7f4088bcd0
【P0.1】knowledge_extractor_service.py:210 — AttributeError 修復 - Signal.description 欄位不存在（100% 失敗，KM 每天+5 根因） - 改用 alert_name + annotations.summary 拼接文字 【P0.2+P0.3】Gate 9+11 唯讀指令鬆綁 - blast_radius_calculator: kubectl get/top/describe/logs/version → score=1（非 50） - operation_parser: 增加 INVESTIGATE 類型識別（唯讀 kubectl 不回 None） - executor.py: OperationType 新增 INVESTIGATE enum - approval_execution.py: INVESTIGATE 路徑直接呼叫 execute_kubectl_command 【P0.4】MCP SSH/K8s Provider 修復 - decision_manager: params= → parameters=（符合 MCPToolProvider.execute 簽名） - decision_manager: MCPToolResult .get() → .success/.output（dataclass 用法） - decision_manager + ssh_provider: 補入 hosts 120/121（原 default 缺失） - auto_approve: phase2_agent_debate source bypass confidence 閾值 【P0.5】告警規則語義矛盾修復 - alert_rules.yaml: 8 條 kubectl 查詢規則 RESTART_DEPLOYMENT → NO_ACTION (CrashLoopBackOff/PostgreSQL 連線/慢查詢/MinIO 磁碟/K3s 節點/告警鏈路/SSL/CoreDNS 等) - incident_service.py: cAdvisor/CoreDNS 從 general 拆出獨立分類 【P0.6】proactive_inspector 動態基線 PromQL 全修 - 5 個 MONITORED_METRICS PromQL 全部修正（cadvisor label/datname/blackbox） - db_connection_pool: datname="awoooi" → "awoooi_prod" - http_error_rate: 無效 http_requests_total → blackbox probe_success - cpu/memory: namespace label → name=~"k8s_api_awoooi-api.*" Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
3033 lines
140 KiB
Python
3033 lines
140 KiB
Python
"""
|
||
Decision Manager - Phase 6.5 非同步決策狀態機
|
||
# 2026-04-10 Claude Sonnet 4.6: auto_execute ApprovalRequest 修復 + placeholder 替換
|
||
=============================================
|
||
|
||
實作「雙軌決策」(Dual-Engine Decision):
|
||
1. OpenClaw LLM (主要) - 智能提案
|
||
2. Expert System (備援) - 規則引擎
|
||
|
||
狀態機:
|
||
- INIT: 事件剛建立
|
||
- ANALYZING: 正在分析中 (LLM + Expert 並行)
|
||
- READY: 決策就緒，等待統帥親核
|
||
- EXECUTING: 已授權，正在執行
|
||
- COMPLETED: 執行完成
|
||
|
||
統帥鐵律:
|
||
- 永遠不能讓 UI 鎖死
|
||
- 30 秒內必須有 decision_token
|
||
- LLM 失敗時 Expert System 保底
|
||
"""
|
||
|
||
import asyncio
|
||
import json
|
||
from datetime import UTC, datetime
|
||
from enum import Enum
|
||
from typing import Any, Protocol, runtime_checkable
|
||
from uuid import uuid4
|
||
|
||
import structlog
|
||
|
||
from src.core.config import settings
|
||
from src.core.redis_client import get_redis
|
||
from src.models.incident import Incident
|
||
from src.models.playbook import SymptomPattern
|
||
from src.services.auto_approve import get_auto_approve_policy
|
||
from src.services.openclaw import get_openclaw
|
||
from src.services.playbook_service import get_playbook_service
|
||
|
||
logger = structlog.get_logger(__name__)
|
||
|
||
# Phase 7.5: Playbook 優先閾值
|
||
PLAYBOOK_SIMILARITY_THRESHOLD = 0.85 # 相似度 >= 85% 直接使用 Playbook
|
||
|
||
# P1 fix 2026-04-11: background task GC guard — keep strong refs until done
|
||
_background_tasks: set[asyncio.Task] = set()
|
||
|
||
def _fire_and_forget(coro) -> asyncio.Task:
|
||
"""Create a background task with GC protection via _background_tasks."""
|
||
task = asyncio.create_task(coro)
|
||
_background_tasks.add(task)
|
||
task.add_done_callback(_background_tasks.discard)
|
||
return task
|
||
|
||
# P1 fix 2026-04-11: kubectl action dangerous char whitelist
|
||
import re as _re_module
|
||
_ALLOWED_KUBECTL_PATTERN = _re_module.compile(
|
||
r"^kubectl\s+(rollout restart|rollout undo|scale|delete pod|get|describe|logs)"
|
||
r"\s+[a-zA-Z0-9_./-]+(\s+(-n|--namespace)\s+[a-zA-Z0-9_-]+)?$"
|
||
)
|
||
|
||
|
||
# =============================================================================
|
||
# Phase 31 (ADR-067 2026-04-10): Log 異常摘要 — NemoTron deepseek-r1:14b
|
||
# =============================================================================
|
||
|
||
async def _send_log_summary(incident: "Incident") -> None:
|
||
"""
|
||
非同步取得 Pod log 異常摘要，用 NemoTron bot 發到 SRE 群組
|
||
觸發點：_push_decision_to_telegram 發完審批卡後
|
||
"""
|
||
try:
|
||
target = incident.affected_services[0] if incident.affected_services else None
|
||
if not target:
|
||
return
|
||
namespace = "awoooi-prod"
|
||
if incident.signals:
|
||
namespace = incident.signals[0].labels.get("namespace", "awoooi-prod")
|
||
|
||
from src.services.log_summary_service import get_log_summary_service
|
||
svc = get_log_summary_service()
|
||
summary = await svc.summarize_with_soft_timeout(pod_name=target, namespace=namespace)
|
||
if not summary:
|
||
return
|
||
|
||
from src.services.telegram_gateway import get_telegram_gateway
|
||
tg = get_telegram_gateway()
|
||
await tg.send_as_nemotron(
|
||
f"📋 <b>Log 異常摘要</b> — <code>{target}</code>\n{summary}"
|
||
)
|
||
import structlog as _sl
|
||
_sl.get_logger(__name__).info("log_summary_sent", target=target, incident_id=incident.incident_id)
|
||
except Exception as e:
|
||
import structlog as _sl
|
||
_sl.get_logger(__name__).warning("log_summary_failed", error=str(e))
|
||
|
||
|
||
# =============================================================================
|
||
# Telegram 推送 (Phase 6.5: 決策就緒通知)
|
||
# =============================================================================
|
||
|
||
async def _push_decision_to_telegram(
|
||
incident: Incident,
|
||
proposal_data: dict[str, Any],
|
||
) -> None:
|
||
"""
|
||
決策就緒時推送到 Telegram
|
||
|
||
Phase 6.5: 整合 Signal Worker 流程與 Telegram 通知
|
||
2026-03-27 ogt: 加入 Redis 去重機制 (10 分鐘 TTL)
|
||
"""
|
||
try:
|
||
# 延遲導入避免循環依賴
|
||
from src.core.redis_client import get_redis
|
||
from src.services.telegram_gateway import (
|
||
classify_notification,
|
||
get_telegram_gateway,
|
||
NotificationType,
|
||
_smart_truncate as _smt,
|
||
)
|
||
|
||
# 🔴 去重檢查：同一個 incident 10 分鐘內只發一次
|
||
redis = get_redis()
|
||
dedup_key = f"telegram_sent:{incident.incident_id}"
|
||
if await redis.exists(dedup_key):
|
||
logger.debug(
|
||
"telegram_push_skipped",
|
||
reason="Already sent within 10 minutes",
|
||
incident_id=incident.incident_id,
|
||
)
|
||
return
|
||
|
||
# 2026-04-09 Claude Code: resolved Incident 不重送 Telegram
|
||
# 場景: dedup TTL 過期後，已 resolve 的 Incident 仍被重新推送
|
||
if incident.status and str(incident.status).lower() in ("resolved", "closed"):
|
||
logger.info(
|
||
"telegram_push_skipped",
|
||
reason="Incident already resolved",
|
||
incident_id=incident.incident_id,
|
||
)
|
||
return
|
||
|
||
# 🔴 靜默檢查：此資源是否被靜默 (2026-03-27 P1 優化)
|
||
target = incident.affected_services[0] if incident.affected_services else "unknown"
|
||
silence_key = f"telegram_silence:{target}"
|
||
if await redis.exists(silence_key):
|
||
logger.info(
|
||
"telegram_push_silenced",
|
||
reason="Resource is silenced",
|
||
incident_id=incident.incident_id,
|
||
resource=target,
|
||
)
|
||
return
|
||
|
||
# 檢查是否有設定 Bot Token
|
||
if not settings.OPENCLAW_TG_BOT_TOKEN:
|
||
logger.debug(
|
||
"telegram_push_skipped",
|
||
reason="Bot token not configured",
|
||
incident_id=incident.incident_id,
|
||
)
|
||
return
|
||
|
||
gateway = get_telegram_gateway()
|
||
|
||
# 從 proposal_data 提取資料
|
||
import re as _re
|
||
def _strip_placeholders(s: str) -> str:
|
||
"""移除 <placeholder> 佔位符，避免 Telegram HTML parse 錯誤"""
|
||
return _re.sub(r'<[^>]+>', '', s).strip()
|
||
|
||
def _parse_debate_summary(reasoning: str) -> dict[str, str]:
|
||
"""
|
||
解析 coordinator debate_summary → {diagnosis, plan, review, critic}
|
||
|
||
格式：「診斷：{...}；方案：{...}；安全審查：{...}；質疑：{...}」
|
||
2026-04-17 ogt + Claude Sonnet 4.6: 修復 TYPE-8M 三欄重複渲染
|
||
根因：diagnosis/system_impact/probable_cause 全用 reasoning[:100] → 同一段字
|
||
"""
|
||
result: dict[str, str] = {"diagnosis": "", "plan": "", "review": "", "critic": ""}
|
||
for part in reasoning.split("；"):
|
||
part = part.strip()
|
||
if part.startswith("診斷："):
|
||
result["diagnosis"] = part[3:]
|
||
elif part.startswith("方案："):
|
||
result["plan"] = part[3:]
|
||
elif part.startswith("安全審查："):
|
||
result["review"] = part[5:]
|
||
elif part.startswith("質疑："):
|
||
result["critic"] = part[3:]
|
||
return result
|
||
|
||
target = incident.affected_services[0] if incident.affected_services else "unknown"
|
||
risk_level = proposal_data.get("risk_level", "medium")
|
||
# 2026-04-09 Claude Code: action 不用 _strip_placeholders，避免截掉 deployment name
|
||
# <placeholder> 應在 nemotron 補正後已填入真實值
|
||
action = proposal_data.get("action", proposal_data.get("kubectl_command", ""))
|
||
|
||
# 2026-04-09 Claude Code: 修復舊 Incident proposal_data 存 enum string 導致建議空白
|
||
# 舊 code 存 action="RESTART_DEPLOYMENT" 而非 kubectl command
|
||
# 偵測：無 kubectl/ssh/docker 關鍵字 → 用規則引擎重新查
|
||
_KUBECTL_MARKERS = ("kubectl", "ssh", "docker", "systemctl", "/")
|
||
if action and not any(m in action for m in _KUBECTL_MARKERS):
|
||
# action 是 enum string，嘗試用規則引擎補出 kubectl command
|
||
try:
|
||
from src.services.alert_rule_engine import match_rule as _match_rule
|
||
_labels = incident.signals[0].labels if incident.signals else {}
|
||
# 2026-04-12 ogt: Incident 沒有 title 欄位，用 signal annotation summary
|
||
_sig_msg = (
|
||
incident.signals[0].annotations.get("summary", "") or
|
||
incident.signals[0].annotations.get("description", "") or
|
||
incident.signals[0].alert_name
|
||
) if incident.signals else ""
|
||
_rule_resp = _match_rule({
|
||
"labels": _labels,
|
||
"alert_type": _labels.get("alertname", target),
|
||
"message": _sig_msg,
|
||
"target_resource": target,
|
||
"namespace": incident.signals[0].labels.get("namespace", "awoooi-prod") if incident.signals else "awoooi-prod",
|
||
"severity": risk_level,
|
||
})
|
||
if _rule_resp and _rule_resp.get("kubectl_command", "").strip():
|
||
action = _rule_resp["kubectl_command"]
|
||
except Exception:
|
||
pass # 規則引擎失敗不影響通知，保留原 action
|
||
description = proposal_data.get("description", "")
|
||
reasoning = _strip_placeholders(proposal_data.get("reasoning", ""))
|
||
confidence = proposal_data.get("confidence", 0.0) # 🔴 預設 0.0 表示未經 AI 分析
|
||
source = proposal_data.get("source", "unknown")
|
||
ai_provider = proposal_data.get("provider", "") # 2026-03-29 ogt: AI 模型來源
|
||
ai_model = proposal_data.get("model", "") # 2026-04-04 ogt: 底層模型名稱
|
||
|
||
# 2026-04-02 ogt: Phase 22 Nemotron 協作資料
|
||
nemotron_enabled = proposal_data.get("nemotron_enabled", False)
|
||
nemotron_tools = proposal_data.get("nemotron_tools")
|
||
nemotron_validation = proposal_data.get("nemotron_validation", "")
|
||
nemotron_latency_ms = proposal_data.get("nemotron_latency_ms", 0.0)
|
||
# 2026-04-09 Claude Sonnet 4.6: Tool Calling 模型/後端
|
||
nemotron_tool_model = proposal_data.get("nemotron_tool_model", "")
|
||
nemotron_tool_backend = proposal_data.get("nemotron_tool_backend", "")
|
||
# 2026-04-16 ogt + Claude Sonnet 4.6: Playbook 匹配名稱穿透到 TG 卡片 (ADR-076)
|
||
_playbook_name = proposal_data.get("playbook_name", "")
|
||
|
||
# 2026-04-16 ogt + Claude Sonnet 4.6: 覆寫 Webhook 的垃圾 action
|
||
# 問題：Webhook inline LLM 建立 ApprovalRecord 時寫入通用 action（如 kubectl rollout restart）
|
||
# Agent 分析正確但只發新 Telegram 卡，未覆寫 ApprovalRecord.action
|
||
# 用戶批准 Agent 卡 → 系統查 incident_id → 執行舊 webhook 垃圾 action
|
||
# 修復：Agent 確認 action 後立即覆寫 ApprovalRecord（只要有值，空字串不覆寫）
|
||
_agent_action = action # action 已由 _package_to_proposal_data + rule engine 確定
|
||
if not _agent_action and description:
|
||
# NO_ACTION：用描述摘要讓用戶知道 Agent 的建議是「觀察/調查」
|
||
_agent_action = f"NO_ACTION - {description[:120]}"
|
||
if _agent_action:
|
||
try:
|
||
from src.services.approval_db import get_approval_service as _get_approval_svc
|
||
await _get_approval_svc().update_action_by_incident_id(
|
||
incident_id=incident.incident_id,
|
||
new_action=_agent_action,
|
||
)
|
||
except Exception as _update_err:
|
||
logger.warning(
|
||
"approval_action_update_by_agent_failed",
|
||
incident_id=incident.incident_id,
|
||
error=str(_update_err),
|
||
)
|
||
|
||
# 🚨 ADR-091 鐵律 (2026-04-17 ogt + Claude Sonnet 4.6): 禁止分析失敗廣播
|
||
# 問題: GET /incidents 觸發 Agent Debate → LLM 全部失敗 → description="待分析" + action=""
|
||
# → 系統每隔幾分鐘廣播「待分析」喪屍卡片 → 告警疲勞（SRE 最致命的殺手）
|
||
# 規則: description="待分析" + action 屬於失敗狀態集合 = Phase 2 所有 Agent 無有效輸出 → 靜默退出
|
||
# 已完成: DB 狀態已在上方更新 (update_action_by_incident_id)，不需要 Telegram 廣播
|
||
# 禁止改動: 此閘門保護全域告警信噪比，任何「加例外」需首席架構師書面授權
|
||
# 2026-04-17 ogt + Claude Sonnet 4.6 (hotfix): 修復 d5dbfc9 邏輯漏洞
|
||
# 舊 bug: `not action.strip()` 在 action="待分析" 時為 False → 閘門失效 → 喪屍卡片突圍
|
||
# 原因: c759b4e P1 修復讓 suggested_action fallback 為 "待分析"（非空字串）而非 ""
|
||
# 修復: action 必須不在失敗狀態集合才允許廣播
|
||
_action_text = action.strip()
|
||
_FAILED_ACTION_TOKENS = {"", "待分析", "NO_ACTION", "待分析 - 系統自動保護"}
|
||
if description.strip() == "待分析" and _action_text in _FAILED_ACTION_TOKENS:
|
||
logger.info(
|
||
"telegram_push_suppressed_no_analysis",
|
||
incident_id=incident.incident_id,
|
||
action_text=_action_text,
|
||
reason="Agent Debate 無有效輸出 (description=待分析, action 屬於失敗狀態集合)",
|
||
)
|
||
return
|
||
|
||
# 建立 approval_id (使用 incident_id 作為追蹤)
|
||
# 2026-03-27 ogt: 修復 INC-INC-INC- 重複前綴 bug
|
||
approval_id = incident.incident_id # 已經是 INC-xxx 格式
|
||
|
||
# ADR-071: 通知分類器 — 依告警類型/狀態決定卡片種類
|
||
# 2026-04-11 Claude Sonnet 4.6: 接通 classify_notification()，原本死程式碼
|
||
_auto_executed = proposal_data.get("auto_executed", False)
|
||
_decision_state = proposal_data.get("decision_state", "")
|
||
_mcp_all_failed = proposal_data.get("mcp_all_failed", False)
|
||
_notif_type = classify_notification(
|
||
incident=incident,
|
||
confidence=confidence,
|
||
auto_executed=_auto_executed,
|
||
mcp_all_failed=_mcp_all_failed,
|
||
decision_state=_decision_state,
|
||
)
|
||
|
||
# 2026-04-12 ogt: ADR-075 — 從 Incident 提取 alert_category/notification_type（各分支共用）
|
||
_alert_category = getattr(incident, "alert_category", "") or ""
|
||
_notification_type = getattr(incident, "notification_type", "") or (_notif_type.value if _notif_type else "")
|
||
_alertname = incident.signals[0].labels.get("alertname", "MetaSystemAlert") if incident.signals else "MetaSystemAlert"
|
||
|
||
# blocked_reason 由上游「決策路由閘門」統一設定（decide() 第 4c 步）
|
||
# 此處只做狀態轉譯，通知層禁止查詢業務邏輯（架構師鐵律 2026-04-17）
|
||
# ① INVALID_TARGET → TYPE-4：目標無法解析，SRE 需人工調查
|
||
# ② NO_ACTION + critical → TYPE-4：critical 事件不可靜默
|
||
# ③ NO_ACTION + non-critical → TYPE-1：純資訊卡
|
||
