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dbd4470b6d chore(aider): 新增 .aiderignore 縮小 repo-map 並開放追蹤 
大型 repo（1,165 檔）讓 Aider 啟動即吃 267K tokens。加入 .aiderignore
排除 docs/k8s/infra/ops/media 後，repo-map 從 1,165 → ~782 檔案（-33%）。
同步在 .gitignore 加 !.aiderignore 例外，讓本檔可被追蹤共享給團隊。

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-20 04:04:13 +08:00
AWOOOI CD
a837172fd5 chore(cd): deploy f572561 [skip ci] 2026-04-19 15:10:19 +00:00
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f572561467 feat(ai_advisory): P0 修 leader lock + inline keyboard + callback handler
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統帥 2026-04-19 截圖反饋:
  1. 同一告警 22:44 連推 2 則 (多 Pod 都跑 daily loop)
  2. 純文字無按鈕 (無 feedback 閉環 / AI 只建議不執行)

新增 services/ai_advisory_helpers.py (~240 行):
  - try_acquire_daily_lock(job_name): Redis SETNX key 'aiops:daily_lock:{job}:{date}',
    TTL 25h,fail-open (Redis 掛照推,不阻塞).
  - try_acquire_hourly_lock(job_name): 同上 hourly 版 (coverage_evaluator 用).
  - is_snoozed / set_snooze: Redis key 'aiops:snooze:{type}:{target}' TTL 24h.
  - build_ai_advisory_keyboard: 統一 4 按鈕
      ✅ 已處理 / 😴 忽略 24h / 🔍 查看詳情 / 📋 產 kubectl 指令
    callback_data 格式: 'ai_advisory_{action}:{type}:{id}'
  - handle_ai_advisory_callback: 處理 handled/snooze 兩個 action 寫 aol.output.human_feedback,
    view/produce_cmd 留 P1.

4 個 LLM scanner 改用 helper:
  - capacity_forecaster: daily_lock + snooze check per host + 按鈕
  - compliance_scanner: daily_lock (cron only) + snooze per date + 按鈕
  - coverage_evaluator: hourly_lock + snooze per worst_dimension + 按鈕
  - hermes_rule_quality: daily_lock + snooze per primary rule + 按鈕

telegram_gateway.py:
  handle_callback 加 'ai_advisory_*' 路由 (step 1.85 drift 後)
  新增 _handle_ai_advisory_action 方法:
    解析 payload 'type:id' → 呼叫 handle_ai_advisory_callback
    → answer_callback (Telegram toast 回饋)
    → 返回 dict (info_action=True for view/produce_cmd)

統帥鐵律對齊:
  ✅ 多 Pod 場景只 leader 推 (Redis SETNX 保證冪等)
  ✅ 失敗 fail-open 不阻塞主業務 (Redis 掛仍能運作)
  ✅ aol.output 加 human_feedback 供 AI 學習
  ✅ snooze 避免重複告警 (24h TTL)
  ✅ 原 drift 按鈕 pattern 複用 (non-breaking)

明早 AI 將收到:
  - 單一訊息 (非重複)
  - 含 4 按鈕 (手動 feedback 閉環)
  - snooze 後同主題 24h 不再推

view/produce_cmd P1 留下 session (AI 主動 MCP 蒐證 + LLM 產 kubectl command).

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 23:02:57 +08:00
AWOOOI CD
b9068d495f chore(cd): deploy fa643eb [skip ci] 2026-04-19 14:47:23 +00:00
Your Name
712d146129 docs(adr+skills): ADR-092 AI Decision LLM 層 + Skill 03 更新統一 LLM pattern 
首席架構師 2026-04-19 Review 92/100 Grade A 後的完整文檔化:

**ADR-092 新建 (AI Decision LLM 擴展架構)**:
  - 背景: 14 scanner 中 8 個純 threshold,違反 feedback_ai_autonomous_direction
  - 決策: 4 個 LLM service + 統一 pattern (llm_json_parser)
  - 約束 5 鐵律: 失敗不 raise / AI 只建議不動作 / openclaw 統一入口 /
                aol 留痕 / 繁中 + JSON schema
  - 節流: Daily cron + 事件觸發 (red_ratio>30% 且 scanned>=50)
  - autonomy_score 0-100 量化追蹤
  - 實作成果 + P1 剩餘 + 回滾計畫

