decode("utf-8", errors="replace").strip()
exit_code = stdout.channel.recv_exit_status()
target.close()
jump.close()
if exit_code == 0:
return True, out or "指令執行成功"
else:
return False, f"exit_code={exit_code}\n{err or out}"
except ImportError:
# paramiko 尚未安裝，降級到 cli ssh
sys_log.warning("[AutoHeal] paramiko 未安裝，改用 subprocess + CLI ssh")
import subprocess
full_cmd = [
"ssh", "-o", "StrictHostKeyChecking=no",
"-J", f"{_JUMP_USER}@{_JUMP_HOST}",
f"{_TARGET_USER}@{_TARGET_HOST}", cmd,
]
result = subprocess.run(full_cmd, capture_output=True, text=True, timeout=60)
if result.returncode == 0:
return True, result.stdout.strip() or "指令執行成功"
else:
return False, result.stderr.strip() or result.stdout.strip()
except Exception as e:
return False, f"SSH 執行例外: {e}"
# ──────────────────────────────────────────────────────────
# 核心引擎
# ──────────────────────────────────────────────────────────
class AutoHealService:
"""
AIOps 自動修復引擎。
使用方式（在 scheduler.py 的 except 區塊）：
from services.auto_heal_service import auto_heal_service
auto_heal_service.handle_exception(
task_name="run_auto_import_task",
exception=e,
traceback_str=traceback.format_exc()
)
"""
# ── 步驟 1：統一入口 ────────────────────────────────
def handle_exception(self, task_name: str, exception: Exception,
traceback_str: str = "") -> Optional[int]:
"""
統一例外處理入口。回傳 incident_id，若前置失敗則回傳 None。
"""
error_msg = str(exception)
error_type, severity = _classify_error(error_msg)
sys_log.info(f"[AutoHeal] 收到例外 task={task_name} type={error_type} sev={severity}")
incident = self._create_incident(task_name, error_type, error_msg,
traceback_str, severity)
if not incident:
return None
playbook = self._match_playbook(incident)
if not playbook:
sys_log.info(f"[AutoHeal] 未找到匹配 PlayBook (incident_id={incident.id})")
self._notify_no_playbook(incident)
return incident.id
heal_log = self._execute_playbook(incident, playbook)
self._sink_to_km(incident, playbook, heal_log)
self._notify_telegram(incident, playbook, heal_log)
return incident.id
# ── 步驟 2：建立 Incident ───────────────────────────
def _create_incident(self, task_name: str, error_type: str, error_msg: str,
traceback_str: str, severity: str) -> Optional[Incident]:
session = get_session()
try:
incident = Incident(
task_name = task_name,
error_type = error_type,
error_message = error_msg[:2000], # 限制長度
error_traceback = traceback_str[:5000],
severity = severity,
status = "open",
created_at = datetime.now(),
updated_at = datetime.now(),
)
session.add(incident)
session.commit()
sys_log.info(f"[AutoHeal] 建立 Incident id={incident.id} type={error_type}")
return incident
except Exception as e:
session.rollback()
sys_log.error(f"[AutoHeal] create_incident 失敗: {e}")
return None
finally:
session.close()
# ── 步驟 3：PlayBook 匹配 ───────────────────────────
def _match_playbook(self, incident: Incident) -> Optional[Playbook]:
"""
匹配邏輯：
1. error_type 精確比對
2. match_pattern 任一關鍵字命中
3. 冷卻時間檢查（同 playbook 最近一次執行是否已超過 cooldown_min）
"""
session = get_session()
try:
candidates = session.query(Playbook).filter_by(
error_type=incident.error_type, is_active=True
).all()
error_lower = incident.error_message.lower()
for pb in candidates:
patterns = pb.get_match_patterns()
if not any(p.lower() in error_lower for p in patterns):
continue
# 冷卻檢查
cooldown_threshold = datetime.now() - timedelta(minutes=pb.cooldown_min)
recent_log = session.query(HealLog).filter(
HealLog.playbook_id == pb.id,
HealLog.created_at >= cooldown_threshold,
HealLog.result == "success",
).first()
if recent_log:
sys_log.info(f"[AutoHeal] PlayBook '{pb.name}' 在冷卻中，略過")
continue
# 上限檢查（同 incident 的 retry_count）
if incident.retry_count >= pb.max_retries:
sys_log.warning(f"[AutoHeal] 已達 max_retries({pb.max_retries})，升級為 escalated")
self._escalate_incident(incident)
return None