_blocked_reason = proposal_data.get("blocked_reason", "")
|
||
if "INVALID_TARGET" in _blocked_reason:
|
||
_notif_type = NotificationType.TYPE_4
|
||
elif "NO_ACTION" in _blocked_reason:
|
||
if risk_level == "critical":
|
||
_notif_type = NotificationType.TYPE_4
|
||
else:
|
||
_notif_type = NotificationType.TYPE_1
|
||
|
||
# 2026-04-12 ogt: classify_alert_early() 設的 notification_type 優先於 classify_notification()
|
||
# 場景：backup/info 告警被 classify_notification() 誤判為 TYPE-3（confidence=0, 無 auto_executed）
|
||
# 規則：incident.notification_type 明確為 TYPE-1 → 強制走 info 路徑
|
||
if _notification_type == "TYPE-1":
|
||
_notif_type = NotificationType.TYPE_1
|
||
elif _notification_type == "TYPE-4D":
|
||
_notif_type = NotificationType.TYPE_4_DRIFT
|
||
elif _notification_type == "TYPE-8M":
|
||
_notif_type = NotificationType.TYPE_8M
|
||
|
||
if _notif_type == NotificationType.TYPE_1:
|
||
# 純資訊通知 — 無按鈕
|
||
# 2026-04-12 ogt: Incident 沒有 title 欄位，用 alertname
|
||
# 2026-04-17 ogt + Claude Sonnet 4.6: BUG-A 修復 — 只取 diagnosis 欄位
|
||
# 舊：message=reasoning[:200] → 整條 debate_summary 生文字傾倒
|
||
# 新：解析 debate_summary，只取「診斷：...」部分給 SRE 看
|
||
_info_title = (
|
||
incident.signals[0].labels.get("alertname", "") or
|
||
incident.signals[0].alert_name
|
||
) if incident.signals else "告警通知"
|
||
_parsed_info = _parse_debate_summary(reasoning)
|
||
_info_msg = _smt(_parsed_info.get("diagnosis") or description, 200)
|
||
tg_result = await gateway.send_info_notification(
|
||
incident_id=incident.incident_id,
|
||
title=_info_title or "告警通知",
|
||
message=_info_msg,
|
||
alertname=incident.signals[0].labels.get("alertname", "") if incident.signals else "",
|
||
severity="info",
|
||
)
|
||
elif _notif_type == NotificationType.TYPE_4_DRIFT:
|
||
# Config Drift 專屬卡片
|
||
# 2026-04-17 ogt + Claude Sonnet 4.6: BUG-B JSON Catcher
|
||
# LLM 可能輸出 JSON 結構（{"action_title":"...","description":"...","rollback":"..."}）
|
||
# 解析成功 → 格式化可讀文字；失敗 → 平滑降級為原始截斷字串（不可拋出 Exception）
|
||
try:
|
||
_drift_data = json.loads(description)
|
||
_parts: list[str] = []
|
||
if _drift_data.get("action_title"):
|
||
_parts.append(f"📝 建議操作：{_drift_data['action_title']}")
|
||
if _drift_data.get("description"):
|
||
_parts.append(f"📖 說明：{_smt(_drift_data['description'], 200)}")
|
||
if _drift_data.get("rollback"):
|
||
_parts.append(f"⏪ 回滾方案：{_smt(_drift_data['rollback'], 100)}")
|
||
_diff_text = "\n".join(_parts) if _parts else description[:500]
|
||
except (json.JSONDecodeError, TypeError, AttributeError):
|
||
_diff_text = description[:500]
|
||
tg_result = await gateway.send_drift_card(
|
||
incident_id=incident.incident_id,
|
||
approval_id=approval_id,
|
||
resource_name=target[:50],
|
||
diff_summary=_diff_text,
|
||
)
|
||
elif _notif_type == NotificationType.TYPE_8M or _alert_category in ("alertchain_health", "flywheel_health"):
|
||
# TYPE-8M：飛輪/告警鏈路健康異常，發到個人 DM（不發群組）
|
||
# 2026-04-17 ogt + Claude Sonnet 4.6: 解析 debate_summary，各欄位用不同組件
|
||
# 根因：diagnosis/system_impact/probable_cause 全取 reasoning[:100] → 三欄重複同一段字
|
||
_parsed = _parse_debate_summary(reasoning)
|
||
_diag = _smt(_parsed.get("diagnosis") or description, 120) if (_parsed.get("diagnosis") or description) else "（無診斷）"
|
||
_impact = _smt(_parsed.get("plan") or "", 150)
|
||
_cause = _smt(_parsed.get("critic") or _parsed.get("review") or "", 100)
|
||
tg_result = await gateway.send_meta_alert(
|
||
incident_id=incident.incident_id,
|
||
approval_id=approval_id,
|
||
alertname=_alertname,
|
||
alert_category=_alert_category,
|
||
diagnosis=_diag,
|
||
severity_level=risk_level,
|
||
system_impact=_impact,
|
||
probable_cause=_cause,
|
||
)
|
||
elif _alert_category == "secops":
|
||
# TYPE-5S：資安事件 — 隔離/封鎖審核卡，發到個人 DM (ADR-075 Step-5)
|
||
# 2026-04-12 ogt (ADR-075 Step-5)
|
||
_labels = incident.signals[0].labels if incident.signals else {}
|
||
_threat_level = _labels.get("threat_level", risk_level)
|
||
tg_result = await gateway.send_secops_card(
|
||
incident_id=incident.incident_id,
|
||
approval_id=approval_id,
|
||
alertname=_alertname,
|
||
threat_level=_threat_level,
|
||
resource=target[:60],
|
||
threat_behavior=_smt(_parse_debate_summary(reasoning).get("diagnosis") or reasoning, 150) if reasoning else description[:150],
|
||
)
|
||
elif _alert_category == "business":
|
||
# TYPE-6B：業務/FinOps 資訊告警 — 發到 SRE 群組（無審核按鈕）(ADR-075 Step-5)
|
||
# 2026-04-12 ogt (ADR-075 Step-5)
|
||
_labels = incident.signals[0].labels if incident.signals else {}
|
||
_business_domain = _labels.get("business_domain", "finops")
|
||
tg_result = await gateway.send_business_alert(
|
||
incident_id=incident.incident_id,
|
||
alertname=_alertname,
|
||
business_domain=_business_domain,
|
||
metric_name=_labels.get("metric_name", _alertname),
|
||
current_value=_labels.get("value", "--"),
|
||
threshold=_labels.get("threshold", "--"),
|
||
)
|
||
else:
|
||
# TYPE-2 / TYPE-3 / TYPE-4 都走 send_approval_card（按鈕組合由 alert_category 決定）
|
||
# 2026-04-17 ogt + Claude Sonnet 4.6 (BUG-C): TYPE-3 root_cause 清洗
|
||
# 舊：root_cause=_smt(reasoning, 500) → debate_summary 全文傾倒到 AI 診斷欄位
|
||
# 新：_parse_debate_summary 只取 diagnosis；方案/審查/質疑不在此卡顯示
|
||
_parsed_card = _parse_debate_summary(reasoning)
|
||
_card_root_cause = _smt(_parsed_card.get("diagnosis") or description, 300)
|
||
tg_result = await gateway.send_approval_card(
|
||
approval_id=approval_id,
|
||
risk_level=risk_level,
|
||
resource_name=target[:50],
|
||
root_cause=_card_root_cause,
|
||
# 2026-04-17 ogt + Claude Sonnet 4.6（亞太）: 修復超時降級髒資料
|
||
# 舊：action="" 時 fallback 到 description，而 description 可能是「待分析」或診斷摘要
|
||
# 這導致 description 中的診斷文字（如「根因：...」）出現在「建議修復動作」欄位
|
||
# 新：action="" 時固定顯示「待分析」，禁止 description 流進 suggested_action
|
||
suggested_action=action[:120] if action else "待分析",
|
||
estimated_downtime="5-15 min",
|
||
primary_responsibility="INFRA",
|
||
confidence=confidence,
|
||
namespace=incident.signals[0].labels.get("namespace", "default") if incident.signals else "default",
|
||
ai_provider=ai_provider,
|
||
ai_model=ai_model,
|
||
nemotron_enabled=nemotron_enabled,
|
||
nemotron_tools=nemotron_tools,
|
||
nemotron_validation=nemotron_validation,
|
||
nemotron_latency_ms=nemotron_latency_ms,
|
||
nemotron_tool_model=nemotron_tool_model,
|
||
nemotron_tool_backend=nemotron_tool_backend,
|
||
incident_id=incident.incident_id,
|
||
alert_category=_alert_category,
|
||
notification_type=_notification_type,
|
||
playbook_name=_playbook_name,
|
||
)
|
||
|
||
# 2026-04-09 Claude Sonnet 4.6: 存 message_id → 後續狀態更新在原訊息延續
|
||
# 同時寫 Redis (快速查詢) 和 DB (持久化，不受 TTL 限制)
|
||
tg_message_id = tg_result.get("result", {}).get("message_id") if isinstance(tg_result, dict) else None
|
||
tg_chat_id = tg_result.get("result", {}).get("chat", {}).get("id") if isinstance(tg_result, dict) else None
|
||
if tg_message_id:
|
||
await redis.setex(f"tg_msg:{incident.incident_id}", 86400, str(tg_message_id))
|
||
# 持久化到 DB
|
||
try:
|
||
from src.services.approval_db import get_approval_service as _get_approval_svc
|
||
_approval_svc = _get_approval_svc()
|
||
await _approval_svc.update_telegram_message(
|
||
incident_id=incident.incident_id,
|
||
telegram_message_id=tg_message_id,
|
||
telegram_chat_id=tg_chat_id,
|
||
)
|
||
except Exception as _e:
|
||
logger.warning("telegram_message_id_db_save_failed", incident_id=incident.incident_id, error=str(_e))
|
||
|
||
# Phase 31 (ADR-067 2026-04-10): Log 異常摘要 — NemoTron deepseek-r1:14b
|
||
# 非同步執行，不阻塞主流程
|
||
_fire_and_forget(_send_log_summary(incident))
|
||
|
||
# MCP Phase 4a: NemoClaw second opinion (2026-04-11 Claude Sonnet 4.6)
|
||
# 若 proposal_data 有 advisory_note，用 NemoClaw bot 身分追加一條訊息
|
||
_advisory_note = proposal_data.get("advisory_note", "")
|
||
if _advisory_note:
|
||
_fire_and_forget(
|
||
gateway.send_as_nemotron(
|
||
f"🤔 <b>NemoClaw 第二意見</b> (信心={confidence:.2f})\n"
|
||
f"<i>{_advisory_note}</i>"
|
||
)
|
||
)
|
||
|
||
# 🔴 發送成功後設置去重 key (TTL 10 分鐘)
|
||
await redis.setex(dedup_key, 600, "1")
|
||
|
||
logger.info(
|
||
"telegram_decision_pushed",
|
||
incident_id=incident.incident_id,
|
||
source=source,
|
||
risk_level=risk_level,
|
||
)
|
||
|
||
except Exception as e:
|
||
# Telegram 失敗不影響主流程
|
||
logger.warning(
|
||
"telegram_decision_push_failed",
|
||
incident_id=incident.incident_id,
|
||
error=str(e),
|
||
)
|
||
|
||
|
||
async def _nemoclaw_second_opinion(incident: "Incident", primary_result: dict) -> str | None:
|
||
"""
|
||
MCP Phase 4a: NemoClaw second opinion — 信心 < 0.7 時觸發
|
||
============================================================
|
||
用 deepseek-r1:14b (Ollama 188) 對同一份資料做獨立推理，
|
||
輸出純文字 advisory_note，不執行任何操作。
|
||
|
||
2026-04-11 Claude Sonnet 4.6 Asia/Taipei
|
||
"""
|
||
try:
|
||
from src.core.config import settings
|
||
import httpx as _httpx
|
||
|
||
from src.services.model_registry import get_model as _get_model
|
||
ollama_url = getattr(settings, "OLLAMA_URL", "http://192.168.0.111:11434")
|
||
# D1 集中化 2026-04-11: 從 models.json providers.ollama.models.nemoclaw 讀取
|
||
model = _get_model("ollama", "nemoclaw")
|
||
|
||
signals_summary = ""
|
||
if incident.signals:
|
||
lbl = incident.signals[0].labels
|
||
signals_summary = (
|
||
f"alertname={lbl.get('alertname','?')} "
|
||
f"severity={lbl.get('severity','?')} "
|
||
f"instance={lbl.get('instance','?')}"
|
||
)
|
||
|
||
prompt = (
|
||
f"你是資深 SRE，請對以下告警做獨立分析並提出建議。\n"
|
||
f"告警摘要: {signals_summary}\n"
|
||
f"受影響服務: {', '.join(incident.affected_services or [])}\n"
|
||
f"主 AI 已提出: {primary_result.get('action','?')} "
|
||
f"(信心={primary_result.get('confidence',0):.2f})\n"
|
||
f"主 AI 根因: {primary_result.get('reasoning','')[:200]}\n\n"
|
||
f"請用繁體中文，100 字以內，給出你的獨立判斷與建議（若同意主 AI 則說明原因）。"
|
||
)
|
||
|
||
async with _httpx.AsyncClient(timeout=30.0) as client:
|
||
resp = await client.post(
|
||
f"{ollama_url}/api/generate",
|
||
json={"model": model, "prompt": prompt, "stream": False},
|
||
)
|
||
resp.raise_for_status()
|
||
data = resp.json()
|
||
|
||
advisory = data.get("response", "").strip()
|
||
# 截取 <think>...</think> 後的正文（deepseek-r1 CoT 格式）
|
||
if "</think>" in advisory:
|
||
advisory = advisory.split("</think>", 1)[-1].strip()
|
||
|
||
return advisory[:300] if advisory else None
|
||
|
||
except Exception as e:
|
||
import structlog as _sl
|
||
_sl.get_logger(__name__).debug("nemoclaw_second_opinion_error", error=str(e))
|
||
return None
|
||
|
||
|
||
async def _generate_playbook_draft_if_new(incident: "Incident") -> None:
|
||
"""
|
||
MCP Phase 4c: Playbook 無命中時，自動生成 AI 草稿 Playbook 寫入 KM
|
||
=====================================================================
|
||
- 僅在 KM 中不存在同 alertname 的 Playbook 時觸發（避免重複）
|
||
- 用 qwen2.5:7b-instruct (Ollama 188) 生成結構化 Playbook 草稿
|
||
- 寫入 KnowledgeEntry，status=DRAFT，需人工審核後升為 APPROVED
|
||
- 寫入 AlertOperationLog PLAYBOOK_DRAFT_CREATED 事件
|
||
|
||
2026-04-11 Claude Sonnet 4.6 Asia/Taipei
|
||
"""
|
||
try:
|
||
import httpx as _httpx
|
||
from src.core.config import settings
|
||
from src.models.knowledge import (
|
||
EntrySource, EntryStatus, EntryType, KnowledgeEntryCreate,
|
||
)
|
||
from src.repositories.alert_operation_log_repository import get_alert_operation_log_repository
|
||
from src.services.knowledge_service import get_knowledge_service
|
||
|
||
alertname = ""
|
||
if incident.signals:
|
||
alertname = incident.signals[0].labels.get("alertname", "")
|
||
if not alertname:
|
||
return
|
||
|
||
# 已存在同 alertname 的 KM 條目則跳過
|
||
knowledge_svc = get_knowledge_service()
|
||
existing = await knowledge_svc.semantic_search(alertname, limit=1, threshold=0.92)
|
||
if existing:
|
||
return
|
||
|
||
# 用 qwen2.5:7b-instruct 生成 Playbook 草稿
|
||
severity = incident.signals[0].labels.get("severity", "warning") if incident.signals else "warning"
|
||
services = ", ".join(incident.affected_services or ["unknown"])
|
||
prompt = (
|
||
f"你是資深 SRE，請為以下告警生成一份結構化 Playbook 草稿（繁體中文）。\n"
|
||
f"告警名稱: {alertname}\n"
|
||
f"嚴重度: {severity}\n"
|
||
f"受影響服務: {services}\n\n"
|
||
f"請按以下格式輸出（不超過 300 字）:\n"
|
||
f"## 症狀\n（描述此告警代表什麼）\n"
|
||
f"## 根因假設\n（最常見的 2-3 個原因）\n"
|
||
f"## 診斷步驟\n（kubectl 或 shell 指令）\n"
|
||
f"## 修復動作\n（具體修復指令，含 kubectl rollout restart 等）\n"
|
||
f"## 驗收條件\n（如何確認修復成功）"
|
||
)
|
||
|
||
from src.services.model_registry import get_model as _get_model
|
||
ollama_url = getattr(settings, "OLLAMA_URL", "http://192.168.0.111:11434")
|
||
# D1 集中化 2026-04-11: 從 models.json providers.ollama.models.playbook_draft 讀取
|
||
_pb_model = _get_model("ollama", "playbook_draft")
|
||
async with _httpx.AsyncClient(timeout=45.0) as client:
|
||
resp = await client.post(
|
||
f"{ollama_url}/api/generate",
|
||
json={"model": _pb_model, "prompt": prompt, "stream": False},
|
||
)
|
||
resp.raise_for_status()
|
||
content = resp.json().get("response", "").strip()
|
||
|
||
if not content or len(content) < 50:
|
||
return
|
||
|
||
# 寫入 KM，status=DRAFT
|
||
entry = await knowledge_svc.create_entry(
|
||
KnowledgeEntryCreate(
|
||
title=f"[AI草稿] {alertname} Playbook",
|
||
content=content,
|
||
entry_type=EntryType.AUTO_RUNBOOK,
|
||
category="ai_system",
|
||
tags=[alertname, severity, "ai_draft", "mcp_phase4c"],
|
||
source=EntrySource.AI_EXTRACTED,
|
||
status=EntryStatus.DRAFT,
|
||
related_incident_id=incident.incident_id,
|
||
)
|
||
)
|
||
|
||
# 寫入操作日誌
|
||
op_repo = get_alert_operation_log_repository()
|
||
await op_repo.append(
|
||
event_type="PLAYBOOK_DRAFT_CREATED",
|
||
incident_id=incident.incident_id,
|
||
actor="mcp_phase4c",
|
||
action_detail=f"AI 草稿 Playbook: {entry.entry_id}",
|
||
success=True,
|
||
context={"alertname": alertname, "km_entry_id": entry.entry_id},
|
||
)
|
||
|
||
import structlog as _sl
|
||
_sl.get_logger(__name__).info(
|
||
"playbook_draft_created",
|
||
incident_id=incident.incident_id,
|
||
alertname=alertname,
|
||
entry_id=entry.entry_id,
|
||
)
|
||
|
||
# 2026-04-16 ogt + Claude Sonnet 4.6: KM 建立後推 Telegram 通知 (ADR-076)
|
||
# best-effort — 不阻塞主流程
|
||
try:
|
||
from src.services.telegram_gateway import get_telegram_gateway as _get_tg
|
||
_tg = _get_tg()
|
||
await _tg.send_as_nemotron(
|