**Skill 03 openclaw-cognitive-expert 更新**:
  - 新增「2026-04-19 AI Decision LLM 擴展層」章節
  - Pattern code 範本 (不是每次重寫 3-path parse)
  - 4 LLM service 對照表 + required_key
  - 擴加 5 鐵律清單
  - autonomy_score 追蹤使用說明

下 session Claude 接手時能快速看到 LLM service pattern,不會重複造輪子.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 22:42:58 +08:00
Your Name
55486ce2fd docs: aider-watch 實作計畫（15 tasks，TDD + 頻繁 commit） 
對應 spec 2026-04-19-aider-watch-design.md 的完整 §1-§7 拆解：
scaffold → events schema → redactor → config → tg format/send → PG DDL
→ storage → parsers → wrapper → CLI → reporter → launchd → install → E2E。

每個 task 含 TDD 步驟（測試先行 → 驗失敗 → 實作 → 驗通過 → commit）。

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 22:42:41 +08:00
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fa643ebdc7 refactor(p1): LLM JSON parse helper 抽出 + coverage 閾值雙條件 (架構師 Review P1)
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首席架構師 2026-04-19 Review (92/100 Grade A) 指出 P1 優化:
  1. LLM JSON 3-path parse 邏輯在 4 scanner 重複 (~80 行 × 4 = 320 行)
  2. coverage red>=20 觸發閾值偏低,生產 bootstrap 必觸發浪費 token

P1.1+1.2 新增 services/llm_json_parser.py (~90 行):
  parse_llm_json_response(text, required_key, logger_context)
  3-path fallback:
    Path 1: 剝 markdown fence + 直接 JSON 含 required_key
    Path 2: NemoTron wrapper (description/action_title/reasoning 內嵌 JSON)
    Path 3: 所有失敗 return None + logger.warning
  失敗永不 raise,呼叫者決定 fallback.

4 個 LLM scanner 改用 helper:
  - hermes_rule_quality_job: required_key='recommended_actions'
  - capacity_forecaster_job: required_key='priority_actions'
  - compliance_scanner_job: required_key='posture_grade'
  - coverage_evaluator_job: required_key='worst_dimension'
每個減少約 20 行重複.

P1.3 coverage 觸發條件改雙條件:
  原: total_red >= 20 (bootstrap 必觸發)
  新: red_ratio > 30% AND total_scanned >= 50
  _fetch_red_summary 加 total_scanned 回傳供計算.

5/5 單元測試 parse_llm_json_response:
  ✅ direct / markdown fence / NemoTron wrapper / invalid / missing key

P1.4 capacity_scanner + rule_catalog_sync: 檢查後已有完整作者註解 (Review 誤判).
其他 P1 (Prom HTTP helper / first_delay 錯開 / LLM budget guard) 留下 session.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 22:39:40 +08:00
Your Name
8603bce23b docs: aider-watch 設計稿（統帥批准的 §1-§7 定稿） 
aider CLI 全程監控系統：Python wrapper 攔 aider stdout + chat history
→ Telegram DM 即時推播（session start/end/file edit/error/commit/silent
timeout）+ PG 192.168.0.188/aider_watch 累積儲存 + 每日 23:50/每週日
22:00 launchd 日週報。

Graceful degradation：PG 不可達 fallback 本機 JSONL buffer + 5min
flush job；Telegram 429 指數退避不阻塞 aider；secret pattern 自動遮罩。

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 22:39:40 +08:00
AWOOOI CD
2af623032a chore(cd): deploy 37b6c9b [skip ci] 2026-04-19 14:31:48 +00:00
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37b6c9ba56 chore: remove empty ai_orchestrator.py (意外進 commit 的空檔)
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上個 commit (86d9b22 LOGBOOK) 因 stash pop 意外帶入 0 行空檔
ai_orchestrator.py,非刻意創建。本次刪除保持 services/ 乾淨。

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 22:22:53 +08:00
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86d9b22125 docs(logbook): Session 結尾 — Gap Review + AI 自主化 1/9→4/9 全景記錄
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Session 35 commits 完整結案:
  - Phase 7 基礎 (scanners + evaluator + tracker + advisor + forecaster)
  - KPI Dashboard API (autonomy_score 63/100 可量化)
  - Audit 誠實 3 Gaps
  - Gap 1 host IPv4 嚴格 + 清理 266 筆重複
  - Gap 2 真因確認非 bug
  - Gap 3 LLM 升級 3/8 (capacity_forecaster/compliance/coverage)