sys_log.info(f"[AutoHeal] 匹配 PlayBook: '{pb.name}' (id={pb.id})")
return pb
return None
except Exception as e:
sys_log.error(f"[AutoHeal] match_playbook 失敗: {e}")
return None
finally:
session.close()
# ── 步驟 4：執行 PlayBook ───────────────────────────
def _execute_playbook(self, incident: Incident, playbook: Playbook) -> HealLog:
"""根據 action_type 執行對應動作，回傳 HealLog"""
t_start = time.time()
params = playbook.get_action_params()
action_detail = ""
result = "failed"
result_output = ""
# 更新 incident 狀態
self._update_incident_status(incident.id, "healing", playbook.id)
try:
if playbook.action_type == "DOCKER_RESTART":
container = params.get("container", "")
use_compose = params.get("compose", False)
if use_compose:
cmd = f"cd /home/ollama/momo-pro && docker compose restart {container}"
else:
cmd = f"docker restart {container}"
action_detail = cmd
ok, output = _execute_ssh_cmd(cmd if not use_compose else f"docker compose restart {container}")
# compose 指令需要在目錄下執行，強制用 SSH
if use_compose:
ok, output = _execute_ssh_cmd(f"docker restart {container}")
result = "success" if ok else "failed"
result_output = output
elif playbook.action_type == "SSH_CMD":
cmd = params.get("cmd", "")
action_detail = cmd
ok, output = _execute_ssh_cmd(cmd)
result = "success" if ok else "failed"
result_output = output
elif playbook.action_type == "ALERT_ONLY":
msg = params.get("message", "需人工介入")
action_detail = f"[ALERT_ONLY] {msg}"
result = "success"
result_output = msg
elif playbook.action_type == "WAIT_RETRY":
wait_min = params.get("wait_minutes", 30)
action_detail = f"[WAIT_RETRY] 靜默等待 {wait_min} 分鐘後由排程自動重試"
result = "success"
result_output = f"已記錄，排程將在 {wait_min} 分鐘後重試"
else:
action_detail = f"未知 action_type: {playbook.action_type}"
result = "skipped"
result_output = action_detail
except Exception as e:
result = "failed"
result_output = f"執行例外: {e}"
sys_log.error(f"[AutoHeal] execute_playbook 例外: {e}")
duration_ms = (time.time() - t_start) * 1000
heal_log = self._write_heal_log(
incident.id, playbook.id,
playbook.action_type, action_detail,
result, result_output, duration_ms,
)
# 更新 PlayBook 統計
self._update_playbook_stats(playbook.id, result)
# 更新 Incident 最終狀態
final_status = "resolved" if result == "success" else "open"
self._update_incident_status(incident.id, final_status, playbook.id,
increment_retry=(result != "success"))
sys_log.info(f"[AutoHeal] 執行完成 result={result} duration={duration_ms:.0f}ms")
return heal_log
# ── 步驟 5：寫入 HealLog ────────────────────────────
def _write_heal_log(self, incident_id, playbook_id, action_type,
action_detail, result, result_output, duration_ms) -> HealLog:
session = get_session()
try:
hl = HealLog(
incident_id = incident_id,
playbook_id = playbook_id,
action_type = action_type,
action_detail = action_detail,
result = result,
result_output = (result_output or "")[:2000],
duration_ms = duration_ms,
created_at = datetime.now(),
)
session.add(hl)
session.commit()
return hl
except Exception as e:
session.rollback()
sys_log.error(f"[AutoHeal] write_heal_log 失敗: {e}")
return HealLog(result=result, action_detail=action_detail)
finally:
session.close()
# ── 步驟 6：KM 沉澱 ────────────────────────────────
def _sink_to_km(self, incident: Incident, playbook: Playbook, heal_log: HealLog) -> None:
"""將修復知識寫入 ai_insights（KM RAG 雙寫）"""
try:
from services.openclaw_learning_service import store_insight
today = datetime.now().strftime("%Y-%m-%d")
result_zh = {"success": "成功", "failed": "失敗", "skipped": "跳過"}.get(
heal_log.result, heal_log.result
)
content = (
f"[AIOps 自動修復紀錄]\n"
f"事件：{incident.task_name} 發生 {incident.error_type}（嚴重度 {incident.severity}）\n"
f"症狀：{incident.error_message[:300]}\n"
f"行動：執行 PlayBook「{playbook.name}」→ {heal_log.action_detail}\n"
f"結果：{result_zh}（耗時 {heal_log.duration_ms:.0f}ms）\n"