||
f"📚 <b>KM 新條目</b> — <code>{entry.entry_id}</code>\n"
|
||
f"🏷️ 分類：<b>auto_generated</b> 狀態：DRAFT\n"
|
||
f"📋 告警：<code>{alertname}</code> 事件：<code>{incident.incident_id}</code>\n"
|
||
f"標題：{str(getattr(entry, 'title', alertname))[:60]}"
|
||
)
|
||
except Exception as _tg_err:
|
||
_sl.get_logger(__name__).debug("km_tg_notify_failed", error=str(_tg_err))
|
||
|
||
except Exception as e:
|
||
import structlog as _sl
|
||
_sl.get_logger(__name__).debug("playbook_draft_failed", error=str(e))
|
||
|
||
|
||
async def _resolve_target_from_k8s(incident: "Incident", namespace: str) -> str | None:
|
||
"""
|
||
BUG-002 補救：主機層告警無 component/job/pod label 時，
|
||
用 K8s MCP kubectl get pods 依 alertname/host label 動態查詢受影響 Pod name，
|
||
回傳 deployment name（去掉 hash suffix）或 None。
|
||
|
||
2026-04-11 Claude Sonnet 4.6 Asia/Taipei
|
||
"""
|
||
try:
|
||
from src.plugins.mcp.providers.k8s_provider import K8sProvider
|
||
|
||
k8s = K8sProvider()
|
||
if not k8s.enabled:
|
||
return None
|
||
|
||
alertname = ""
|
||
if incident.signals:
|
||
labels = incident.signals[0].labels
|
||
alertname = labels.get("alertname", "")
|
||
|
||
# 用 kubectl get pods 列出所有 pods，再根據 alertname 推測受影響的 deployment
|
||
result = await k8s.execute(
|
||
tool_name="kubectl_get",
|
||
params={"resource": "pods", "namespace": namespace, "output": "name"},
|
||
)
|
||
if not result.get("success"):
|
||
return None
|
||
|
||
pod_lines: list[str] = (result.get("output", "") or "").splitlines()
|
||
if not pod_lines:
|
||
return None
|
||
|
||
# alertname → 關鍵字映射（主機層告警常見類型）
|
||
# I2 修復 2026-04-11: HostHighDiskUsage → HostOutOfDiskSpace（與 alerts-unified.yml 一致）
|
||
# DockerContainerUnhealthy/HostOutOfDiskSpace keywords=[] 走 fallback（找第一個非 infra pod）
|
||
# 並加 log 便於追蹤 fallback 路徑
|
||
_ALERTNAME_KEYWORDS: dict[str, list[str]] = {
|
||
"HostHighCpuLoad": ["api", "web"],
|
||
"HostOutOfMemory": ["api", "web"],
|
||
"DockerContainerUnhealthy": [],
|
||
"DockerContainerExited": [],
|
||
"HostOutOfDiskSpace": [],
|
||
}
|
||
keywords = _ALERTNAME_KEYWORDS.get(alertname, [])
|
||
if not keywords and alertname in _ALERTNAME_KEYWORDS:
|
||
logger.debug(
|
||
"resolve_target_k8s_fallback_to_first_pod",
|
||
alertname=alertname,
|
||
reason="alertname 有對應但 keywords=[]，走 fallback 取第一個非 infra pod",
|
||
)
|
||
|
||
import re as _re
|
||
for line in pod_lines:
|
||
pod = line.removeprefix("pod/").strip()
|
||
if not pod:
|
||
continue
|
||
# 優先找關鍵字命中的 pod
|
||
if keywords and not any(kw in pod for kw in keywords):
|
||
continue
|
||
# 去掉 hash suffix → deployment name
|
||
parts = pod.rsplit("-", 2)
|
||
if len(parts) >= 3 and len(parts[-1]) == 5 and len(parts[-2]) in (9, 10):
|
||
return parts[0]
|
||
if len(parts) >= 2:
|
||
return "-".join(parts[:-1])
|
||
return pod
|
||
|
||
# 無關鍵字命中時，回傳第一個 non-infra pod
|
||
for line in pod_lines:
|
||
pod = line.removeprefix("pod/").strip()
|
||
if pod and not any(inf in pod for inf in ("prometheus", "alertmanager", "grafana")):
|
||
parts = pod.rsplit("-", 2)
|
||
if len(parts) >= 3:
|
||
return parts[0]
|
||
return pod
|
||
|
||
except Exception as e:
|
||
logger.debug("resolve_target_from_k8s_failed", error=str(e))
|
||
|
||
return None
|
||
|
||
|
||
async def _verify_k8s_deployment_exists(target: str, namespace: str, alertname: str = "") -> bool:
|
||
"""
|
||
BUG-003 補救：呼叫 K8s MCP 確認 deployment/pod 是否真實存在。
|
||
K8s MCP 不可用時：
|
||
- 主機層告警 (Host*/Docker*) → 返回 False（阻止 K8s 操作）
|
||
- K8s 層告警 → 返回 True（保守放行，讓 kubectl 自行報錯）
|
||
|
||
2026-04-11 Claude Sonnet 4.6 Asia/Taipei
|
||
"""
|
||
# 主機層告警前綴 — 這類告警的修復目標是 Docker container/主機，不是 K8s deployment
|
||
_HOST_ALERTNAME_PREFIXES = ("Host", "Docker", "Backup", "Velero", "SSH")
|
||
_is_host_alert = alertname.startswith(_HOST_ALERTNAME_PREFIXES) if alertname else False
|
||
|
||
try:
|
||
from src.plugins.mcp.providers.k8s_provider import K8sProvider
|
||
|
||
k8s = K8sProvider()
|
||
if not k8s.enabled:
|
||
# 主機層告警：K8s MCP 不可用 → 拒絕（不應對主機層問題執行 K8s 操作）
|
||
# K8s 層告警：保守放行，讓 kubectl 自行報錯
|
||
return not _is_host_alert
|
||
|
||
result = await k8s.execute(
|
||
tool_name="kubectl_get",
|
||
params={"resource": "deployment", "name": target, "namespace": namespace},
|
||
)
|
||
if result.get("success"):
|
||
return True
|
||
|
||
# 嘗試 pod（有些告警對應的是 pod 而非 deployment）
|
||
result_pod = await k8s.execute(
|
||
tool_name="kubectl_get",
|
||
params={"resource": "pod", "namespace": namespace, "selector": f"app={target}"},
|
||
)
|
||
return bool(result_pod.get("success") and result_pod.get("output", "").strip())
|
||
|
||
except Exception as e:
|
||
logger.debug("verify_k8s_deployment_exists_failed", target=target, error=str(e))
|
||
# 例外時：主機層告警拒絕，其他保守放行
|
||
return not _is_host_alert
|
||
|
||
|
||
async def _fetch_metrics_snapshot(incident: Incident) -> dict:
|
||
"""
|
||
ADR-071-I: 從 Prometheus 抓取與此 incident 相關的指標快照
|
||
失敗時靜默返回空 dict，不阻塞主流程
|
||
|
||
2026-04-11 Claude Sonnet 4.6 Asia/Taipei
|
||
"""
|
||
try:
|
||
from src.plugins.mcp.providers.prometheus_provider import PrometheusProvider
|
||
prom = PrometheusProvider()
|
||
if not prom.enabled:
|
||
return {}
|
||
|
||
labels = incident.signals[0].labels if incident.signals else {}
|
||
alertname = labels.get("alertname", "")
|
||
instance = labels.get("instance", "")
|
||
snapshots: dict = {}
|
||
|
||
# 根據 alertname 選擇最相關的指標
|
||
if alertname in ("HostHighCpuLoad", "HostOutOfMemory"):
|
||
if instance:
|
||
host = instance.split(":")[0]
|
||
# P0 fix 2026-04-11: _instant_query 要求 dict，回傳 {"result": [...]}
|
||
r = await prom._instant_query({"query": f'100 - (avg by(instance) (irate(node_cpu_seconds_total{{mode="idle",instance=~"{host}.*"}}[5m])) * 100)'})
|
||
for item in r.get("result", []):
|
||
snapshots["cpu_pct"] = round(float(item["value"][1]), 1)
|
||
cpu_query = (
|
||
f'(1 - (node_memory_MemAvailable_bytes{{instance=~"{instance}"}} / node_memory_MemTotal_bytes{{instance=~"{instance}"}})) * 100'
|
||
if instance else "100 * (1 - node_memory_MemAvailable_bytes / node_memory_MemTotal_bytes)"
|
||
)
|
||
r2 = await prom._instant_query({"query": cpu_query})
|
||
for item in r2.get("result", []):
|
||
snapshots["mem_pct"] = round(float(item["value"][1]), 1)
|
||
|
||
elif alertname == "HostOutOfDiskSpace":
|
||
r = await prom._instant_query({"query": 'max(100 - ((node_filesystem_avail_bytes{fstype!="tmpfs"} / node_filesystem_size_bytes{fstype!="tmpfs"}) * 100))'})
|
||
for item in r.get("result", []):
|
||
snapshots["disk_pct"] = round(float(item["value"][1]), 1)
|
||
|
||
elif alertname in ("PodRestartingTooMuch", "PodCrashLoopBackOff"):
|
||
pod = labels.get("pod", labels.get("component", ""))
|
||
if pod:
|
||
r = await prom._instant_query({"query": f'sum(kube_pod_container_status_restarts_total{{namespace="awoooi-prod",pod=~"{pod}.*"}})'})
|
||
for item in r.get("result", []):
|
||
snapshots["restart_count"] = int(float(item["value"][1]))
|
||
|
||
return snapshots
|
||
except Exception as _e:
|
||
logger.debug("metrics_snapshot_failed", incident_id=incident.incident_id, error=str(_e))
|
||
return {}
|
||
|
||
|
||
def _format_metrics_delta(before: dict, after: dict) -> str:
|
||
"""
|
||
ADR-071-I: 格式化指標前後對比文字
|
||
例：CPU 92%→23% | Mem 78%→45%
|
||
"""
|
||
if not before and not after:
|
||
return ""
|
||
parts = []
|
||
for key, label in [("cpu_pct", "CPU"), ("mem_pct", "Mem"), ("disk_pct", "Disk")]:
|
||
b = before.get(key)
|
||
a = after.get(key)
|
||
if b is not None and a is not None:
|
||
parts.append(f"{label} {b}%→{a}%")
|
||
elif b is not None:
|
||
parts.append(f"{label} {b}% (before)")
|
||
elif a is not None:
|
||
parts.append(f"{label} {a}% (after)")
|
||
for key, label in [("restart_count", "Restarts")]:
|
||
b = before.get(key)
|
||
a = after.get(key)
|
||
if b is not None and a is not None:
|
||
parts.append(f"{label} {b}→{a}")
|
||
return " | ".join(parts)
|
||
|
||
|
||
async def _push_auto_repair_result(
|
||
incident: Incident,
|
||
action: str,
|
||
success: bool,
|
||
error: str = "",
|
||
) -> None:
|
||
"""
|
||
自動修復執行後，在原始告警訊息追加狀態行。
|
||
統帥要求: 所有狀態變更必須在原告警訊息延續，不發新訊息。
|
||
- append_incident_update() 取 Redis tg_msg:{id} → reply 原訊息 + 換按鈕
|
||
- 找不到 message_id 時 fallback 到 send_notification（降級）
|
||
|
||
ADR-071-I: 成功時抓 metrics_after 快照，寫入 incidents 表，並在通知中顯示前後對比
|
||
2026-04-09 Claude Sonnet 4.6 Asia/Taipei
|
||
2026-04-11 Claude Sonnet 4.6: +ADR-071-I 指標快照
|
||
"""
|
||
try:
|
||
from src.services.telegram_gateway import get_telegram_gateway
|
||
|
||
gateway = get_telegram_gateway()
|
||
target = incident.affected_services[0] if incident.affected_services else "unknown"
|
||
inc_id = incident.incident_id
|
||
|
||
# ADR-071-I: 抓 metrics_after（成功時）
|
||
metrics_delta_text = ""
|
||
if success:
|
||
metrics_after = await _fetch_metrics_snapshot(incident)
|
||
metrics_before = getattr(incident, "metrics_before", None) or {}
|
||
|
||
# 寫入 DB（不阻塞主流程）
|
||
if metrics_after:
|
||
try:
|
||
from src.db.base import get_db_context
|
||
from src.db.models import Incident as IncidentORM
|
||
from sqlalchemy import update as _update
|
||
async with get_db_context() as db:
|
||
await db.execute(
|
||
_update(IncidentORM)
|
||
.where(IncidentORM.incident_id == inc_id)
|
||
.values(metrics_after=metrics_after)
|
||
)
|
||
await db.commit()
|
||
logger.info("metrics_after_saved", incident_id=inc_id, metrics=metrics_after)
|
||
except Exception as _e:
|
||
logger.warning("metrics_after_save_failed", incident_id=inc_id, error=str(_e))
|
||
|
||
metrics_delta_text = _format_metrics_delta(metrics_before, metrics_after)
|
||
|
||
# MCP Phase 4b: 抓 K8s Pod 狀態寫入 k8s_state_after (2026-04-11 Claude Sonnet 4.6)
|
||
try:
|
||
from src.plugins.mcp.providers.k8s_provider import K8sProvider
|
||
_k8s = K8sProvider()
|
||
if _k8s.enabled:
|
||
_service = (incident.affected_services or [""])[0]
|
||
if _service:
|
||
_k8s_result = await _k8s.execute(
|
||
"kubectl_get",
|
||
{"resource_type": "pods", "namespace": "awoooi-prod",
|
||
"label_selector": f"app={_service}"},
|
||
)
|
||
if _k8s_result.success and _k8s_result.data:
|
||
_k8s_state = str(_k8s_result.data)[:500]
|
||
from src.db.base import get_db_context
|
||
from src.db.models import Incident as IncidentORM
|
||
from sqlalchemy import update as _upd2
|
||
async with get_db_context() as _db2:
|
||
await _db2.execute(
|
||
_upd2(IncidentORM)
|
||
.where(IncidentORM.incident_id == inc_id)
|
||
.values(k8s_state_after=_k8s_state)
|
||
)
|
||
await _db2.commit()
|
||
except Exception as _k8s_err:
|
||
logger.debug("k8s_state_after_failed", incident_id=inc_id, error=str(_k8s_err))
|
||
|
||
if success:
|
||
delta_line = f"\n├ 指標: <code>{metrics_delta_text}</code>" if metrics_delta_text else ""
|
||
status_line = (
|
||
f"✅ <b>自動修復完成</b>\n"
|
||
f"├ <code>{action[:100] if action else '已執行'}</code>"
|
||
f"{delta_line}"
|
||
)
|
||
else:
|
||
status_line = (
|
||
f"❌ <b>自動修復失敗，請人工介入</b>\n"
|
||
f"├ 動作: <code>{action[:80] if action else '未知'}</code>\n"
|
||
f"└ 錯誤: {error[:100] if error else '未知錯誤'}"
|
||
)
|
||
|
||
# BUG-006 修復 2026-04-11: outcome + verification_result 全為 null
|
||
# 原因：_push_auto_repair_result 只送 Telegram，沒寫 DB
|
||
# 修復：寫入 incidents 表 outcome/verification_result 欄位
|
||
try:
|
||
from src.db.base import get_db_context
|
||
from src.db.models import IncidentRecord
|
||
from sqlalchemy import update as _upd_outcome
|
||
_outcome = "auto_repaired" if success else "auto_repair_failed"
|
||
async with get_db_context() as _odb:
|
||
await _odb.execute(
|
||
_upd_outcome(IncidentRecord)
|
||
.where(IncidentRecord.incident_id == inc_id)
|
||
.values(outcome=_outcome)
|
||
)
|
||
await _odb.commit()
|
||
logger.info("outcome_written", incident_id=inc_id, outcome=_outcome)
|
||
except Exception as _oe:
|
||
logger.warning("outcome_write_failed", incident_id=inc_id, error=str(_oe))
|
||
|
||
# 優先: reply 原告警訊息並換掉按鈕
|
||
appended = await gateway.append_incident_update(
|
||
incident_id=inc_id,
|
||
status_line=status_line,
|
||
keep_info_buttons=True, # 保留詳情/重診/歷史，移除批准/拒絕
|
||
)
|
||
|
||
# Fallback: 找不到原訊息 ID（舊告警或 Redis 過期）→ 發新訊息
|
||
# 2026-04-15 ogt: 改為 ADR-075 TYPE-2 格式（禁止 raw text）
|
||
if not appended:
|
||
result_icon = "✅" if success else "❌"
|
||
result_label = "完成" if success else "失敗"
|
||
fallback_text = (
|
||
f"{result_icon} <b>TYPE-2 | 自動修復{result_label}</b>\n"
|
||
"──────────────────────\n"
|
||
f"├─ 事件: <code>{inc_id}</code>\n"
|
||
f"├─ 對象: <code>{target[:50]}</code>\n"
|
||
f"└─ {status_line}"
|
||
)
|
||
await gateway.send_notification(fallback_text)
|
||
|
||
logger.info("auto_repair_result_sent", incident_id=inc_id, success=success, appended=appended)
|
||
|
||
except Exception as e:
|
||
logger.warning("auto_repair_result_push_failed", incident_id=incident.incident_id, error=str(e))
|
||
|
||
|
||
# =============================================================================
|
||
# Decision States
|
||
# =============================================================================
|
||
|
||
class DecisionState(str, Enum):
|
||
"""決策狀態機"""
|
||
INIT = "init" # 事件剛建立
|
||
ANALYZING = "analyzing" # 正在分析
|
||
READY = "ready" # 決策就緒
|
||
EXECUTING = "executing" # 正在執行
|
||
COMPLETED = "completed" # 已完成
|
||
ERROR = "error" # 錯誤
|
||
|
||
|
||
# =============================================================================
|
||
# Expert System - 規則引擎 (Local Fallback)
|
||
# =============================================================================
|
||
|
||
EXPERT_RULES: dict[str, dict[str, Any]] = {
|
||
# Pod 崩潰 → 重啟
|
||
"pod_crash": {
|
||
"patterns": ["crash", "restart", "oom", "killed", "failed"],
|
||
"action": "kubectl rollout restart deployment/{target}",
|
||
"description": "Expert System: 偵測到 Pod 異常，建議重啟部署",
|
||
"risk_level": "medium",
|
||
"reasoning": "根據歷史數據，重啟可解決 85% 的 Pod 崩潰問題",
|
||
},
|
||
# 高延遲 → 擴容
|
||
"high_latency": {
|
||
"patterns": ["latency", "slow", "timeout", "p99"],
|
||
"action": "kubectl scale deployment/{target} --replicas=3",
|
||
"description": "Expert System: 偵測到高延遲，建議擴容至 3 副本",
|
||
"risk_level": "low",
|
||
"reasoning": "擴容可分散負載，降低單一 Pod 壓力",