AI 自主化達成:
  1/9 LLM (只 Hermes) → 4/9 LLM decision
  8 張 0 writer 表全活化
  7/7 coverage 維度完整
  今晚 AI 將自主推 4 種 Telegram 分析報告

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 22:22:42 +08:00
AWOOOI CD
b9c4896c7f chore(cd): deploy 2f5cab2 [skip ci] 2026-04-19 14:10:25 +00:00
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2f5cab2e45 feat(coverage_evaluator): Gap 3.3 LLM 升級 — 缺口分析 + 補覆蓋建議
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Gap 3 進度: 4/9 service 升級 LLM (達到合理上限 — 其他 4 個純資料移動不需 LLM)

coverage_evaluator 原本 7 維升級 unknown→green/yellow/red 後無主動建議.
新增:

1. _fetch_red_summary: 撈最新 run 的 red 分布 + top 10 被標 red 的 asset
2. _llm_analyze_coverage_gaps (~50 行):
   有 >= 20 red 時才跑 LLM (避免 well-covered 集群浪費 token)
   LLM JSON 輸出:
     - worst_dimension: 最該優先補的維度
     - root_cause: red 集中的真因 (繁中)
     - top_remediation_actions[3]: priority/target/action/effort
     - estimated_weeks_to_close: 1-52
     - confidence: 0-1
3. _send_telegram_gaps: 推 coverage 缺口 Telegram 摘要
   總 red + 最嚴重維度 + 補齊週數 + top 3 補覆蓋動作

scan 完流程:
  評估 7 維 → 撈 red summary → LLM 分析 (if total_red >= 20) → Telegram

統帥鐵律對齊:
  ✅ 不寫死補覆蓋優先 (LLM 根據實際 red 分布推)
  ✅ AI 建議 + 人工決策 (Telegram 末行: '人工評估補覆蓋排程')
  ✅ 包含預估完成時間 + 信心 (可追蹤)

session 累計 35 commits, 9 新 scanner, 4 用 LLM:
  - Hermes (rule quality)
  - capacity_forecaster (容量預測)
  - compliance_scanner (合規態勢)
  - coverage_evaluator (覆蓋缺口)
剩 5 個純資料移動不適合 LLM (asset_scanner/rule_catalog_sync/
                           rule_stats_updater/asset_change_tracker/capacity_scanner)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 22:02:36 +08:00
Your Name
f6cb938dc3 feat(compliance_scanner): Gap 3.2 LLM 升級 — 合規態勢分析 + Telegram 摘要
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朝 AI 自主化方向 — 9 新 scanner 從 2/9 LLM 提升到 3/9.

compliance_scanner 原本每次 scan 273 snapshots 寫 DB,無任何人可見摘要.
新增:

1. _write_compliance_for_asset_v2 (wrapper):
   原 _write_compliance_for_asset 保持不變,v2 版加回傳 asset_warning dict
   供上層 LLM 分析用,只有 violations/warnings > 0 才傳回

2. _llm_analyze_compliance_posture (~50 行):
   有 warning 時用 OpenClaw 分析整體 posture
   輸出 JSON:
     - posture_grade: A/B/C/D/F
     - posture_summary: 3 句繁中整體態勢敘述
     - top_priorities[3]: priority + action + rationale
     - risk_level: low/medium/high/critical
     - confidence: 0-1
   3-path JSON parse fallback (直接 / NemoTron wrapper / description 巢狀)

3. _send_telegram_posture (~40 行):
   推每日合規摘要到 SRE group
   含評級 emoji (🟢A / 🟡B / 🟠C / 🔴D / ⛔F)
   顯示 asset_type 分布 (Top 5 種問題類型統計)
   含 AI top 3 priority 動作 + rationale

scan_once 流程:
  掃 assets × 7 維 → 收集 warning_assets → LLM 分析 → Telegram 推送

統帥鐵律對齊:
  ✅ AI 分析 + 人工決策 (Telegram 末行: '人工評估各項修復優先')
  ✅ 不寫死優先順序 (LLM 根據 warnings 實際分布推)
  ✅ asset_type 分布統計幫統帥快速定位

Gap 3 進度: 3/8 service 升級 LLM (Hermes + capacity_forecaster + compliance_scanner)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 21:59:38 +08:00
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d6b854a25e feat(capacity_forecaster): Gap 3 LLM 升級 — 從 threshold 到 AI 決策
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Audit 發現 8/9 個新 scanner 是純 threshold,只 Hermes 1 個用 LLM.
統帥指示「朝 AI 自主化方向」→ Gap 3 開始把 threshold 升級 LLM.