f"教訓：此類型錯誤（{incident.error_type}）可透過 {playbook.action_type} 自動修復。\n"
f"處理時間：{today}"
)
store_insight(
insight_type = "auto_heal_playbook",
period = today,
content = content,
metadata = {
"playbook_id": playbook.id,
"incident_id": incident.id,
"error_type": incident.error_type,
"result": heal_log.result,
},
ai_model = "auto_heal_engine_v1",
)
sys_log.info(f"[AutoHeal] KM 沉澱完成 (incident_id={incident.id})")
except Exception as e:
sys_log.warning(f"[AutoHeal] sink_to_km 失敗（不影響主流程）: {e}")
# ── 步驟 7：Telegram 通知 ───────────────────────────
def _notify_telegram(self, incident: Incident, playbook: Playbook,
heal_log: HealLog) -> None:
"""推播修復結果通知"""
icon = {"success": "✅", "failed": "❌", "skipped": "⏭️"}.get(heal_log.result, "❓")
sev_icon = {"P1": "🔴", "P2": "🟠", "P3": "🟡"}.get(incident.severity, "⚪")
msg = (
f"{sev_icon} <b>[EwoooC AIOps] 自動修復報告</b>\n\n"
f"📌 任務：<code>{incident.task_name}</code>\n"
f"🚨 錯誤類型：<code>{incident.error_type}</code>\n"
f"📝 症狀：{incident.error_message[:200]}\n\n"
f"🔧 PlayBook：{playbook.name}\n"
f"⚙️ 動作：<code>{heal_log.action_detail}</code>\n"
f"{icon} 結果：<b>{heal_log.result}</b>（{heal_log.duration_ms:.0f}ms）\n\n"
f"💾 已沉澱至 KM（auto_heal_playbook）"
)
_send_telegram(msg)
def _notify_no_playbook(self, incident: Incident) -> None:
"""未找到 PlayBook 時的人工告警"""
sev_icon = {"P1": "🔴", "P2": "🟠", "P3": "🟡"}.get(incident.severity, "⚪")
msg = (
f"{sev_icon} <b>[EwoooC AIOps] 需人工介入</b>\n\n"
f"📌 任務：<code>{incident.task_name}</code>\n"
f"🚨 錯誤類型：<code>{incident.error_type}</code>\n"
f"📝 症狀：{incident.error_message[:300]}\n\n"
f"⚠️ 未找到匹配的 PlayBook，請人工排查。\n"
f"🆔 Incident ID：{incident.id}"
)
_send_telegram(msg)
# ── 輔助函數 ────────────────────────────────────────
def _update_incident_status(self, incident_id: int, status: str,
playbook_id: Optional[int] = None,
increment_retry: bool = False) -> None:
session = get_session()
try:
inc = session.query(Incident).get(incident_id)
if inc:
inc.status = status
inc.updated_at = datetime.now()
if playbook_id:
inc.playbook_id = playbook_id
if status == "resolved":
inc.resolved_at = datetime.now()
if increment_retry:
inc.retry_count = (inc.retry_count or 0) + 1
session.commit()
except Exception as e:
session.rollback()
sys_log.error(f"[AutoHeal] update_incident_status 失敗: {e}")
finally:
session.close()
def _escalate_incident(self, incident: Incident) -> None:
self._update_incident_status(incident.id, "escalated")
sev_icon = {"P1": "🔴", "P2": "🟠", "P3": "🟡"}.get(incident.severity, "⚪")
msg = (
f"{sev_icon} <b>[EwoooC AIOps] 告警升級 — 需立即人工介入</b>\n\n"
f"📌 任務：<code>{incident.task_name}</code>\n"
f"🚨 錯誤：<code>{incident.error_type}</code>\n"
f"🔁 已重試 {incident.retry_count} 次，自動修復失敗。\n"
f"📝 {incident.error_message[:300]}"
)
_send_telegram(msg)
def _update_playbook_stats(self, playbook_id: int, result: str) -> None:
session = get_session()
try:
pb = session.query(Playbook).get(playbook_id)
if pb:
if result == "success":
pb.success_count = (pb.success_count or 0) + 1
else:
pb.fail_count = (pb.fail_count or 0) + 1
pb.updated_at = datetime.now()
session.commit()
except Exception as e:
session.rollback()
sys_log.error(f"[AutoHeal] update_playbook_stats 失敗: {e}")
finally:
session.close()
# ── 種子 PlayBook 初始化 ────────────────────────────
@staticmethod
def init_seed_playbooks() -> None:
"""首次啟動時植入預設 PlayBook（已存在則略過）"""
session = get_session()
try:
for seed in SEED_PLAYBOOKS:
exists = session.query(Playbook).filter_by(name=seed["name"]).first()
if not exists:
session.add(Playbook(**seed))
session.commit()
sys_log.info("[AutoHeal] 種子 PlayBook 初始化完成")
except Exception as e:
session.rollback()
sys_log.error(f"[AutoHeal] init_seed_playbooks 失敗: {e}")
finally:
session.close()
# ─── 模組級單例 ─────────────────────────────────────────
auto_heal_service = AutoHealService()