|
||
},
|
||
# 高錯誤率 → 回滾
|
||
"high_error_rate": {
|
||
"patterns": ["error", "5xx", "fail", "exception"],
|
||
"action": "kubectl rollout undo deployment/{target}",
|
||
"description": "Expert System: 偵測到高錯誤率，建議回滾至上一版",
|
||
"risk_level": "critical",
|
||
"reasoning": "錯誤率突增通常源自最近部署，回滾是最快修復方式",
|
||
},
|
||
# 資源耗盡 → 擴容
|
||
"resource_exhaustion": {
|
||
"patterns": ["cpu", "memory", "resource", "quota"],
|
||
"action": "kubectl scale deployment/{target} --replicas=2",
|
||
"description": "Expert System: 偵測到資源耗盡，建議擴容",
|
||
"risk_level": "medium",
|
||
"reasoning": "增加副本可分散資源壓力",
|
||
},
|
||
# 預設 → 重啟 (最保守)
|
||
"default": {
|
||
"patterns": [],
|
||
"action": "kubectl rollout restart deployment/{target}",
|
||
"description": "Expert System: 無法確定具體問題，建議安全重啟",
|
||
"risk_level": "medium",
|
||
"reasoning": "重啟是最安全的通用修復動作",
|
||
},
|
||
}
|
||
|
||
|
||
def _package_to_proposal_data(package: Any) -> dict[str, Any]:
|
||
"""
|
||
將 Phase 2 DecisionPackage 轉換為 proposal_data dict。
|
||
|
||
proposal_data 格式是既有 decision_manager 決策流程的共同語言，
|
||
所有下游（auto_approve / Telegram / approval_record）都依此格式讀取。
|
||
|
||
ADR-082: Phase 2 多 Agent 協作
|
||
2026-04-15 ogt + Claude Sonnet 4.6（亞太）
|
||
"""
|
||
action = package.recommended_action or ""
|
||
confidence = package.confidence
|
||
|
||
# requires_human_approval → risk_level 映射
|
||
# Phase 2 Reviewer + Critic 已做安全審查，不需要 human = low/medium
|
||
if package.requires_human_approval:
|
||
risk_level = "high" if confidence > 0 else "critical"
|
||
elif confidence >= 0.8:
|
||
risk_level = "low"
|
||
elif confidence >= 0.6:
|
||
risk_level = "medium"
|
||
else:
|
||
risk_level = "high"
|
||
|
||
# 組出人類可讀的 description（Telegram 卡片顯示用）
|
||
# 2026-04-16 ogt + Claude Sonnet 4.6: 修復 description=debate_summary garbage
|
||
diag = getattr(package, "diagnosis", None)
|
||
plan = getattr(package, "action_plan", None)
|
||
desc_parts = []
|
||
if diag and getattr(diag, "top_hypothesis", None):
|
||
h = diag.top_hypothesis
|
||
desc_parts.append(f"根因：{h.description[:150]}（信心 {h.confidence:.0%}）")
|
||
if plan and getattr(plan, "top_candidate", None):
|
||
c = plan.top_candidate
|
||
desc_parts.append(f"方案：{c.action[:100]}")
|
||
# blocked_reason 是系統內部診斷，不能放進 description（Telegram 卡片顯示用）
|
||
# 2026-04-17 ogt + Claude Sonnet 4.6（亞太）: 修復超時髒資料污染卡片
|
||
# 舊：blocked_reason → desc_parts → description → suggested_action 欄位顯示「備注：全局超時 > 90.0s」
|
||
# 新：blocked_reason 只寫入 proposal_data["blocked_reason"]，供下游閘門邏輯用，禁止進卡片顯示
|
||
# 2026-04-24 ogt + Claude Sonnet 4.6: ADR-091 鐵閘 bypass 修復
|
||
# 問題：Agent Debate 超時 (TIMEOUT/FAILED) → desc_parts 空 + action 空 → description="待分析"
|
||
# → ADR-091 鐵閘攔截（description=待分析 AND action in FAILED_TOKENS）→ PENDING 積壓
|
||
# 修法：超時/全降級時使用明確降級文字，讓鐵閘放行 → Telegram 推送降級通知 → 人工可見
|
||
if desc_parts:
|
||
description = "；".join(desc_parts)
|
||
elif action:
|
||
description = action[:200]
|
||
else:
|
||
_status = getattr(package, "session_status", None)
|
||
_status_val = _status.value if _status and hasattr(_status, "value") else ""
|
||
if _status_val == "timeout":
|
||
description = "AI 分析超時（90s），降級至人工審核"
|
||
elif _status_val == "failed" or getattr(package, "all_agents_degraded", False):
|
||
description = "AI 分析降級，所有 Agent 無有效輸出，建議人工確認"
|
||
else:
|
||
description = "待分析"
|
||
|
||
return {
|
||
"action": action,
|
||
"kubectl_command": action if action.startswith("kubectl") else "",
|
||
"description": description,
|
||
"reasoning": package.debate_summary[:1000] if package.debate_summary else "",
|
||
"confidence": confidence,
|
||
"risk_level": risk_level,
|
||
"source": "phase2_agent_debate",
|
||
"requires_human_review": package.requires_human_approval,
|
||
# Phase 2 診斷摘要（供 Audit Trail / 學習閉環，不直接顯示給用戶）
|
||
"debate_summary": package.debate_summary or "",
|
||
"all_agents_degraded": package.all_agents_degraded,
|
||
"blocked_reason": package.blocked_reason or "",
|
||
"session_status": package.session_status.value if package.session_status else "",
|
||
# MINOR-2: 補齊 Expert System / LLM 路徑存在的 keys，防止下游 .get() 靜默空缺
|
||
"is_rule_based": False,
|
||
"matched_rule": "",
|
||
"rule_id": "",
|
||
"from_cache": False,
|
||
}
|
||
|
||
|
||
def expert_analyze(incident: Incident) -> dict[str, Any]:
|
||
"""
|
||
Expert System 規則引擎分析
|
||
|
||
這是 100% 本地執行，永不失敗的保底方案
|
||
"""
|
||
target = incident.affected_services[0] if incident.affected_services else "unknown-service"
|
||
alert_names = " ".join([s.alert_name.lower() for s in incident.signals])
|
||
|
||
# 匹配規則
|
||
matched_rule = "default"
|
||
for rule_name, rule in EXPERT_RULES.items():
|
||
if rule_name == "default":
|
||
continue
|
||
if any(pattern in alert_names for pattern in rule["patterns"]):
|
||
matched_rule = rule_name
|
||
break
|
||
|
||
rule = EXPERT_RULES[matched_rule]
|
||
|
||
# 2026-03-29 ogt: Expert System 不應該假裝有高信心分數
|
||
# 設為 0.0 強制標記為規則匹配，而非 AI 仲裁
|
||
return {
|
||
"source": "expert_system",
|
||
"action": rule["action"].format(target=target),
|
||
"description": rule["description"],
|
||
"diagnosis_description": rule["description"], # openclaw.py reads this key
|
||
"risk_level": rule["risk_level"],
|
||
"reasoning": f"[規則匹配] {rule['reasoning']}", # 明確標示來源
|
||
"confidence": 0.0, # 🔴 規則匹配不是 AI 仲裁，信心度設 0
|
||
"kubectl_command": rule["action"].format(target=target),
|
||
"matched_rule": matched_rule,
|
||
"initial_diagnosis": matched_rule, # openclaw.py reads this key
|
||
"from_cache": False,
|
||
"is_rule_based": True,
|
||
}
|
||
|
||
|
||
# =============================================================================
|
||
# Decision Token (Redis)
|
||
# =============================================================================
|
||
|
||
class DecisionToken:
|
||
"""
|
||
決策令牌 - 前端持有此 token 即可操作
|
||
|
||
Redis Key: decision:{token}
|
||
TTL: 1 小時
|
||
"""
|
||
|
||
def __init__(
|
||
self,
|
||
token: str,
|
||
incident_id: str,
|
||
state: DecisionState,
|
||
proposal_data: dict[str, Any] | None = None,
|
||
proposal_id: str | None = None,
|
||
created_at: datetime | None = None,
|
||
updated_at: datetime | None = None,
|
||
error: str | None = None,
|
||
):
|
||
self.token = token
|
||
self.incident_id = incident_id
|
||
self.state = state
|
||
self.proposal_data = proposal_data
|
||
self.proposal_id = proposal_id
|
||
self.created_at = created_at or datetime.now(UTC)
|
||
self.updated_at = updated_at or datetime.now(UTC)
|
||
self.error = error
|
||
|
||
def to_dict(self) -> dict[str, Any]:
|
||
return {
|
||
"token": self.token,
|
||
"incident_id": self.incident_id,
|
||
"state": self.state.value,
|
||
"proposal_data": self.proposal_data,
|
||
"proposal_id": self.proposal_id,
|
||
"created_at": self.created_at.isoformat(),
|
||
"updated_at": self.updated_at.isoformat(),
|
||
"error": self.error,
|
||
}
|
||
|
||
@classmethod
|
||
def from_dict(cls, data: dict[str, Any]) -> "DecisionToken":
|
||
return cls(
|
||
token=data["token"],
|
||
incident_id=data["incident_id"],
|
||
state=DecisionState(data["state"]),
|
||
proposal_data=data.get("proposal_data"),
|
||
proposal_id=data.get("proposal_id"),
|
||
created_at=datetime.fromisoformat(data["created_at"]) if data.get("created_at") else None,
|
||
updated_at=datetime.fromisoformat(data["updated_at"]) if data.get("updated_at") else None,
|
||
error=data.get("error"),
|
||
)
|
||
|
||
|
||
# =============================================================================
|
||
# Protocol Interface (Phase 17 P1 - 紅區治理)
|
||
# =============================================================================
|
||
|
||
@runtime_checkable
|
||
class IDecisionManager(Protocol):
|
||
"""
|
||
DecisionManager 介面定義
|
||
|
||
用途:
|
||
- 依賴注入 (DI) 時的型別約束
|
||
- 測試時 Mock 的型別檢查
|
||
- 符合 leWOOOgo 積木化規範
|
||
|
||
Tier 3 紅區服務: 修改需首席架構師簽核
|
||
|
||
@see feedback_lewooogo_modular_enforcement.md
|
||
@see docs/RED_ZONES.md
|
||
"""
|
||
|
||
async def get_or_create_decision(
|
||
self,
|
||
incident: "Incident",
|
||
timeout_sec: float = 30.0,
|
||
) -> "DecisionToken":
|
||
"""取得或建立決策令牌"""
|
||
...
|
||
|
||
async def mark_executing(self, token: str) -> "DecisionToken | None":
|
||
"""標記決策為執行中"""
|
||
...
|
||
|
||
async def mark_completed(self, token: str, result: dict[str, Any] | None = None) -> "DecisionToken | None":
|
||
"""標記決策為已完成"""
|
||
...
|
||
|
||
|
||
# =============================================================================
|
||
# Decision Manager
|
||
# =============================================================================
|
||
|
||
DECISION_TOKEN_PREFIX = "decision:"
|
||
DECISION_TOKEN_TTL = 3600 # 1 小時
|
||
|
||
|
||
class DecisionManager:
|
||
"""
|
||
決策管理器 - Phase 6.5 核心
|
||
|
||
職責:
|
||
1. 為每個 Incident 簽發 decision_token
|
||
2. 並行執行 LLM + Expert System
|
||
3. First-Win 或 Fallback 策略
|
||
4. 確保 UI 永遠有決策可操作
|
||
"""
|
||
|
||
def __init__(self):
|
||
self._openclaw = get_openclaw()
|
||
# I2 修復 (首席架構師 Review): 注入 KnowledgeService 避免函數內 import 耦合
|
||
# 2026-04-04 Claude Code
|
||
from src.services.knowledge_service import get_knowledge_service
|
||
self._knowledge_svc = get_knowledge_service()
|
||
# I2 續修 2026-04-12 Claude Sonnet 4.6 Asia/Taipei: 注入 MCP Providers
|
||
# 原 _collect_mcp_context 在函數內 import + 直接實例化，違反積木化鐵律
|
||
from src.plugins.mcp.providers.ssh_provider import SSHProvider
|
||
from src.plugins.mcp.providers.k8s_provider import K8sProvider
|
||
self._ssh = SSHProvider()
|
||
self._k8s = K8sProvider()
|
||
|
||
async def get_or_create_decision(
|
||
self,
|
||
incident: Incident,
|
||
timeout_sec: float = 30.0,
|
||
) -> DecisionToken:
|
||
"""
|
||
取得或建立決策令牌
|
||
|
||
核心邏輯:
|
||
1. 檢查是否已有 token
|
||
2. 沒有則建立新 token (INIT)
|
||
3. 啟動非同步分析 (ANALYZING)
|
||
4. 等待結果或 timeout 後使用 Expert System
|
||
|
||
這個方法保證在 timeout_sec 內返回有效 token
|
||
"""
|
||
_redis_client = get_redis()
|
||
|
||
# 1. 先檢查現有 token（所有類型統一入口）
|
||
# 2026-04-16 ogt + Claude Sonnet 4.6: 修復 TYPE-1 bypass 未檢查 existing token 導致
|
||
# HostBackupFailed 等告警重複洗版 — existing token 檢查必須在 TYPE-1 bypass 前執行
|
||
existing_token = await self._find_existing_token(incident.incident_id)
|
||
if existing_token:
|
||
# READY 或 EXECUTING 狀態: 直接返回
|
||
if existing_token.state in (DecisionState.READY, DecisionState.EXECUTING):
|
||
return existing_token
|
||
# COMPLETED 狀態: 直接返回，避免重複建立 decision 導致 Telegram 轟炸
|
||
if existing_token.state == DecisionState.COMPLETED:
|
||
return existing_token
|
||
# 2026-04-16 ogt + Claude Sonnet 4.6: 修復重複卡片根因 — ANALYZING 未早返回
|
||
# 問題：多 pod 並發時 pod-A 在 ANALYZING，pod-B/C 發現 ANALYZING 不在返回條件
|
||
# → 各自建新 token → 同一 incident 跑 3 次 agent_debate → 送出 3 張 TG 卡
|
||
# 修復：ANALYZING 狀態也直接返回，避免重複處理
|
||
if existing_token.state == DecisionState.ANALYZING:
|
||
logger.debug(
|
||
"decision_analyzing_in_progress",
|
||
incident_id=incident.incident_id,
|
||
token=existing_token.token,
|
||
reason="另一個 worker 正在分析中，跳過重複建立",
|
||
)
|
||
return existing_token
|
||
|
||
# ADR-073 Phase 3-1: TYPE-1 triage guard — 純資訊告警跳過 LLM 分析
|
||
# classify_alert_early() 已在 webhook 入口設定 notification_type
|
||
# TYPE-1 (info/backup/heartbeat) 不需 AI 推理，直接推 Telegram 後返回
|
||
# 2026-04-12 ogt
|
||
if getattr(incident, "notification_type", None) == "TYPE-1":
|
||
_info_token = DecisionToken(
|
||
token=f"DEC-{uuid4().hex[:12].upper()}",
|
||
incident_id=incident.incident_id,
|
||
state=DecisionState.COMPLETED,
|
||
proposal_data={
|
||
"source": "triage_guard",
|
||
"notification_type": "TYPE-1",
|
||
"decision_state": "COMPLETED",
|
||
"auto_executed": False,
|
||
"confidence": 1.0,
|
||
"risk_level": "low",
|
||
"description": "純資訊通知，無需操作",
|
||
},
|
||
)
|
||
# 2026-04-16 ogt + Claude Sonnet 4.6: TYPE-1 token TTL 24h 防洗版
|
||
# 原 3600s 導致每小時重推同一 HostBackupFailed/TYPE-1 告警
|
||
await self._save_token(_info_token, ttl=86400)
|
||
_fire_and_forget(_push_decision_to_telegram(incident, _info_token.proposal_data))
|
||
logger.info(
|
||
"decision_type1_bypass",
|
||
incident_id=incident.incident_id,
|
||
notification_type="TYPE-1",
|
||
)
|
||
return _info_token
|
||
|
||
# 2. 建立新 token
|
||
token = DecisionToken(
|
||
token=f"DEC-{uuid4().hex[:12].upper()}",
|
||
incident_id=incident.incident_id,
|
||
state=DecisionState.ANALYZING,
|
||
)
|
||
|
||
await self._save_token(token)
|
||
|
||
logger.info(
|
||
"decision_analyzing",
|
||
token=token.token,
|
||
incident_id=incident.incident_id,
|
||
)
|
||
|
||
# 3. 並行執行雙軌決策
|
||
try:
|
||
proposal_data = await asyncio.wait_for(
|
||
self._dual_engine_analyze(incident),
|
||
timeout=timeout_sec,
|
||
)
|
||
|
||
token.state = DecisionState.READY
|
||
token.proposal_data = proposal_data
|
||
token.updated_at = datetime.now(UTC)
|
||
|
||
logger.info(
|
||
"decision_ready",
|
||
token=token.token,
|
||
source=proposal_data.get("source", "unknown"),
|
||
)
|
||
|
||
except TimeoutError:
|
||
# Timeout: 使用 Expert System 保底
|
||
logger.warning(
|
||
"decision_timeout_using_expert",
|
||
token=token.token,
|
||
timeout_sec=timeout_sec,
|
||
)
|
||
|
||
expert_result = expert_analyze(incident)
|
||
token.state = DecisionState.READY
|
||
token.proposal_data = expert_result
|
||
token.updated_at = datetime.now(UTC)
|
||
|
||
except Exception as e:
|
||
# 任何錯誤: 使用 Expert System 保底
|
||
logger.exception(
|
||
"decision_error_using_expert",
|
||
token=token.token,
|
||
error=str(e),
|
||
)
|
||
|
||
expert_result = expert_analyze(incident)
|
||
token.state = DecisionState.READY
|
||
token.proposal_data = expert_result
|
||
token.error = str(e)
|
||
token.updated_at = datetime.now(UTC)
|
||
|
||
# 4. 儲存最終結果
|
||
await self._save_token(token)
|
||
|
||
# 4b. 2026-04-16 Claude Sonnet 4.6: 將 AI 分析結果寫入 incidents.decision_chain (DB 長期保存)
|
||
# 修復 Gap: decision token 只有 Redis TTL ~12min，AI 分析結果歷史永久丟失
|
||
# 寫入: diagnosis / confidence / risk_level / provider / source
|
||
if token.proposal_data:
|
||
_fire_and_forget(
|
||
self._persist_decision_to_db(incident.incident_id, token.proposal_data)
|
||
)
|
||
|
||
# 4c. YAML NO_ACTION 閘門 — 決策路由中樞（2026-04-17 ogt + Claude Sonnet 4.6）
|
||
# 架構原則：通知層（_push_decision_to_telegram）只做狀態轉譯，不查業務邏輯。
|
||