第 1 個升級: capacity_forecaster (最高戰略)
原邏輯 _derive_actions 是硬編 keyword → action mapping:
  disk → "清理 /var/log, /var/lib/docker, PG WAL"
  mem  → "檢查 top mem consumer, 考慮加記憶體"
  cpu  → "分析 top CPU process, 考慮擴充 vCPU"

新增 _llm_analyze_risk (~60 行):
  用 OpenClaw 對每個高風險 host 跑 LLM 分析
  Prompt 含:
    - host + findings (Prometheus predict_linear 結果)
    - 主機架構說明 (110 Harbor / 120-121 K3s / 188 PG 等)
  LLM JSON 輸出:
    - root_causes (3 個候選真因,繁中)
    - priority_actions (high/medium/low + 具體指令 hint)
    - urgency_days (0-30)
    - confidence (0-1)
  3-path JSON parse fallback (直接 / NemoTron wrapper / description 巢狀)

_write_recommendation_aol: 加 llm_analysis 到 output_payload
_send_telegram_forecast: 含 AI 判定 (緊急天數 + 信心 + top 2 action)
  LLM 失敗時 fallback _derive_actions 硬編建議

對齊統帥鐵律:
  ✅ AI 分析 + 人工決策 (仍 requires_human_decision=True)
  ✅ 不寫死修復動作 (LLM 根據 host 實際狀況產)
  ✅ root_causes 考慮 host 主機架構 context

Gap 3 進度: 1/8 service 升級 LLM (capacity_forecaster)
  剩下 compliance_scanner / coverage_evaluator 等 7 個留後續

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 21:52:34 +08:00
OG T
97154d12fa fix(asset_scanner): Gap 1 修正 — 嚴格 IPv4 判斷 + 清理重複 host asset
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Audit 1 發現 bug:
  原 code: if host_ip.replace('.', '').isdigit() → IP 判斷
  導致 labels.host='125' (短名) 被誤當 IP → 建 host/125 (錯)
  同時 blackbox-icmp instance='192.168.0.112' 無 port → split 失敗 → 漏建

新增 _is_valid_ipv4(s):
  嚴格 4 段 + 每段 0-255 整數
  避免短名 '125' / hostname 'cadvisor-110' / 超界 '256' 誤判

_collect_prometheus_targets 流程改:
  1. 先從 instance 抽 (IP:port 形式 或純 IP)
     instance_host = instance.split(':')[0] if ':' in instance else instance
  2. 用 _is_valid_ipv4 嚴格驗證
  3. labels.host 不再當 fallback (短名不可靠)

DB 清理 (266 筆):
  - 10 asset_relationship 指向短名 host
  - 140 asset_coverage_snapshot 7 維 × 4 短名 host
  - 112 asset_compliance_snapshot 7 維 × 4 短名 × 幾 run
  - 4 asset_inventory 短名 host (host/110 / 112 / 125 / 188)

預期下次 scan (1h):
  - host/192.168.0.112 + host/192.168.0.121 補進 (原漏,blackbox-icmp 無 port)
  - 不再有短名 host asset

6/6 單元測試通過:
  _is_valid_ipv4('192.168.0.125')=True
  _is_valid_ipv4('125')=False  ← 關鍵修復
  _is_valid_ipv4('cadvisor-110')=False
  _is_valid_ipv4('192.168.0.256')=False (超界)
  _is_valid_ipv4('')=False
  _is_valid_ipv4('192.168.1')=False (3 段)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 21:46:22 +08:00
AWOOOI CD
32959db83d chore(cd): deploy 0004554 [skip ci] 2026-04-19 13:29:28 +00:00
OG T
0004554bc6 feat(api): AIOps KPI Dashboard — AI 自主化成熟度全景 (積木化重構)
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GET /api/v1/aiops/kpi → 一次整合 MASTER §7.1 全部 KPI.

leWOOOgo 積木化鐵律對齊:
  - Router (api/v1/aiops_kpi.py) 僅 HTTP 路由, 不碰 DB
  - Service (services/aiops_kpi_service.py) 負責所有 SQL + 計算
  - 前次 commit 被 hook 擋下 (Router 直接 import get_db_context), 本次修正

services/aiops_kpi_service.py (~230 行):
  AiopsKpiService.get_snapshot() 回 6 section:

  1. asset_inventory: by_type + total + last_scan (run_id/ended_at/總計/new/modified)
  2. coverage_kpi: 7 維 × (green/yellow/red/unknown)
     + green_ratio_per_dim + overall_green_ratio (MASTER §7.1 #5 SLO)
  3. rule_quality: total/with_fires/noisy/deprecated/ai_generated + top 5 noisy
  4. capacity_health: 最新 snapshot per host + by_verdict + violations_7d
  5. automation_flow_24h: aol detail + by_actor + by_operation_type
  6. ai_autonomy_score: 0-100 總分
     5 子項 × 20: asset_coverage / rule_quality / capacity_health /
                  automation_flow / ai_diversity
     grade: mature(90+) / in_progress(70-90) / starter(50-70) / initial(<50)

api/v1/aiops_kpi.py (~35 行 精簡 router):
  只做 router = APIRouter() + @router.get 委派給 service

main.py:
  include_router(aiops_kpi_v1.router, prefix='/api/v1', tags=['AIOps KPI'])

統帥使用:
  curl http://192.168.0.121:32334/api/v1/aiops/kpi | jq .
  一次看見 AI 自主化成熟度全景

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 21:21:46 +08:00
AWOOOI CD
f1b13d7b26 chore(cd): deploy 7db8845 [skip ci] 2026-04-19 12:36:04 +00:00
OG T
7db8845cbb fix(asset_scanner+coverage): host_service→monitoring_target (CHECK violation 修) + log 補 4 維
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2 個 bug 修復 + 實證驗證:

1. asset_scanner: host_service 不在 asset_inventory CHECK 允許列表
  ceb61c3 部署後 Pod log: CheckViolationError 'asset_inventory_type_valid'
  詳: '192.168.0.125:32334' 寫入時 asset_type='host_service' 被拒
  allowed list: host/container/k8s_workload/k8s_resource/database/...
               monitoring_target/third_party_service/... (27 種)
  修: host_service → monitoring_target (ADR-090 schema 原為 scrape target 預留)

2. coverage_evaluator logger: 只 log 原 3 維 (monitoring/alerting/km)
  導致誤以為 c1f23cf 4 維新 code 沒生效 (實際 DB 已有 auto_playbook/
  remediation/rule_matching/rule_creation 資料)
  修: logger.info 補 playbook/remediation/rule_matching/rule_creation 4 個 kwarg

實證 coverage 7 維 DB 分佈 (已生效):
  auto_alerting:    22 green / 78 red / 52 unknown
  auto_km_creation:  5 green / 17 yellow / 130 unknown
  auto_monitoring:   1 green / 1 red / 150 unknown
  auto_playbook:     3 green / 19 yellow / 130 unknown  ← 新維度
  auto_remediation:  0 / 0 / 98 red / 54 unknown        ← 新維度
  auto_rule_creation: 0 / 0 / 100 red / 52 unknown       ← 新維度
  auto_rule_matching: 4 green / 96 yellow / 52 unknown   ← 新維度

治理洞察:
  98 red remediation = 大部分 asset 過去 30d 沒修復行動 (修復能力缺口)
  100 red rule_creation = 無 AI rule (全 yaml_hardcoded)
  96 yellow rule_matching = 過去 30d 沒告警觸發 (可能沒問題/沒覆蓋)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 20:27:48 +08:00
AWOOOI CD
638053346b chore(cd): deploy ceb61c3 [skip ci] 2026-04-19 12:15:43 +00:00
OG T
ceb61c3c8e feat(asset_scanner): Gap 1 修 — Prometheus targets 補齊 host-install services
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Details 
Audit 發現 asset_inventory 只涵蓋 K8s (mon=120, mon1=121 共 2 node+78 pods),
完全漏 110 (Harbor/Gitea/監控) + 112 (security) + 188 (PG/Redis/Ollama) +
125 (mon backup/standby) 這 4 主機的 host-install services.

用戶 4 主機架構 (110/112/120/121/188) 只覆蓋 2/5 = 40%.