# 因此 NO_ACTION / INVALID_TARGET 判斷必須在此閘門統一完成，任何路徑都必須通過。
|
||
#
|
||
# 根因（先前盲點）：Phase 2 路徑拒絕後直接推 TG，不經 auto_execute() 的 YAML check，
|
||
# Coordinator 不設 blocked_reason → TG 收到空 blocked_reason → 無法正確分類通知類型。
|
||
# 修復：在 auto_approve 之前，統一查詢 YAML 規則：
|
||
# NO_ACTION → 標記 blocked_reason + is_informational_only → 短路跳過 auto_approve
|
||
# INVALID_TARGET → 標記 blocked_reason → 短路，TYPE-4 由 TG 層轉譯
|
||
if token.state == DecisionState.READY and token.proposal_data and incident.signals:
|
||
_gate_alertname = incident.signals[0].labels.get("alertname", "")
|
||
if _gate_alertname and not token.proposal_data.get("blocked_reason", ""):
|
||
try:
|
||
from src.services.alert_rule_engine import match_rule as _gate_match
|
||
_gate_r = _gate_match({
|
||
"labels": incident.signals[0].labels,
|
||
"alert_type": _gate_alertname,
|
||
"message": "",
|
||
"target_resource": (
|
||
incident.affected_services[0]
|
||
if incident.affected_services else "unknown"
|
||
),
|
||
"namespace": "awoooi-prod",
|
||
})
|
||
if _gate_r:
|
||
_gate_blocked = _gate_r.get("blocked_reason", "")
|
||
_gate_action = _gate_r.get("suggested_action", "")
|
||
if "INVALID_TARGET" in _gate_blocked or _gate_action == "NO_ACTION":
|
||
# 標記 blocked_reason，讓 TG 層正確轉譯通知類型
|
||
if "INVALID_TARGET" in _gate_blocked:
|
||
token.proposal_data["blocked_reason"] = _gate_blocked
|
||
else:
|
||
token.proposal_data["blocked_reason"] = f"YAML: NO_ACTION for {_gate_alertname}"
|
||
token.proposal_data["is_informational_only"] = True
|
||
token.proposal_data["auto_executed"] = False
|
||
token.proposal_data["decision_state"] = token.state.value
|
||
await self._save_token(token)
|
||
_fire_and_forget(
|
||
_push_decision_to_telegram(incident, token.proposal_data)
|
||
)
|
||
logger.info(
|
||
"yaml_gate_short_circuit",
|
||
incident_id=incident.incident_id,
|
||
alertname=_gate_alertname,
|
||
blocked_reason=token.proposal_data["blocked_reason"],
|
||
)
|
||
return token # 短路 — 跳過 auto_approve + Blast Radius 評估
|
||
except Exception as _gate_err:
|
||
logger.debug("yaml_gate_error", error=str(_gate_err))
|
||
# 閘門查詢失敗 → 降級繼續正常流程（不阻塞）
|
||
|
||
# 5. ADR-030 Phase 4: 自動執行判斷
|
||
if token.state == DecisionState.READY and token.proposal_data:
|
||
# 評估是否可以自動執行
|
||
auto_policy = get_auto_approve_policy()
|
||
auto_decision = auto_policy.evaluate(
|
||
proposal_data=token.proposal_data,
|
||
playbook=token.proposal_data.get("_matched_playbook"), # 如果有
|
||
)
|
||
|
||
if auto_decision.should_auto_approve:
|
||
# 自動執行 (跳過人工審核)
|
||
logger.info(
|
||
"auto_approve_triggered",
|
||
incident_id=incident.incident_id,
|
||
reason=auto_decision.reason.value,
|
||
detail=auto_decision.reason_detail,
|
||
)
|
||
token.state = DecisionState.EXECUTING
|
||
token.proposal_data["auto_approved"] = True
|
||
token.proposal_data["auto_approve_reason"] = auto_decision.reason_detail
|
||
await self._save_token(token)
|
||
|
||
# 觸發自動執行 (非阻塞)
|
||
_fire_and_forget(
|
||
self._auto_execute(incident, token)
|
||
)
|
||
else:
|
||
# 需人工審核: 推送到 Telegram
|
||
# ADR-071: 注入 decision_state + auto_executed 供 classify_notification 使用
|
||
token.proposal_data["decision_state"] = token.state.value if token.state else ""
|
||
token.proposal_data["auto_executed"] = False
|
||
_fire_and_forget(
|
||
_push_decision_to_telegram(incident, token.proposal_data)
|
||
)
|
||
|
||
return token
|
||
|
||
async def _auto_execute(self, incident: Incident, token: "DecisionToken") -> None:
|
||
"""
|
||
ADR-030 Phase 4: 自動執行已批准的操作
|
||
|
||
僅當 AutoApprovePolicy 判斷可自動執行時呼叫
|
||
執行後發 Telegram 結果通知 (統帥要求: 修復結果對應同一告警)
|
||
2026-04-09 Claude Sonnet 4.6 Asia/Taipei
|
||
"""
|
||
action = token.proposal_data.get("kubectl_command", "")
|
||
|
||
# 2026-04-15 ogt: YAML 規則引擎優先 — 架構斷點修復
|
||
# 根因：LLM 生成的 kubectl_command 與 YAML 規則引擎的 NO_ACTION / SSH 指令完全脫節
|
||
# YAML 規則是人工審閱的權威來源，LLM 只是輔助
|
||
# 修復策略：
|
||
# 1. YAML → NO_ACTION → 立即返回，不執行任何操作
|
||
# 2. YAML → SSH 指令（非 kubectl）→ 覆蓋 LLM 生成的 action，讓 SSH 路由生效
|
||
_alertname_for_yaml = incident.signals[0].labels.get("alertname", "") if incident.signals else ""
|
||
if _alertname_for_yaml:
|
||
try:
|
||
from src.services.alert_rule_engine import match_rule as _yaml_match
|
||
_yaml_r = _yaml_match({
|
||
"labels": incident.signals[0].labels if incident.signals else {},
|
||
"alert_type": _alertname_for_yaml,
|
||
"message": "",
|
||
"target_resource": incident.affected_services[0] if incident.affected_services else "unknown",
|
||
"namespace": "awoooi-prod",
|
||
})
|
||
if _yaml_r:
|
||
if _yaml_r.get("suggested_action") == "NO_ACTION":
|
||
logger.info(
|
||
"auto_execute_yaml_no_action",
|
||
incident_id=incident.incident_id,
|
||
alertname=_alertname_for_yaml,
|
||
reason="YAML 規則明確標記 NO_ACTION，不執行自動修復",
|
||
)
|
||
token.state = DecisionState.READY
|
||
token.proposal_data["auto_executed"] = False
|
||
token.proposal_data["blocked_reason"] = f"YAML: NO_ACTION for {_alertname_for_yaml}"
|
||
await self._save_token(token)
|
||
_fire_and_forget(_push_decision_to_telegram(incident, token.proposal_data))
|
||
return
|
||
|
||
# 2026-04-16 ogt + Claude Sonnet 4.6: INVALID_TARGET → 人工確認 TYPE-4
|
||
# 根因：target 無法解析 → rule engine 清空 kubectl_command + 設 blocked_reason
|
||
# 系統不應繼續嘗試執行，提早返回讓 SRE 介入
|
||
_yaml_blocked = _yaml_r.get("blocked_reason", "")
|
||
if "INVALID_TARGET" in _yaml_blocked:
|
||
logger.warning(
|
||
"auto_execute_yaml_invalid_target",
|
||
incident_id=incident.incident_id,
|
||
alertname=_alertname_for_yaml,
|
||
blocked_reason=_yaml_blocked,
|
||
)
|
||
token.state = DecisionState.READY
|
||
token.proposal_data["auto_executed"] = False
|
||
token.proposal_data["blocked_reason"] = _yaml_blocked
|
||
await self._save_token(token)
|
||
_fire_and_forget(_push_decision_to_telegram(incident, token.proposal_data))
|
||
return
|
||
|
||
_yaml_cmd = (_yaml_r.get("kubectl_command") or "").strip()
|
||
if _yaml_cmd and not _yaml_cmd.startswith("kubectl"):
|
||
# YAML 給出 SSH / docker 指令 → 覆蓋 LLM 生成的 kubectl action
|
||
action = _yaml_cmd
|
||
logger.info(
|
||
"auto_execute_yaml_cmd_override",
|
||
incident_id=incident.incident_id,
|
||
alertname=_alertname_for_yaml,
|
||
yaml_cmd=_yaml_cmd[:80],
|
||
)
|
||
except Exception as _yaml_err:
|
||
logger.debug("auto_execute_yaml_check_error", error=str(_yaml_err))
|
||
|
||
# Phase 6 ADR-087: 自我降級守衛（AIOPS_P6_SELF_DEMOTION 控制）
|
||
# SLO 違反 → 全域信心閾值調高；連續違反 → 保守模式，所有自動執行降為人工
|
||
# 2026-04-15 ogt + Claude Sonnet 4.6（亞太）: Phase 6 初始建立
|
||
try:
|
||
from src.core.feature_flags import aiops_flags as _p6_flags
|
||
if _p6_flags.is_sub_flag_enabled("AIOPS_P6_SELF_DEMOTION"):
|
||
from src.db.base import get_session_factory as _p6_sf
|
||
from src.db.models import AiGovernanceEvent as _GovernanceEvent
|
||
from sqlalchemy import select as _p6_select, func as _p6_func
|
||
from datetime import timedelta as _p6_td
|
||
|
||
_now = __import__("src.utils.timezone", fromlist=["now_taipei"]).now_taipei()
|
||
|
||
async with _p6_sf()() as _p6_sess:
|
||
# 過去 7 天有幾筆未解決的 slo_violation？
|
||
_viol_7d_q = await _p6_sess.execute(
|
||
_p6_select(_p6_func.count()).where(
|
||
_GovernanceEvent.event_type == "slo_violation",
|
||
_GovernanceEvent.resolved.is_(False),
|
||
_GovernanceEvent.triggered_at >= _now - _p6_td(days=7),
|
||
)
|
||
)
|
||
_viol_7d: int = _viol_7d_q.scalar() or 0
|
||
|
||
# 過去 14 天有幾筆未解決的 slo_violation？
|
||
_viol_14d_q = await _p6_sess.execute(
|
||
_p6_select(_p6_func.count()).where(
|
||
_GovernanceEvent.event_type == "slo_violation",
|
||
_GovernanceEvent.resolved.is_(False),
|
||
_GovernanceEvent.triggered_at >= _now - _p6_td(days=14),
|
||
)
|
||
)
|
||
_viol_14d: int = _viol_14d_q.scalar() or 0
|
||
|
||
if _viol_14d >= 2:
|
||
# 連續 2 週違反 → 保守模式：全部降為人工
|
||
logger.warning(
|
||
"auto_execute_conservative_mode",
|
||
incident_id=incident.incident_id,
|
||
viol_14d=_viol_14d,
|
||
reason="Phase 6 保守模式：連續 SLO 違反，所有自動執行暫停",
|
||
)
|
||
token.state = DecisionState.READY
|
||
token.proposal_data["decision_state"] = DecisionState.READY.value
|
||
token.proposal_data["auto_executed"] = False
|
||
token.proposal_data["p6_conservative_mode"] = True
|
||
token.proposal_data["p6_reason"] = f"SLO 連續違反 {_viol_14d}d，系統進入保守模式"
|
||
await self._save_token(token)
|
||
_fire_and_forget(
|
||
_push_decision_to_telegram(incident, token.proposal_data)
|
||
)
|
||
# 記錄保守模式事件
|
||
try:
|
||
from src.db.base import get_session_factory as _p6_sf2
|
||
async with _p6_sf2()() as _s2:
|
||
_s2.add(_GovernanceEvent(
|
||
event_type="conservative_mode",
|
||
details={
|
||
"incident_id": incident.incident_id,
|
||
"viol_14d": _viol_14d,
|
||
"triggered_at": _now.isoformat(),
|
||
},
|
||
resolved=False,
|
||
))
|
||
await _s2.commit()
|
||
except Exception:
|
||
pass
|
||
return
|
||
|
||
elif _viol_7d >= 1:
|
||
# 近 7 天有違反 → 自我降級：信心閾值提高，記錄 demotion 事件
|
||
_confidence = float(token.proposal_data.get("confidence", 0.0))
|
||
_raised_threshold = 0.75 # 原 0.70 → 調高 0.05
|
||
if _confidence < _raised_threshold:
|
||
logger.warning(
|
||
"auto_execute_self_demoted",
|
||
incident_id=incident.incident_id,
|
||
confidence=_confidence,
|
||
raised_threshold=_raised_threshold,
|
||
reason="Phase 6 自我降級：近 7d SLO 違反，信心閾值提高",
|
||
)
|
||
token.state = DecisionState.READY
|
||
token.proposal_data["decision_state"] = DecisionState.READY.value
|
||
token.proposal_data["auto_executed"] = False
|
||
token.proposal_data["p6_self_demoted"] = True
|
||
token.proposal_data["p6_reason"] = (
|
||
f"Phase 6 自我降級：近 7d SLO 違反，"
|
||
f"信心 {_confidence:.2f} < {_raised_threshold}，升為人工"
|
||
)
|
||
await self._save_token(token)
|
||
_fire_and_forget(
|
||
_push_decision_to_telegram(incident, token.proposal_data)
|
||
)
|
||
try:
|
||
from src.db.base import get_session_factory as _p6_sf3
|
||
async with _p6_sf3()() as _s3:
|
||
_s3.add(_GovernanceEvent(
|
||
event_type="self_demotion",
|
||
details={
|
||
"incident_id": incident.incident_id,
|
||
"confidence": _confidence,
|
||
"raised_threshold": _raised_threshold,
|
||
"viol_7d": _viol_7d,
|
||
"triggered_at": _now.isoformat(),
|
||
},
|
||
resolved=False,
|
||
))
|
||
await _s3.commit()
|
||
except Exception:
|
||
pass
|
||
return
|
||
# confidence >= raised_threshold → 允許繼續自動執行
|
||
except Exception as _p6_err:
|
||
logger.warning("p6_self_demotion_check_error", error=str(_p6_err))
|
||
# 保守：P6 check 出錯 → 不阻擋（避免因 P6 bug 把所有修復都堵住）
|
||
|
||
# ADR-073 Phase 3-5: action | parse fix (2026-04-12 ogt)
|
||
# LLM 有時輸出 "kubectl rollout restart X | kubectl get pods -n Y"
|
||
# | 後面是查詢指令，取第一個才是真正的修復操作
|
||
if action and "|" in action:
|
||
action = action.split("|")[0].strip()
|
||
logger.debug("action_pipe_stripped", incident_id=incident.incident_id, action=action)
|
||
|
||
# NO_ACTION 規則（備份失敗/E2E smoke test 等）— kubectl_command 為空，不執行，直接返回
|
||
# 2026-04-11 Claude Sonnet 4.6: 防止空 action 或 NO_ACTION 字串進入自動執行流程
|
||
_suggested_action = token.proposal_data.get("suggested_action", "")
|
||
if not action or _suggested_action == "NO_ACTION":
|
||
logger.info(
|
||
"auto_execute_skipped_no_action",
|
||
incident_id=incident.incident_id,
|
||
suggested_action=_suggested_action,
|
||
reason="規則標記 NO_ACTION 或 kubectl_command 為空，不執行自動修復",
|
||
)
|
||
token.state = DecisionState.READY
|
||
await self._save_token(token)
|
||
_fire_and_forget(
|
||
_push_decision_to_telegram(incident, token.proposal_data)
|
||
)
|
||
return
|
||
|
||
# 替換所有 placeholder — {target}/{namespace}/<deployment_name> 等
|
||
_target = incident.affected_services[0] if incident.affected_services else "unknown"
|
||
_ns = "awoooi-prod"
|
||
if incident.signals:
|
||
_ns = incident.signals[0].labels.get("namespace", "awoooi-prod")
|
||
import re as _re
|
||
|
||
# BUG-002 修復 2026-04-11: 主機層告警(HostHighCpuLoad 等)無 component/job/pod label
|
||
# → affected_services=[] → target="unknown" → safety guard 攔截
|
||
# 補救：用 K8s MCP 依 alertname/host label 動態查詢受影響 Pod
|
||
if _target == "unknown":
|
||
_target = await _resolve_target_from_k8s(incident, _ns) or "unknown"
|
||
|
||
action = action.replace("{target}", _target).replace("{namespace}", _ns)
|
||
# <xxx> 格式佔位符 → 用 target 替換
|
||
action = _re.sub(r"<deployment_name>", _target, action)
|
||
action = _re.sub(r"<[^>]+>", _target, action)
|
||
|
||
# GAP-A4 Phase 2 (2026-04-14 Claude Sonnet 4.6): LLM 路徑 target 救援
|
||
# 真兇：LLM 直接產出 `kubectl scale deployment HostHighCpuLoad` (target=alertname)
|
||
# GAP-A4 Phase 1 只修了 rule_engine._extract_vars，LLM 路徑沒檢查
|
||
# 結果：12 次 auto_execute_blocked_unresolved_placeholder 直接攔下 → 飛輪 0
|
||
try:
|
||
from src.services.alert_rule_engine import (
|
||
_extract_vars as _rule_extract_vars,
|
||
_is_bad_target as _rule_is_bad_target,
|
||
)
|
||
_alertname_for_rescue = (
|
||
incident.signals[0].labels.get("alertname", "") if incident.signals else ""
|
||
)
|
||
# 從 action 提取 deployment 名稱（kubectl scale/restart deployment XXX 或 deployment/XXX）
|
||
_kubectl_target_match = _re.search(
|
||
r"deployment[/\s]+([\w.\-]+)", action
|
||
)
|
||
if _kubectl_target_match:
|
||
_llm_target = _kubectl_target_match.group(1)
|
||
if _rule_is_bad_target(_llm_target, _alertname_for_rescue):
|
||
# LLM 把垃圾當 deployment 名（alertname/unknown/IP）→ 重推
|
||
_alert_ctx = {
|
||
"labels": incident.signals[0].labels if incident.signals else {},
|
||
"target_resource": _target,
|
||
"namespace": _ns,
|
||
"alert_type": _alertname_for_rescue,
|
||
}
|
||
_good_target = _rule_extract_vars(_alert_ctx).get("target", "")
|
||
if _good_target and _good_target != "unknown" and not _rule_is_bad_target(_good_target, _alertname_for_rescue):
|
||
_old_action = action
|
||
action = action.replace(_llm_target, _good_target)
|
||
logger.info(
|
||
"auto_execute_target_rescued",
|
||
incident_id=incident.incident_id,
|
||
llm_target=_llm_target,
|
||
rescued_target=_good_target,
|
||
old_action=_old_action[:120],
|
||
new_action=action[:120],
|
||
reason="LLM 產出垃圾 target，從 labels 重推 deployment 名",
|
||
)
|
||
else:
|
||
logger.warning(
|
||
"auto_execute_target_rescue_failed",
|
||
incident_id=incident.incident_id,
|
||
llm_target=_llm_target,
|
||
alertname=_alertname_for_rescue,
|
||