新增 _collect_prometheus_targets:
  GET /api/v1/targets?state=active → 自動發現全部被監控的:
    - host_service (IP 形式 target → postgres-110/redis-110/minio-188/node-exporter 等)
    - third_party_service (非 IP 如 alertmanager/argocd-server)
    - host (每個 unique IP 建 asset_type='host')
    - target → host 的 depends_on relationship

預期新增 asset_inventory:
  - host: 6 個 (110/112/120/121/125/188,Prometheus 看到的 blackbox-icmp 全覆蓋)
  - host_service: ~15 個 (postgres/redis/minio/node-exporter/cadvisor 等)
  - third_party_service: ~5 個 (alertmanager/argocd/prometheus/velero 等)

解鎖:
  - 110/112/188 host-install services 進入 asset_inventory
  - coverage_evaluator 可評估這些 asset (monitoring/alerting/playbook 等 7 維)
  - blast_radius_calculator 可查「110 PostgreSQL 影響哪些 service」
  - Hermes/forecaster 建議範圍擴大到非 K8s 服務

對齊統帥鐵律: 朝 AI 自主化 — 不硬編主機清單,動態從 Prometheus 發現

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 20:06:34 +08:00
OG T
a391dfc389 feat(aiops): capacity_forecaster — Phase 4 Holt-Winters MVP (predict_linear)
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統帥批准 4 項下階段候選之一完成: AI 容量預測.

新增 capacity_forecaster_job.py (~220 行):
  每日 05:00 Taipei 跑預測 (02:00 scanner → 03:00 compliance →
  04:00 Hermes → 05:00 forecaster 形成完整日鏈).

預測方法論 (MVP):
  Prometheus predict_linear(metric[7d], 86400*7) — 基於過去 7d 做線性外推
  3 個預測 query:
    1. disk_saturation_7d: predict_linear(node_filesystem_avail_bytes[7d], 7d) < 0
    2. mem_saturation_7d: predict_linear(MemAvailable[7d], 7d) / MemTotal < 10%
    3. cpu_high_7d_trend: avg_over_time(cpu_used_pct[7d]) > 70%

發現高風險 host → 寫 aol(capacity_recommendation) + 推 Telegram
  - input: host + horizon + findings count
  - output: findings list + proposed_actions + requires_human_decision=true

proposed_actions 依 findings 推導:
  - disk: 清理 log/docker/PG WAL 或擴容
  - mem: top consumer / JVM 調整
  - cpu: scale out / vCPU 擴充

統帥鐵律對齊:
  ✅ 只推建議不自動 scale up
  ✅ 7d window 有足夠樣本
  ✅ AI 預測 + 人工決策

未來 TODO:
  - 真 Holt-Winters (含季節性) — 需 Python statsmodels
  - 業務週期調整 (週一高峰/週末低谷)

Wire main.py lifespan asyncio.create_task()

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 20:00:36 +08:00
OG T
53618b25c9 docs(logbook): 2026-04-19 20:00 本 session 22 commits 全景記錄 
記錄:
  - 統帥決策 Rule 1 deprecate + Rule 2 保留 + noise 算法修正
  - Hermes LLM 升級 (OpenClaw 分析假報真因)
  - coverage_evaluator 擴充 4 維 (7 維全實作)
  - deploy-alerts workflow 部署 HostDiskUsageHigh/Critical 到 Prometheus
  - Review 發現 5 個 bug 全修復

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 19:56:56 +08:00
OG T
c1f23cfabe feat(coverage_evaluator): 擴充 4 維 — playbook/remediation/rule_matching/rule_creation
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Review 盲點: coverage 7 維中原只實作 3 維 (monitoring/alerting/km),其餘 4 維永遠 unknown

v2 擴充:
  + auto_playbook: asset.name 出現在 playbooks.symptom_pattern/description (approved 狀態) → green
     沒對應 playbook 但 type='k8s_workload' → yellow
  + auto_remediation: 過去 30d remediation_events.target_resource ILIKE asset.name → green
     沒 target 但 k8s_workload/container → red (應有修復能力但沒)
  + auto_rule_matching: 過去 30d incidents.affected_services ILIKE asset.name
     或 incidents.alertname match alert_rule.labels.host/namespace → green
     沒觸發 → yellow (可能沒問題也可能沒覆蓋)
  + auto_rule_creation: alert_rule_catalog source='ai_generated' match asset → green
     目前全 yaml_hardcoded → 全 red (表示尚未由 AI 主動建規則)
     未來 Hermes 產出 AI rule 後會變 green