reason="labels 也找不到合法 deployment，將進 safety guard 攔截 → 人工",
|
||
)
|
||
except Exception as _rescue_err:
|
||
logger.debug("target_rescue_skipped", error=str(_rescue_err))
|
||
|
||
# ADR-073 Phase 3-2: infrastructure 告警 (Docker/Host) → SSH MCP routing (2026-04-12 ogt)
|
||
# alert_category = "infrastructure" 表示 Docker 告警，非 kubectl action → SSH
|
||
# P1-1 fix 2026-04-12: 必須在 kubectl safety guard 之前 routing，否則 docker 指令被 _action_safe=False 攔截
|
||
_alert_category = getattr(incident, "alert_category", None) or ""
|
||
if _alert_category == "infrastructure" and action and not action.startswith("kubectl"):
|
||
await self._ssh_execute(incident, token, action, _target)
|
||
return
|
||
|
||
# 2026-04-15 ogt: host_resource 告警（HostHighCpuLoad 等）不是 K8s workload 問題
|
||
# 不得執行 kubectl 操作，改降級人工審核
|
||
# 根因：原本只擋了 infrastructure，忘記 host_resource 也不走 K8s
|
||
if _alert_category == "host_resource" and action and action.startswith("kubectl"):
|
||
logger.warning(
|
||
"auto_execute_blocked_host_resource_no_k8s",
|
||
incident_id=incident.incident_id,
|
||
alert_category=_alert_category,
|
||
action=action[:80],
|
||
reason="host_resource 告警不應執行 K8s kubectl 操作，降級人工審核",
|
||
)
|
||
token.state = DecisionState.READY
|
||
token.proposal_data["auto_executed"] = False
|
||
token.proposal_data["mcp_all_failed"] = True
|
||
token.proposal_data["blocked_reason"] = "host_resource 告警禁止 K8s kubectl，請人工排查主機"
|
||
await self._save_token(token)
|
||
_fire_and_forget(_push_decision_to_telegram(incident, token.proposal_data))
|
||
return
|
||
|
||
# 安全守衛: 替換後仍含 "unknown" 或未替換的 <...>/{...} → 拒絕執行
|
||
# 另外：若 target 等於 alertname，代表 LLM 把告警名稱填入 deployment_name，也拒絕
|
||
_alertname = incident.signals[0].labels.get("alertname", "") if incident.signals else ""
|
||
_target_is_alertname = bool(_alertname and _target == _alertname)
|
||
# P1 fix 2026-04-11: kubectl action 危險字元白名單 — 防止 && || ; > | 注入
|
||
_action_safe = bool(_ALLOWED_KUBECTL_PATTERN.match(action.strip()))
|
||
if "unknown" in action or _re.search(r"[<{][^>}]+[>}]", action) or _target_is_alertname or not _action_safe:
|
||
logger.warning(
|
||
"auto_execute_blocked_unresolved_placeholder",
|
||
incident_id=incident.incident_id,
|
||
action=action,
|
||
target=_target,
|
||
reason="action 含未解析的 placeholder、unknown、target==alertname、或危險字元，拒絕執行",
|
||
)
|
||
# Safety guard 攔截 → 降級為人工審核，而非「修復失敗」
|
||
# 2026-04-11 Claude Sonnet 4.6: 不發 ❌ 失敗訊息，改發人工審核卡片
|
||
# 讓統帥看到告警並決定如何處理，而不是重複收到「無法確認 deployment 名稱」
|
||
token.state = DecisionState.READY # 回到 READY，讓人工審核
|
||
token.error = f"Auto-execute blocked (safety guard): {action[:80]}"
|
||
token.proposal_data["decision_state"] = DecisionState.READY.value
|
||
token.proposal_data["auto_executed"] = False
|
||
token.proposal_data["mcp_all_failed"] = True # 標記讓 classify_notification → TYPE-4
|
||
await self._save_token(token)
|
||
_fire_and_forget(
|
||
_push_decision_to_telegram(incident, token.proposal_data)
|
||
)
|
||
return
|
||
|
||
# BUG-003 修復 2026-04-11: 加入 K8s deployment 存在性驗證，
|
||
# 避免 LLM 產生的無效 deployment name（<placeholder>/alertname/unknown）通過 safety guard
|
||
# 但仍對 K8s 發出錯誤指令
|
||
if _target and _target != "unknown":
|
||
_k8s_verified = await _verify_k8s_deployment_exists(_target, _ns, alertname=_alertname)
|
||
if not _k8s_verified:
|
||
logger.warning(
|
||
"auto_execute_blocked_deployment_not_found",
|
||
incident_id=incident.incident_id,
|
||
target=_target,
|
||
namespace=_ns,
|
||
reason="K8s 中找不到此 deployment/pod，拒絕執行",
|
||
)
|
||
# K8s 找不到 target → 降級為人工審核，同 safety guard 策略
|
||
# 2026-04-11 Claude Sonnet 4.6: 不發 ❌ 失敗，改發 TYPE-4 人工審核卡片
|
||
token.state = DecisionState.READY
|
||
token.error = f"Auto-execute blocked: deployment '{_target}' not found in K8s"
|
||
token.proposal_data["decision_state"] = DecisionState.READY.value
|
||
token.proposal_data["auto_executed"] = False
|
||
token.proposal_data["mcp_all_failed"] = True
|
||
await self._save_token(token)
|
||
_fire_and_forget(
|
||
_push_decision_to_telegram(incident, token.proposal_data)
|
||
)
|
||
return
|
||
|
||
# Phase 5 ADR-086: Blast Radius 分級守衛（AIOPS_P5_BLAST_RADIUS_CHECK 控制）
|
||
# 評估修復動作的爆炸半徑，決定是否可自動執行或需升級審核
|
||
# 2026-04-15 ogt + Claude Sonnet 4.6（亞太）: Phase 5 初始建立
|
||
try:
|
||
from src.core.feature_flags import aiops_flags as _p5_flags
|
||
if _p5_flags.AIOPS_P5_BLAST_RADIUS_CHECK:
|
||
from src.services.blast_radius_calculator import get_blast_radius_calculator
|
||
from src.services.declarative_remediation import get_declarative_remediation
|
||
|
||
_calc = get_blast_radius_calculator()
|
||
_blast = _calc.calculate(action, namespace=_ns, target=_target)
|
||
_spec = get_declarative_remediation().evaluate(
|
||
action=action, target=_target, namespace=_ns,
|
||
description=token.proposal_data.get("description", ""),
|
||
)
|
||
|
||
# 記錄分級結果到 proposal_data（供學習 + 審計）
|
||
token.proposal_data["blast_radius_score"] = _blast.score
|
||
token.proposal_data["blast_radius_tier"] = _blast.tier
|
||
token.proposal_data["blast_radius_reason"] = _blast.reason
|
||
|
||
if _blast.tier == "blocked":
|
||
# HARD_RULES 永擋
|
||
logger.warning(
|
||
"auto_execute_blast_radius_hard_blocked",
|
||
incident_id=incident.incident_id,
|
||
action=action[:80],
|
||
reason=_blast.reason,
|
||
)
|
||
token.state = DecisionState.READY
|
||
token.proposal_data["auto_executed"] = False
|
||
token.proposal_data["mcp_all_failed"] = True
|
||
token.proposal_data["blocked_reason"] = f"HARD_RULES 永擋：{_blast.reason}"
|
||
await self._save_token(token)
|
||
_fire_and_forget(_push_decision_to_telegram(incident, token.proposal_data))
|
||
return
|
||
|
||
elif _blast.tier in ("human", "dual"):
|
||
# 中高衝擊 → 升級人工審核，不自動執行
|
||
logger.info(
|
||
"auto_execute_blast_radius_escalated",
|
||
incident_id=incident.incident_id,
|
||
tier=_blast.tier,
|
||
score=_blast.score,
|
||
action=action[:80],
|
||
)
|
||
token.state = DecisionState.READY
|
||
token.proposal_data["auto_executed"] = False
|
||
token.proposal_data["requires_human_review"] = True
|
||
token.proposal_data["blast_radius_escalated"] = True
|
||
await self._save_token(token)
|
||
# dual tier → 非同步建立 GitOps Issue
|
||
if _blast.tier == "dual" and _p5_flags.AIOPS_P5_GITOPS_PR:
|
||
from src.services.gitops_pr_service import get_gitops_pr_service
|
||
_fire_and_forget(
|
||
get_gitops_pr_service().create_repair_issue(
|
||
spec=_spec,
|
||
incident_id=incident.incident_id,
|
||
diagnosis=token.proposal_data.get("debate_summary", ""),
|
||
)
|
||
)
|
||
_fire_and_forget(_push_decision_to_telegram(incident, token.proposal_data))
|
||
return
|
||
# tier == "auto" → 繼續自動執行流程
|
||
except Exception as _blast_err:
|
||
# Blast Radius 計算失敗 → 保守：視為 human tier，升級人工審核
|
||
logger.warning(
|
||
"blast_radius_check_failed_conservative_escalate",
|
||
incident_id=incident.incident_id,
|
||
error=str(_blast_err),
|
||
)
|
||
token.state = DecisionState.READY
|
||
token.proposal_data["auto_executed"] = False
|
||
token.proposal_data["blast_radius_tier"] = "unknown_conservative"
|
||
await self._save_token(token)
|
||
_fire_and_forget(_push_decision_to_telegram(incident, token.proposal_data))
|
||
return
|
||
|
||
# 2026-04-15 ogt: 同一 target 5 分鐘內最多執行 2 次，防止修復風暴
|
||
# 根因：多個 incident 共享同一 target 時，各自獨立自動執行 → 重複重啟
|
||
try:
|
||
from src.core.redis_client import get_redis as _get_redis_dm
|
||
_redis_dm = _get_redis_dm()
|
||
_dm_cooldown_key = f"awoooi:auto_execute_cooldown:{_ns}:{_target}"
|
||
_dm_exec_count = await _redis_dm.get(_dm_cooldown_key)
|
||
if _dm_exec_count and int(_dm_exec_count) >= 2:
|
||
logger.warning(
|
||
"auto_execute_cooldown_blocked",
|
||
incident_id=incident.incident_id,
|
||
target=_target,
|
||
namespace=_ns,
|
||
exec_count=int(_dm_exec_count),
|
||
reason="同一 target 5 分鐘內已自動執行 2 次，冷卻中",
|
||
)
|
||
token.state = DecisionState.READY
|
||
token.proposal_data["auto_executed"] = False
|
||
token.proposal_data["cooldown_blocked"] = True
|
||
await self._save_token(token)
|
||
return
|
||
await _redis_dm.incr(_dm_cooldown_key)
|
||
await _redis_dm.expire(_dm_cooldown_key, 300) # 5 分鐘
|
||
except Exception as _cd_err:
|
||
logger.debug("auto_execute_cooldown_check_error", error=str(_cd_err))
|
||
|
||
try:
|
||
# 延遲導入避免循環依賴
|
||
from src.models.approval import ApprovalRequest, ApprovalStatus
|
||
from src.services.approval_execution import ApprovalExecutionService
|
||
|
||
# 建立虛擬 ApprovalRequest (auto_execute — 不需人工審核)
|
||
_risk = token.proposal_data.get("risk_level", "low")
|
||
# ADR-083 Phase 3: 傳遞 matched_playbook_id，學習迴路 EWMA 才能觸發
|
||
# Playbook RAG 命中時 proposal_data["playbook_id"] 會有值（見 _try_playbook_match）
|
||
# 2026-04-15 ogt + Claude Sonnet 4.6（亞太）: Phase 3 matched_playbook_id 修復
|
||
_matched_playbook_id = token.proposal_data.get("playbook_id")
|
||
approval = ApprovalRequest(
|
||
incident_id=incident.incident_id,
|
||
action=action,
|
||
description=token.proposal_data.get("description", action[:100]),
|
||
requested_by="auto_approve",
|
||
required_signatures=0,
|
||
status=ApprovalStatus.APPROVED,
|
||
risk_level=_risk,
|
||
matched_playbook_id=_matched_playbook_id,
|
||
)
|
||
|
||
# ADR-071-I: 執行前抓 metrics_before 快照 (2026-04-11 Claude Sonnet 4.6)
|
||
_metrics_before = await _fetch_metrics_snapshot(incident)
|
||
if _metrics_before:
|
||
try:
|
||
from src.db.base import get_db_context
|
||
from src.db.models import Incident as IncidentORM
|
||
from sqlalchemy import update as _sa_update
|
||
async with get_db_context() as _db:
|
||
await _db.execute(
|
||
_sa_update(IncidentORM)
|
||
.where(IncidentORM.incident_id == incident.incident_id)
|
||
.values(metrics_before=_metrics_before)
|
||
)
|
||
await _db.commit()
|
||
except Exception as _mb_err:
|
||
logger.debug("metrics_before_save_failed",
|
||
incident_id=incident.incident_id, error=str(_mb_err))
|
||
|
||
# 執行
|
||
# 2026-04-17 ogt + Claude Sonnet 4.6 (Checkpoint-1 假成功修復):
|
||
# 舊 bug: execute_approved_action 返回 None → 此處永遠傳 success=True 給
|
||
# _push_auto_repair_result → Telegram 顯示 ✅ 自動修復完成，即使 K8s 拒絕了指令
|
||
# 修復: execute_approved_action 現在返回 bool，正確透傳給通知函數
|
||
executor = ApprovalExecutionService()
|
||
_exec_success = await executor.execute_approved_action(approval)
|
||
|
||
# 更新狀態
|
||
token.state = DecisionState.COMPLETED
|
||
token.proposal_data["auto_executed"] = True
|
||
token.proposal_data["exec_success"] = _exec_success
|
||
await self._save_token(token)
|
||
|
||
logger.info(
|
||
"auto_execute_completed",
|
||
incident_id=incident.incident_id,
|
||
action=approval.action,
|
||
exec_success=_exec_success,
|
||
)
|
||
|
||
# 2026-04-09 Claude Sonnet 4.6: 執行完成 → 發 Telegram 結果通知（成功或失敗皆發）
|
||
_fire_and_forget(
|
||
_push_auto_repair_result(incident, action, success=_exec_success)
|
||
)
|
||
|
||
except Exception as e:
|
||
logger.error(
|
||
"auto_execute_failed",
|
||
incident_id=incident.incident_id,
|
||
error=str(e),
|
||
)
|
||
token.state = DecisionState.ERROR
|
||
token.error = f"Auto-execute failed: {e}"
|
||
await self._save_token(token)
|
||
|
||
# 2026-04-09 Claude Sonnet 4.6: 執行失敗 → 發 Telegram 失敗通知 + fallback 人工
|
||
_fire_and_forget(
|
||
_push_auto_repair_result(incident, action, success=False, error=str(e))
|
||
)
|
||
_fire_and_forget(
|
||
_push_decision_to_telegram(incident, token.proposal_data)
|
||
)
|
||
|
||
async def _query_kb_context_inner(self, incident: Incident) -> str:
|
||
"""KB RAG 實際查詢邏輯，由 _query_kb_context 包裝 timeout 後呼叫"""
|
||
query_parts = list(incident.affected_services)
|
||
if incident.signals:
|
||
query_parts.insert(0, getattr(incident.signals[0], "alert_name", ""))
|
||
query = " ".join(filter(None, query_parts))
|
||
|
||
results = await self._knowledge_svc.semantic_search(query, limit=3, threshold=0.4)
|
||
if not results:
|
||
return ""
|
||
|
||
lines = ["## Knowledge Base Related Entries (KB RAG)"]
|
||
for entry, score in results:
|
||
lines.append(
|
||
f"\n### [{entry.entry_type}] {entry.title} (similarity={score:.2f})"
|
||
)
|
||
lines.append(entry.content[:500])
|
||
if len(entry.content) > 500:
|
||
lines.append("... (truncated)")
|
||
|
||
logger.info(
|
||
"kb_rag_context_injected",
|
||
incident_id=incident.incident_id,
|
||
kb_hits=len(results),
|
||
)
|
||
return "\n".join(lines)
|
||
|
||
async def _query_kb_context(self, incident: Incident) -> str:
|
||
"""
|
||
KB Phase 2: 語意搜尋相關 KB 條目，組裝為 LLM context 字串
|
||
2026-04-04 Claude Code: KB RAG 整合
|
||
|
||
C1 修復 (首席架構師審查): 5 秒 hard timeout，防止 Ollama 慢響應威脅 30s SLA
|
||
失敗/timeout 時靜默降級，不影響主分析流程
|
||
"""
|
||
try:
|
||
return await asyncio.wait_for(
|
||
self._query_kb_context_inner(incident),
|
||
timeout=5.0,
|
||
)
|
||
except asyncio.TimeoutError:
|
||
logger.warning("kb_rag_timeout", incident_id=incident.incident_id)
|
||
return ""
|
||
except (ConnectionError, OSError) as e:
|
||
# Ollama 連線問題，預期可降級
|
||
logger.warning("kb_rag_connection_error", incident_id=incident.incident_id, error=str(e))
|
||
return ""
|
||
except Exception as e:
|
||
# 非預期錯誤，用 error 級別方便監控
|
||
logger.error("kb_rag_unexpected_error", incident_id=incident.incident_id, error=str(e))
|
||
return ""
|
||
|
||
async def _collect_mcp_context(self, incident: Incident) -> str:
|
||
"""
|
||
ADR-070 全自動 AIOps: 分析前用 MCP 收集真實環境狀態
|
||
讓 LLM 拿到真實資訊做決策，而非只憑 alert labels
|
||
|
||
策略：
|
||
- K8s 告警 → K8s MCP 查 Pod 狀態/事件
|
||
- 主機/Docker 告警 → SSH MCP 查容器狀態/資源
|
||
|
||
2026-04-11 Claude Sonnet 4.6 Asia/Taipei
|
||
"""
|
||
if not incident.signals:
|
||
return ""
|
||
|
||
labels = incident.signals[0].labels
|
||
alertname = labels.get("alertname", "")
|
||
host = labels.get("instance", "").split(":")[0] or labels.get("host", "")
|
||
# C1 修復 2026-04-11 (Code Review): 修正 Python ternary 優先度問題
|
||
# 原: `A or B or C[0] if list else ""` → ternary 控制全式，非僅 C[0]
|
||
container = (
|
||
labels.get("name")
|
||
or labels.get("container")
|
||
or (incident.affected_services[0] if incident.affected_services else "")
|
||
)
|
||
ns = labels.get("namespace", "awoooi-prod")
|
||
|
||
ctx_parts: list[str] = []
|
||
|
||
# C2 修復 2026-04-11 (Code Review): 所有 MCP 呼叫加 5s timeout，防止阻塞決策主路徑
|
||
_MCP_TIMEOUT = 5.0
|
||
|
||
# 主機/Docker 告警 → SSH MCP 診斷
|
||
_HOST_ALERT_PREFIXES = ("Host", "Docker", "Sentry", "Harbor", "Ollama", "Backup")
|
||
if alertname.startswith(_HOST_ALERT_PREFIXES) and host:
|
||
try:
|
||
ssh = self._ssh
|
||
# C4: 未知主機記錄 warning（不靜默跳過）
|
||
# P0.4 fix 2026-04-24 ogt + Claude Sonnet 4.6: 補入 120/121，與 ssh_provider default 對齊
|
||
_KNOWN_HOSTS = ("192.168.0.188", "192.168.0.110", "192.168.0.120", "192.168.0.121")
|
||
if ssh.enabled and host not in _KNOWN_HOSTS:
|
||
logger.warning("mcp_context_unknown_host", host=host, known=_KNOWN_HOSTS)
|
||
if ssh.enabled and host in _KNOWN_HOSTS:
|
||
# 查容器狀態
|
||
if container and container != alertname:
|
||
status_result = await asyncio.wait_for(
|
||
ssh.execute(
|
||
tool_name="ssh_get_container_status",
|
||
# P0.4 fix 2026-04-24 ogt + Claude Sonnet 4.6: params= → parameters=（符合 MCPToolProvider.execute 簽名）
|
||
parameters={"host": host, "container_name": container},
|
||
),
|
||
timeout=_MCP_TIMEOUT,
|
||
)
|
||
# P0.4 fix 2026-04-24 ogt + Claude Sonnet 4.6: MCPToolResult 是 dataclass，用 .success/.output 而非 .get()
|
||
if status_result.success:
|
||
ctx_parts.append(f"[SSH] 容器 {container} 狀態: {(status_result.output or '')[:300]}")
|
||
# 查主機資源
|
||
if "CpuLoad" in alertname or "Memory" in alertname:
|
||
top_result = await asyncio.wait_for(
|
||
ssh.execute(
|
||
tool_name="ssh_get_top_processes",
|
||
# P0.4 fix 2026-04-24 ogt + Claude Sonnet 4.6: params= → parameters=
|
||
parameters={"host": host, "top_n": 5},
|
||
),
|
||
timeout=_MCP_TIMEOUT,
|
||
)
|
||
# P0.4 fix 2026-04-24 ogt + Claude Sonnet 4.6: MCPToolResult dataclass 用 .success/.output
|
||
if top_result.success:
|
||
ctx_parts.append(f"[SSH] 主機 {host} Top processes: {(top_result.output or '')[:300]}")
|
||
except asyncio.TimeoutError:
|
||
logger.warning("mcp_context_ssh_timeout", alertname=alertname, host=host, timeout=_MCP_TIMEOUT)
|
||
except Exception as e:
|
||
logger.debug("mcp_context_ssh_failed", alertname=alertname, error=str(e))
|
||
|
||
# K8s 告警 → K8s MCP 查 Pod 狀態
|
||
if alertname.startswith(("Kube", "K3s")) or labels.get("pod"):
|
||
try:
|
||
k8s = self._k8s
|
||
if k8s.enabled:
|
||
pod = labels.get("pod", "")
|
||
if pod:
|
||
events_result = await asyncio.wait_for(
|
||
k8s.execute(
|
||
tool_name="k8s_get_events",
|
||
# P0.4 fix 2026-04-24 ogt + Claude Sonnet 4.6: params= → parameters=
|
||
parameters={"namespace": ns, "field_selector": f"involvedObject.name={pod}"},
|
||
),
|
||
timeout=_MCP_TIMEOUT,
|
||
)
|
||
# P0.4 fix 2026-04-24 ogt + Claude Sonnet 4.6: MCPToolResult 是 dataclass，用 .success/.output
|
||
if events_result.success:
|
||
ctx_parts.append(f"[K8s] Pod {pod} 事件: {(events_result.output or '')[:300]}")
|
||
except asyncio.TimeoutError:
|
||
logger.warning("mcp_context_k8s_timeout", alertname=alertname, timeout=_MCP_TIMEOUT)
|
||
except Exception as e:
|
||
logger.debug("mcp_context_k8s_failed", alertname=alertname, error=str(e))
|
||
|
||
return "\n".join(ctx_parts)
|
||
|
||
async def _dual_engine_analyze(
|
||
self,
|
||
incident: Incident,
|
||
) -> dict[str, Any]:
|
||
"""
|
||
三軌決策分析 (Phase 7.5 升級 + KB Phase 2 RAG 整合 + ADR-070 MCP 前置收集)
|
||
|
||
策略:
|
||
1. MCP 前置收集真實環境狀態（ADR-070）
|
||
2. 先檢查 Playbook 是否有高度匹配 (similarity >= 85%)
|
||
3. Playbook 命中則直接使用 (最快、經驗驗證)
|
||
4. 否則 LLM + Expert System 雙軌 + KB RAG context + MCP context 注入
|
||
|
||
優先順序: Playbook > LLM > Expert System
|
||
"""
|
||
# ADR-081 Phase 1: PreDecisionInvestigator — 8D 感官蒐集（feature flag 守衛）
|
||
# AIOPS_P1_ENABLED=False → 退回舊 _collect_mcp_context() 路徑
|
||
# 2026-04-15 ogt + Claude Sonnet 4.6
|
||
evidence_snapshot = None
|
||
from src.core.feature_flags import aiops_flags
|
||
if aiops_flags.is_sub_flag_enabled("AIOPS_P1_PRE_DECISION_INVESTIGATOR"):
|
||
from src.services.pre_decision_investigator import get_pre_decision_investigator
|
||
investigator = get_pre_decision_investigator()
|
||
evidence_snapshot = await investigator.investigate(incident)
|
||
mcp_context = evidence_snapshot.evidence_summary or ""
|
||
else:
|
||
# ADR-070: 原有 MCP 收集路徑（Phase 0 保留）
|
||
mcp_context = await self._collect_mcp_context(incident)
|
||
|
||
# ADR-082 Phase 2: 5 Agent 辯證（feature flag 守衛）
|
||
# AIOPS_P2_ENABLED=True → 走 AgentOrchestrator 路徑，跳過 Playbook / LLM
|
||
# 需要 EvidenceSnapshot；若 P1 未開啟則自行收集
|
||
# 2026-04-15 ogt + Claude Sonnet 4.6（亞太）
|
||
if aiops_flags.is_phase_enabled(2): # Gate 2: 用 is_phase_enabled 統一父 Phase 守衛
|
||
p2_snapshot = evidence_snapshot
|
||
if p2_snapshot is None:
|
||
try:
|
||
from src.services.pre_decision_investigator import get_pre_decision_investigator
|
||
p2_snapshot = await get_pre_decision_investigator().investigate(incident)
|
||
except Exception:
|
||
logger.warning(
|
||
"p2_snapshot_collect_failed",
|
||
incident_id=incident.incident_id,
|
||
)
|
||
if p2_snapshot is not None:
|
||
from src.services.agent_orchestrator import run_agent_debate
|
||
package = await run_agent_debate(
|
||
snapshot=p2_snapshot,
|
||
incident_id=incident.incident_id,
|
||
)
|
||
return _package_to_proposal_data(package)
|
||
# snapshot 仍為 None → 降級繼續走原路徑（不阻塞）
|
||
logger.warning("p2_no_snapshot_fallback", incident_id=incident.incident_id)
|
||
|
||
# Phase 7.5: 先嘗試 Playbook 匹配
|
||
playbook_result = await self._try_playbook_match(incident)
|
||
if playbook_result:
|
||
return playbook_result
|
||
|
||
# MCP Phase 4c: Playbook 無命中 → 非同步產生 AI 草稿 Playbook (2026-04-11 Claude Sonnet 4.6)
|
||
_fire_and_forget(_generate_playbook_draft_if_new(incident))
|
||
|
||
# Expert System 同步執行 (立即可用)
|
||
expert_result = expert_analyze(incident)
|
||
|
||
# KB Phase 2: 語意搜尋相關知識條目 (失敗時靜默降級)
|
||
# 2026-04-04 Claude Code: KB RAG 整合，提升 LLM 決策品質
|
||
kb_context = await self._query_kb_context(incident)
|
||
|
||
# LLM 非同步執行 (Phase 22: OpenClaw + Nemotron 協作)
|
||
# 2026-03-31 Claude Code: 使用 _with_tools 方法啟用雙軌協作
|
||
try:
|
||
signals_dict = [s.model_dump() for s in incident.signals]
|
||
|
||
# 將 KB context + MCP 實時狀態 注入 expert_context 傳給 LLM
|
||
# ADR-070: MCP context 優先放最前面，讓 LLM 看到真實環境狀態再做決策
|
||
llm_expert_context: dict[str, Any] = {**expert_result} if expert_result else {}
|
||
existing = str(llm_expert_context.get("diagnosis_context", ""))
|
||
context_parts = []
|
||
if mcp_context:
|
||
context_parts.append(f"## 當前環境狀態 (MCP 實時查詢)\n{mcp_context}")
|
||
if kb_context:
|
||
context_parts.append(f"## 相關歷史知識\n{kb_context}")
|
||
if existing:
|
||
context_parts.append(existing)
|
||
if context_parts:
|
||
llm_expert_context["diagnosis_context"] = "\n\n".join(context_parts)
|
||
|
||
# GAP-B4 (2026-04-14 Claude Sonnet 4.6): LLM 25s hard timeout，
|
||
# 比外層 decide() 30s wait_for 更嚴格，留 5s 給 YAML risk override + NemoClaw second opinion
|
||
# Timeout → 明確 llm_timeout_fallback 日誌，返回 expert_result 而非等外層觸發
|
||
llm_result, provider, success = await asyncio.wait_for(
|
||
self._openclaw.generate_incident_proposal_with_tools(
|
||
incident_id=incident.incident_id,
|
||
severity=incident.severity.value,
|
||
signals=signals_dict,
|
||
affected_services=incident.affected_services,
|
||
expert_context=llm_expert_context if llm_expert_context else None,
|
||
),
|
||
timeout=25.0,
|
||
)
|
||
|
||
if success and llm_result:
|
||
logger.info(
|
||
"dual_engine_llm_win",
|
||
incident_id=incident.incident_id,
|
||
provider=provider,
|
||
kb_rag=bool(kb_context),
|
||
)
|
||
result = {**llm_result, "source": f"llm_{provider}"}
|
||
|
||
# ADR-073 Phase 3-6: YAML rule risk_level 優先於 LLM 輸出 (2026-04-12 ogt)
|
||
# LLM 有時把 critical 告警估為 medium，YAML 規則是由人工審閱過的，優先採用
|
||
try:
|
||
from src.services.alert_rule_engine import get_risk_for_alertname
|
||
_alertname_for_risk = (
|
||
incident.signals[0].labels.get("alertname", "")
|
||
if incident.signals else ""
|
||
)
|
||
if _alertname_for_risk:
|
||
_yaml_risk = get_risk_for_alertname(_alertname_for_risk)
|
||
if _yaml_risk and _yaml_risk != result.get("risk_level"):
|
||
logger.info(
|
||
"risk_level_yaml_override",
|
||
incident_id=incident.incident_id,
|
||
llm_risk=result.get("risk_level"),
|
||
yaml_risk=_yaml_risk,
|
||
)
|
||
result["risk_level"] = _yaml_risk
|
||
except Exception as _re:
|
||
logger.debug("risk_level_yaml_override_failed", error=str(_re))
|
||
|
||
# MCP Phase 4a: 信心 < 0.7 → NemoClaw second opinion (2026-04-11 Claude Sonnet 4.6)
|
||
_conf = float(result.get("confidence", 1.0))
|
||
if _conf < 0.7:
|
||
try:
|
||
# GAP-B4 (2026-04-14 Claude Sonnet 4.6): NemoClaw 是 advisory，
|
||
# 3s timeout 保護主決策流程不被拖累
|
||
_advisory = await asyncio.wait_for(
|
||
_nemoclaw_second_opinion(incident, result),
|
||
timeout=3.0,
|
||
)
|
||
if _advisory:
|
||
result["advisory_note"] = _advisory
|
||
logger.info(
|
||
"nemoclaw_second_opinion_added",
|
||
incident_id=incident.incident_id,
|
||
confidence=_conf,
|
||
)
|
||
except asyncio.TimeoutError:
|
||
logger.warning("nemoclaw_second_opinion_timeout",
|
||
incident_id=incident.incident_id)
|
||
except Exception as _soe:
|
||
logger.warning("nemoclaw_second_opinion_failed",
|
||
incident_id=incident.incident_id, error=str(_soe))
|
||
|
||
return result
|
||
|
||
except asyncio.TimeoutError:
|
||
# GAP-B4: LLM 超時 → 明確標記，降級 Expert System
|
||
logger.warning(
|
||
"llm_timeout_fallback",
|
||
incident_id=incident.incident_id,
|
||
timeout_sec=25.0,
|
||
action="降級 Expert System",
|
||
)
|
||
except Exception as e:
|
||
logger.warning(
|
||
"dual_engine_llm_failed",
|
||
incident_id=incident.incident_id,
|
||
error=str(e),
|
||
)
|
||
|
||
# LLM 失敗/超時，使用 Expert System
|
||
logger.info(
|
||
"dual_engine_expert_fallback",
|
||
incident_id=incident.incident_id,
|
||
)
|
||
return expert_result
|
||
|
||
async def _try_playbook_match(
|
||
self,
|
||
incident: Incident,
|
||
) -> dict[str, Any] | None:
|
||
"""
|
||
Phase 7.5: 嘗試 Playbook 匹配
|
||
|
||
條件:
|
||
- 相似度 >= PLAYBOOK_SIMILARITY_THRESHOLD (85%)
|
||
- Playbook 狀態為 APPROVED
|
||
- 成功率 >= 80% (如果有執行紀錄)
|
||
|
||
Returns:
|
||
匹配成功返回 proposal_data，否則 None
|
||
"""
|
||
try:
|
||
playbook_service = get_playbook_service()
|
||
|
||
# 建構症狀模式
|
||
alert_names = [s.alert_name for s in incident.signals] if incident.signals else []
|
||
symptoms = SymptomPattern(
|
||
alert_names=alert_names,
|
||
affected_services=incident.affected_services or [],
|
||
severity_range=[incident.severity.value] if incident.severity else ["P2"],
|
||
)
|
||
|
||
# 取得推薦 (只取 Top 1)
|
||
recommendations = await playbook_service.get_recommendations(
|
||
symptoms=symptoms,
|
||
top_k=1,
|
||
)
|
||
|
||
if not recommendations:
|
||
logger.debug(
|
||
"playbook_no_match",
|
||
incident_id=incident.incident_id,
|
||
)
|
||
return None
|
||
|
||
best_match = recommendations[0]
|
||
playbook = best_match.playbook
|
||
|
||
# 檢查相似度閾值
|
||
if best_match.similarity_score < PLAYBOOK_SIMILARITY_THRESHOLD:
|
||
logger.debug(
|
||
"playbook_similarity_below_threshold",
|
||
incident_id=incident.incident_id,
|
||
playbook_id=playbook.playbook_id,
|
||
similarity=best_match.similarity_score,
|
||
threshold=PLAYBOOK_SIMILARITY_THRESHOLD,
|
||
)
|
||
return None
|
||
|
||
# 檢查成功率 (如果有執行紀錄)
|
||
if playbook.total_executions > 0 and playbook.success_rate < 0.8:
|
||
logger.debug(
|
||
"playbook_low_success_rate",
|
||
incident_id=incident.incident_id,
|
||
playbook_id=playbook.playbook_id,
|
||
success_rate=playbook.success_rate,
|
||
)
|
||
return None
|
||
|
||
# Playbook 命中！
|
||
# 取得第一個修復步驟的指令
|
||
kubectl_command = ""
|
||
if playbook.repair_steps:
|
||
# 將 target 替換為實際服務名稱
|
||
target = incident.affected_services[0] if incident.affected_services else "unknown"
|
||
kubectl_command = playbook.repair_steps[0].command.format(target=target)
|
||
|
||
logger.info(
|
||
"playbook_match_success",
|
||
incident_id=incident.incident_id,
|
||
playbook_id=playbook.playbook_id,
|
||
playbook_name=playbook.name,
|
||
similarity=best_match.similarity_score,
|
||
success_rate=playbook.success_rate,
|
||
)
|
||
|
||
return {
|
||
"source": "playbook",
|
||
"playbook_id": playbook.playbook_id,
|
||
"playbook_name": playbook.name,
|
||
"action": kubectl_command,
|
||
"kubectl_command": kubectl_command,
|
||
"description": playbook.description,
|
||
"risk_level": playbook.repair_steps[0].risk_level.value.lower() if playbook.repair_steps else "medium",
|
||
"reasoning": f"Playbook 匹配 ({best_match.similarity_score:.0%} 相似度, {playbook.success_rate:.0%} 成功率): {best_match.reason}",
|
||
"confidence": 0.0, # 🔴 Playbook RAG 匹配不是 AI 分析，信心度設 0
|
||
"matched_symptoms": best_match.matched_symptoms,
|
||
"from_cache": False,
|
||
}
|
||
|
||
except Exception as e:
|
||
logger.warning(
|
||
"playbook_match_error",
|
||
incident_id=incident.incident_id,
|
||
error=str(e),
|
||
)
|
||
return None
|
||
|
||
async def _find_existing_token(
|
||
self,
|
||
incident_id: str,
|
||
) -> DecisionToken | None:
|
||
"""查找現有的決策令牌"""
|
||
redis_client = get_redis()
|
||
|
||
# 掃描 decision:* 找到匹配的 incident_id
|
||
cursor = 0
|
||
while True:
|
||
cursor, keys = await redis_client.scan(
|
||
cursor=cursor,
|
||
match=f"{DECISION_TOKEN_PREFIX}*",
|
||
count=100,
|
||
)
|
||
|
||
for key in keys:
|
||
try:
|
||
import json
|
||
data = await redis_client.get(key)
|
||
if data:
|
||
token_data = json.loads(data)
|
||
if token_data.get("incident_id") == incident_id:
|
||
return DecisionToken.from_dict(token_data)
|
||
except Exception:
|
||
continue
|
||
|
||
if cursor == 0:
|
||
break
|
||
|
||
return None
|
||
|
||
async def _persist_decision_to_db(
|
||
self, incident_id: str, proposal_data: dict
|
||
) -> None:
|
||
"""
|
||
2026-04-16 Claude Sonnet 4.6: 將 AI 分析結果寫入 incidents.decision_chain (PostgreSQL)
|
||
修復 Gap: decision token 只有 Redis TTL，AI 分析歷史永久丟失
|
||
|
||
寫入格式: JSON array，每次分析追加一條記錄
|
||
欄位: ts / confidence / risk_level / provider / source / diagnosis (前 200 字)
|
||
"""
|
||
try:
|
||
from src.db.base import get_db_context
|
||
from sqlalchemy import text as _sa_text
|
||
import json as _json
|
||
from src.utils.timezone import now_taipei
|
||
|
||
# 2026-04-16 ogt + Claude Sonnet 4.6: 補入 playbook_id / alert_category (ADR-076)
|
||
entry = {
|
||
"ts": now_taipei().isoformat(),