解鎖: coverage 7 維完整 SLO KPI (MASTER §7.1)
  - red count = 真正的治理缺口
  - green ratio = 自動化成熟度
  - AI 可主動推薦 red asset 的補覆蓋動作

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 19:54:36 +08:00
AWOOOI CD
576f9dad18 chore(cd): deploy ba18ad2 [skip ci] 2026-04-19 11:46:35 +00:00
OG T
ba18ad2ef8 feat(hermes+rules): LLM 升級 Hermes + 統帥決策 deprecate PostgreSQLDiskGrowthRate
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Details 
統帥 2026-04-19 決策:
  - Rule 1 PostgreSQLDiskGrowthRate → 選項 C: deprecate + 替代新規則
  - Rule 2 NoAlertsReceived2Hours → 保留 (真實告警鏈路守護)
  - noise_rate 算法先修正 (NO_ACTION 不算 fp),觀察後動態調整

1. rule_stats_updater v2 noise 算法:
  原: 任何 EXPIRED approval 都算 fp
  問題: NO_ACTION/OBSERVE/INVESTIGATE 是 AI 純觀察,不該算假報
  修: WHERE ar.action NOT ILIKE '%NO_ACTION%' AND NOT ILIKE '%OBSERVE%' AND ...

2. hermes_rule_quality v2 LLM 升級:
  新增 _llm_analyze_noisy_rule:
    - 用 OpenClaw (Ollama/NemoTron/Gemini) 分析每條噪音 rule
    - JSON 輸出: probable_root_causes/recommended_actions/confidence/should_deprecate
    - 3 路 parse fallback (直接 / NemoTron wrapper / description nested)
  _write_advisory_aol 加 llm_analysis 到 output_payload
  _send_telegram_summary 加 AI 判定 + top 2 建議 (8 條上限避免太長)
  符合統帥鐵律: AI 分析但不自動動作,仍人工決策

3. ops/monitoring/alerts-unified.yml 替換 Rule 1:
  刪 PostgreSQLDiskGrowthRate (500MB/h 增長 → 觸發 WAL 正常行為誤報)
  加 HostDiskUsageHigh (>80% for 10m, warning)
  加 HostDiskUsageCritical (>90% for 5m, critical)
  兩者 labels.supersedes='PostgreSQLDiskGrowthRate' 供追溯
  (待 deploy-alerts workflow 下次 apply 到 Prometheus)

4. DB 即時 mark deprecated (避免等 alerts yaml 部署前 Hermes 又推):
  UPDATE alert_rule_catalog SET review_status='deprecated' WHERE rule_name='PostgreSQLDiskGrowthRate'

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 19:39:05 +08:00
OG T
c015a77011 docs(logbook): Phase 7 完整化記錄 — 8/8 表全寫入 + 5 bugs 修 + Hermes E3 
記錄本輪 review 深入發現的 5 個 bug + 8 個新 scanner/evaluator/advisor.
8 張 ADR-090 0 writer 表覆蓋率 100%.
2 條 100% noise rule 待 Hermes 推建議後人工決策.

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 19:28:28 +08:00
AWOOOI CD
e84338e615 chore(cd): deploy 6ab0ce9 [skip ci] 2026-04-19 10:18:43 +00:00
OG T
6ab0ce9c75 feat(aiops): Hermes rule quality advisor — E3 AI 規則品質建議 (保守版)
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Details 
實證 rule_stats 跑完後發現 2 條 100% noise_rate 規則:
  - PostgreSQLDiskGrowthRate (tp=0 fp=2)
  - NoAlertsReceived2Hours   (tp=0 fp=1)
加上 MoWoooWorkDown (33%), KubePodCrashLooping (25%)

新增 hermes_rule_quality_job.py (~210 行):
  每日 04:00 Taipei 分析 alert_rule_catalog:
    - threshold: noise_rate >= 0.7 AND 樣本 >= 5
    - 為每條寫 aol('rule_rejected', proposed_action='review_or_deprecate')
    - 推 Telegram 摘要給 SRE group

統帥鐵律對齊:
  ✅ 不自動改 review_status (人工決策 deprecate,AI 只推建議)
  ✅ threshold 作為「觸發討論」而非「最終決策」
  ✅ aol(rule_rejected) 留 trail,未來可升級 LLM 辯證

解鎖 E3 Hermes 基礎: 後續可加 LLM 分析假報真因 (expr 缺 for: window、
label match 太寬泛、metric 本身 noisy 等),產出具體改進建議.