|
||
"confidence": proposal_data.get("confidence", 0.0),
|
||
"risk_level": proposal_data.get("risk_level", "unknown"),
|
||
"provider": proposal_data.get("provider", proposal_data.get("source", "")),
|
||
"source": proposal_data.get("source", ""),
|
||
"diagnosis": str(proposal_data.get("diagnosis", proposal_data.get("description", "")))[:200],
|
||
"playbook_id": proposal_data.get("playbook_id", ""),
|
||
"playbook_name": proposal_data.get("playbook_name", ""),
|
||
"alert_category": proposal_data.get("alert_category", ""),
|
||
}
|
||
|
||
async with get_db_context() as db:
|
||
# 讀取現有 decision_chain (可能為 null 或 json array)
|
||
r = await db.execute(
|
||
_sa_text(
|
||
"SELECT decision_chain FROM incidents WHERE incident_id = :iid"
|
||
),
|
||
{"iid": incident_id},
|
||
)
|
||
row = r.fetchone()
|
||
if row is None:
|
||
return
|
||
existing = row[0] or []
|
||
if isinstance(existing, str):
|
||
try:
|
||
existing = _json.loads(existing)
|
||
except Exception:
|
||
existing = []
|
||
if not isinstance(existing, list):
|
||
existing = []
|
||
existing.append(entry)
|
||
|
||
# asyncpg 不支援 :param::type 語法，改用 CAST(:param AS jsonb)
|
||
# 2026-04-16 Claude Sonnet 4.6: fix syntax error at or near ":"
|
||
await db.execute(
|
||
_sa_text(
|
||
"UPDATE incidents SET decision_chain = CAST(:dc AS jsonb) WHERE incident_id = :iid"
|
||
),
|
||
{"dc": _json.dumps(existing), "iid": incident_id},
|
||
)
|
||
await db.commit()
|
||
logger.debug(
|
||
"decision_chain_persisted",
|
||
incident_id=incident_id,
|
||
confidence=entry["confidence"],
|
||
provider=entry["provider"],
|
||
)
|
||
except Exception as e:
|
||
logger.warning("decision_chain_persist_failed", incident_id=incident_id, error=str(e))
|
||
|
||
async def _save_token(self, token: DecisionToken, ttl: int = DECISION_TOKEN_TTL) -> None:
|
||
"""儲存決策令牌到 Redis
|
||
|
||
ttl: 過期秒數，預設 DECISION_TOKEN_TTL (3600s)
|
||
TYPE-1 純資訊通知使用 86400s (24h) 防重複洗版
|
||
"""
|
||
import json
|
||
redis_client = get_redis()
|
||
key = f"{DECISION_TOKEN_PREFIX}{token.token}"
|
||
|
||
await redis_client.set(
|
||
key,
|
||
json.dumps(token.to_dict()),
|
||
ex=ttl,
|
||
)
|
||
|
||
async def get_token(self, token_id: str) -> DecisionToken | None:
|
||
"""取得決策令牌"""
|
||
import json
|
||
redis_client = get_redis()
|
||
key = f"{DECISION_TOKEN_PREFIX}{token_id}"
|
||
|
||
data = await redis_client.get(key)
|
||
if data:
|
||
return DecisionToken.from_dict(json.loads(data))
|
||
return None
|
||
|
||
async def update_token_state(
|
||
self,
|
||
token_id: str,
|
||
new_state: DecisionState,
|
||
proposal_id: str | None = None,
|
||
) -> DecisionToken | None:
|
||
"""更新決策狀態"""
|
||
token = await self.get_token(token_id)
|
||
if not token:
|
||
return None
|
||
|
||
token.state = new_state
|
||
token.updated_at = datetime.now(UTC)
|
||
if proposal_id:
|
||
token.proposal_id = proposal_id
|
||
|
||
await self._save_token(token)
|
||
return token
|
||
|
||
async def get_or_create_decision_with_consensus(
|
||
self,
|
||
incident: Incident,
|
||
timeout_sec: float = 30.0,
|
||
use_consensus: bool = True,
|
||
) -> DecisionToken:
|
||
"""
|
||
取得或建立決策令牌 (含 Agent Teams 共識)
|
||
|
||
Phase 9.4 升級版本:
|
||
- 對於 P0/P1 事件，自動啟用 ConsensusEngine
|
||
- 整合多專家意見
|
||
- 共識分數影響風險評估
|
||
|
||
Args:
|
||
incident: 事件
|
||
timeout_sec: 超時秒數
|
||
use_consensus: 是否使用共識引擎 (預設 True)
|
||
|
||
Returns:
|
||
DecisionToken
|
||
"""
|
||
# 判斷是否需要共識 (P0/P1 或明確要求)
|
||
should_use_consensus = use_consensus and incident.severity.value in ["P0", "P1"]
|
||
|
||
if not should_use_consensus:
|
||
# 使用原有的雙軌決策
|
||
return await self.get_or_create_decision(incident, timeout_sec)
|
||
|
||
# Phase 9.4: 使用 ConsensusEngine
|
||
from src.services.consensus_engine import get_consensus_engine
|
||
|
||
consensus_engine = get_consensus_engine()
|
||
|
||
# 檢查現有 token
|
||
existing_token = await self._find_existing_token(incident.incident_id)
|
||
if existing_token:
|
||
# READY 或 EXECUTING 狀態: 直接返回
|
||
if existing_token.state in (DecisionState.READY, DecisionState.EXECUTING):
|
||
return existing_token
|
||
# COMPLETED 狀態: 直接返回，避免重複建立 decision 導致 Telegram 轟炸
|
||
if existing_token.state == DecisionState.COMPLETED:
|
||
return existing_token
|
||
|
||
# 建立新 token
|
||
token = DecisionToken(
|
||
token=f"DEC-{uuid4().hex[:12].upper()}",
|
||
incident_id=incident.incident_id,
|
||
state=DecisionState.ANALYZING,
|
||
)
|
||
await self._save_token(token)
|
||
|
||
logger.info(
|
||
"decision_analyzing_with_consensus",
|
||
token=token.token,
|
||
incident_id=incident.incident_id,
|
||
)
|
||
|
||
try:
|
||
# 執行共識分析
|
||
consensus_result = await asyncio.wait_for(
|
||
consensus_engine.run_consensus(incident, timeout_sec),
|
||
timeout=timeout_sec,
|
||
)
|
||
|
||
# 轉換為 proposal_data 格式
|
||
proposal_data = {
|
||
"source": "consensus_engine",
|
||
"consensus_id": consensus_result.consensus_id,
|
||
"consensus_score": consensus_result.consensus_score,
|
||
"action": consensus_result.recommended_action,
|
||
"description": consensus_result.final_reasoning,
|
||
"risk_level": consensus_result.risk_level,
|
||
"kubectl_command": consensus_result.recommended_kubectl,
|
||
"reasoning": consensus_result.final_reasoning,
|
||
"confidence": 0.0, # 🔴 Consensus Engine 共識分數不是 AI 信心度，設 0
|
||
"agent_count": len(consensus_result.opinions),
|
||
"dissenting_opinions": consensus_result.dissenting_opinions,
|
||
"from_cache": False,
|
||
}
|
||
|
||
token.state = DecisionState.READY
|
||
token.proposal_data = proposal_data
|
||
token.updated_at = datetime.now(UTC)
|
||
|
||
logger.info(
|
||
"decision_ready_with_consensus",
|
||
token=token.token,
|
||
consensus_id=consensus_result.consensus_id,
|
||
consensus_score=consensus_result.consensus_score,
|
||
)
|
||
|
||
except TimeoutError:
|
||
logger.warning(
|
||
"consensus_timeout_using_expert",
|
||
token=token.token,
|
||
timeout_sec=timeout_sec,
|
||
)
|
||
# Fallback 到 Expert System
|
||
expert_result = expert_analyze(incident)
|
||
token.state = DecisionState.READY
|
||
token.proposal_data = expert_result
|
||
token.updated_at = datetime.now(UTC)
|
||
|
||
except Exception as e:
|
||
logger.exception(
|
||
"consensus_error_using_expert",
|
||
token=token.token,
|
||
error=str(e),
|
||
)
|
||
expert_result = expert_analyze(incident)
|
||
token.state = DecisionState.READY
|
||
token.proposal_data = expert_result
|
||
token.error = str(e)
|
||
token.updated_at = datetime.now(UTC)
|
||
|
||
await self._save_token(token)
|
||
return token
|
||
|
||
async def resend_stale_ready_tokens(self) -> int:
|
||
"""
|
||
BUG-005 修復 2026-04-11: 掃描 Redis 中所有 state=ready 且 dedup_key 不存在的 token，
|
||
重新推送 Telegram 審核卡片。
|
||
觸發時機：API 啟動（lifespan startup）+ 管理 API 手動呼叫。
|
||
|
||
2026-04-14 Claude Sonnet 4.6 修復: 加並發限制防止 Pod 啟動時壓爆 Ollama
|
||
- 原 fire_and_forget 同時啟動 N 個 task → N=108 時 Ollama embedding 全部 timeout
|
||
- 改 Semaphore 限 5 並發 + 每批 sleep 1s，總體 throughput 降低但系統穩定
|
||
|
||
Returns:
|
||
重新推送的 token 數量
|
||
"""
|
||
import asyncio as _asyncio
|
||
import json as _json
|
||
from src.core.redis_client import get_redis
|
||
from src.db.base import get_db_context
|
||
from src.repositories.incident_repository import IncidentDBRepository
|
||
|
||
redis = get_redis()
|
||
resent = 0
|
||
# GAP-A4 後續修復：限制並發 5，避免壓爆 Ollama
|
||
_sem = _asyncio.Semaphore(5)
|
||
|
||
async def _bounded_push(incident_obj, proposal_data_obj, _id, _token):
|
||
async with _sem:
|
||
try:
|
||
await _push_decision_to_telegram(incident_obj, proposal_data_obj)
|
||
logger.info(
|
||
"stale_ready_token_resent",
|
||
incident_id=_id,
|
||
token=_token,
|
||
)
|
||
except Exception as _e:
|
||
logger.warning(
|
||
"stale_ready_token_resend_failed",
|
||
incident_id=_id,
|
||
error=str(_e),
|
||
)
|
||
# 每次完成後喘 200ms，給 Ollama embedding 恢復空間
|
||
await _asyncio.sleep(0.2)
|
||
|
||
try:
|
||
# 掃描所有 decision:* key
|
||
cursor = 0
|
||
tasks: list[_asyncio.Task] = []
|
||
while True:
|
||
cursor, keys = await redis.scan(cursor, match="decision:*", count=200)
|
||
for key in keys:
|
||
try:
|
||
raw = await redis.get(key)
|
||
if not raw:
|
||
continue
|
||
data = _json.loads(raw)
|
||
if data.get("state") != DecisionState.READY.value:
|
||
continue
|
||
|
||
incident_id = data.get("incident_id", "")
|
||
dedup_key = f"telegram_sent:{incident_id}"
|
||
if await redis.exists(dedup_key):
|
||
continue # dedup 還在，跳過
|
||
|
||
# 取 Incident 資料（確認未 resolved）
|
||
async with get_db_context() as _db:
|
||
incident = await IncidentDBRepository(_db).get_by_id(incident_id)
|
||
if not incident:
|
||
continue
|
||
if str(getattr(incident, "status", "")).lower() in ("resolved", "closed"):
|
||
continue
|
||
|
||
# 2026-04-15 Claude Sonnet 4.6 (節點 3 修復):
|
||
# 跳過 > 3 天的 stale incident — labels 已過時，重 process 無意義
|
||
# 只會壓爆 Ollama + 污染 Telegram 卡片（截圖：4/11 的卡片今天還在彈）
|
||
_STALE_DAYS = 3
|
||
_created_at = getattr(incident, "created_at", None)
|
||
if _created_at:
|
||
from datetime import datetime as _dt, timedelta as _td, timezone as _tz
|
||
_now = _dt.now(_tz.utc)
|
||
_cutoff = _now - _td(days=_STALE_DAYS)
|
||
# 確保 _created_at 有時區
|
||
if _created_at.tzinfo is None:
|
||
_created_at = _created_at.replace(tzinfo=_tz.utc)
|
||
if _created_at < _cutoff:
|
||
logger.debug(
|
||
"stale_ready_token_skipped_too_old",
|
||
incident_id=incident_id,
|
||
age_days=(_now - _created_at).days,
|
||
cutoff_days=_STALE_DAYS,
|
||
)
|
||
continue
|
||
|
||
proposal_data = data.get("proposal_data") or {}
|
||
if not proposal_data:
|
||
continue
|
||
|
||
# 用 Semaphore 限制並發，task 自帶 throttle
|
||
_task = _asyncio.create_task(
|
||
_bounded_push(incident, proposal_data, incident_id, data.get("token", ""))
|
||
)
|
||
tasks.append(_task)
|
||
resent += 1
|
||
except Exception as _te:
|
||
logger.debug("stale_ready_token_scan_error", error=str(_te))
|
||
|
||
if cursor == 0:
|
||
break
|
||
|
||
# 不等所有 task 完成（fire-and-forget 語義保留），但 await 一下讓並發限制生效
|
||
if tasks:
|
||
logger.info("stale_ready_tokens_throttled_dispatch",
|
||
total=len(tasks), max_concurrent=5)
|
||
|
||
except Exception as e:
|
||
logger.warning("resend_stale_ready_tokens_failed", error=str(e))
|
||
|
||
logger.info("stale_ready_tokens_scan_done", resent=resent)
|
||
return resent
|
||
|
||
async def _ssh_execute(
|
||
self,
|
||
incident: "Incident",
|
||
token: "DecisionToken",
|
||
action: str,
|
||
target: str,
|
||
) -> None:
|
||
"""
|
||
ADR-073 Phase 3-2: infrastructure 告警 SSH MCP routing
|
||
Docker/Host 告警走 SSH MCP Provider，不走 K8s executor
|
||
2026-04-12 ogt
|
||
|
||
支援指令:
|
||
- docker restart <container>
|
||
- systemctl restart <service>
|
||
- docker rm -f <container> (含 docker start)
|
||
"""
|
||
import os as _os
|
||
|
||
# 取得主機 — 從 instance label 或 SSH_MCP_ALLOWED_HOSTS 第一台
|
||
_instance = incident.signals[0].labels.get("instance", "") if incident.signals else ""
|
||
_host = _instance.split(":")[0] if ":" in _instance else _instance
|
||
_allowed = [h.strip() for h in _os.environ.get("SSH_MCP_ALLOWED_HOSTS", "").split(",") if h.strip()]
|
||
if not _host or _host not in _allowed:
|
||
_host = _allowed[0] if _allowed else ""
|
||
|
||
if not _host:
|
||
logger.warning(
|
||
"ssh_execute_no_host",
|
||
incident_id=incident.incident_id,
|
||
reason="SSH_MCP_ALLOWED_HOSTS 未設定或 instance label 不在白名單",
|
||
)
|
||
token.state = DecisionState.READY
|
||
token.proposal_data["decision_state"] = DecisionState.READY.value
|
||
token.proposal_data["auto_executed"] = False
|
||
token.proposal_data["mcp_all_failed"] = True
|
||
await self._save_token(token)
|
||
_fire_and_forget(_push_decision_to_telegram(incident, token.proposal_data))
|
||
return
|
||
|
||
# 解析 SSH tool + params
|
||
_action_lower = action.lower().strip()
|
||
if _action_lower.startswith("docker restart"):
|
||
_tool = "docker_restart"
|
||
_container = target
|
||
elif _action_lower.startswith("systemctl restart"):
|
||
_tool = "service_restart"
|
||
_service = target
|
||
else:
|
||
logger.info(
|
||
"ssh_execute_unknown_action",
|
||
incident_id=incident.incident_id,
|
||
action=action,
|
||
reason="不支援的 SSH action 格式，降級為人工審核",
|
||
)
|
||
token.state = DecisionState.READY
|
||
token.proposal_data["decision_state"] = DecisionState.READY.value
|
||
token.proposal_data["auto_executed"] = False
|
||
await self._save_token(token)
|
||
_fire_and_forget(_push_decision_to_telegram(incident, token.proposal_data))
|
||
return
|
||
|
||
params: dict = {"host": _host}
|
||
if _tool == "docker_restart":
|
||
params["container"] = _container
|
||
else:
|
||
params["service"] = _service
|
||
|
||
try:
|
||
result = await self._ssh.execute(tool_name=_tool, parameters=params)
|
||
success = result.success
|
||
|
||
logger.info(
|
||
"ssh_execute_result",
|
||
incident_id=incident.incident_id,
|
||
tool=_tool,
|
||
host=_host,
|
||
success=success,
|
||
output=result.output[:200] if result.output else "",
|
||
)
|
||
|
||
token.state = DecisionState.COMPLETED
|
||
token.proposal_data["auto_executed"] = True
|
||
await self._save_token(token)
|
||
|
||
_fire_and_forget(
|
||
_push_auto_repair_result(incident, action, success=success)
|
||
)
|
||
|
||
except Exception as e:
|
||
logger.error(
|
||
"ssh_execute_failed",
|
||
incident_id=incident.incident_id,
|
||
error=str(e),
|
||
)
|
||
token.state = DecisionState.READY
|
||
token.error = str(e)
|
||
token.proposal_data["decision_state"] = DecisionState.READY.value
|
||
token.proposal_data["auto_executed"] = False
|
||
await self._save_token(token)
|
||
_fire_and_forget(_push_decision_to_telegram(incident, token.proposal_data))
|
||
|
||
|
||
# =============================================================================
|
||
# Singleton
|
||
# =============================================================================
|
||
|
||
_decision_manager: DecisionManager | None = None
|
||
|
||
|
||
def get_decision_manager() -> DecisionManager:
|
||
"""取得 DecisionManager 實例 (Singleton)"""
|
||
global _decision_manager
|
||
if _decision_manager is None:
|
||
_decision_manager = DecisionManager()
|
||
return _decision_manager
|