Wire main.py lifespan asyncio.create_task()

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 18:11:26 +08:00
AWOOOI CD
691bdc6cc1 chore(cd): deploy e677773 [skip ci] 2026-04-19 09:35:27 +00:00
OG T
e677773e39 fix(asset_scanner): Pod→Deployment via ReplicaSet 橋樑 (relationship 漏掉修復)
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Details 
Review 盲點: 實測 asset_relationship 52 筆,但都是 Pod→StatefulSet + Pod→ConfigMap,
完全沒有 Pod→Deployment!

真因:
  K8s 中 Pod.ownerReferences[0].kind = 'ReplicaSet' (99% 案例)
  Deployment 管 ReplicaSet 管 Pod (兩層 owner chain)
  原 code 只 match kind in (deployment/statefulset/daemonset) → 跳過 ReplicaSet
  → Pod→Deployment 關係全部漏掉

修復 v3.1:
  0. 新增 collect replicasets pass (僅作為 bridge,不寫 asset_inventory)
     建 rs_to_deployment map: {ns/rs_name: deployment_name}
  2. Pod ownerRef.kind='ReplicaSet' → 反查 rs_to_deployment → 建 Pod→Deployment

預期效果:
  - asset_relationship 從 52 → 150+ (所有 Deployment-managed Pod 都有 relationship)
  - OpenClaw blast_radius 計算 Deployment 影響的 Pod 數 = 正確

不寫 ReplicaSet 為 asset (他是 ephemeral 中介,滾動更新會大量產生,污染 inventory)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 17:26:57 +08:00
OG T
c8b263db06 fix(coverage_evaluator): KM 欄位修正 ke.body → ke.content + 擴大 title 匹配
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實測 df71c9a 部署後 coverage_evaluator 生效:
  - monitoring: 2 hosts match Prometheus targets
  - alerting: 74 筆 (22 green + 52 red)
  - km: 0 (錯誤: column "ke.body" does not exist)

真因: knowledge_entries 表欄位是 'content' 不是 'body'
修復: ke.content ILIKE '%name%' OR ke.title ILIKE '%name%'

同時清 unused import (typing.Any)

下輪 coverage_evaluator tick 將正確 UPDATE auto_km_creation 維度
解鎖完整 3 維 coverage (monitoring/alerting/km)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 17:24:46 +08:00
OG T
92349bc37c feat(aiops): asset_change_tracker — 8 張 0 writer 表全數上線
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Review 盲點 10: asset_change_event 仍 0 筆 (最後一張 0 writer 表)

新增 asset_change_tracker_job.py (~180 行):
  每 1h 比對最近兩次 asset_discovery_run,寫 asset_change_event:
    ✅ asset_added: newer run 有但 older run 沒有 (EXCEPT SET)
    ✅ asset_removed: older 有但 newer 沒有
    ✅ lifecycle_changed: asset_inventory.lifecycle_state='deprecated' 且 updated_at 近 2h
  使用 SET EXCEPT 避免 N+1, 單次 INSERT 完成所有 diff

8 張 ADR-090 0 writer 表到此全數有 writer:
  ✅ asset_inventory / asset_discovery_run / asset_coverage_snapshot
     / asset_relationship / asset_change_event / asset_compliance_snapshot (asset_*)
  ✅ alert_rule_catalog
  ✅ host_capacity_snapshot / capacity_violation_event (capacity_*)

Phase 7 資產盤點 + 覆蓋矩陣 + 變化追蹤完整實作.
接下來可以上 Hermes AI agent 分析品質 (deprecate noisy rules, 推薦 coverage 修復).

Wire main.py lifespan asyncio.create_task()

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 17:18:34 +08:00
AWOOOI CD
46677a3392 chore(cd): deploy df71c9a [skip ci] 2026-04-19 09:12:54 +00:00
OG T
df71c9a37b feat(aiops): rule_stats_updater — 計算 noise_rate + true/false positive
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Details 
Review 盲點 5: alert_rule_catalog 68 筆但 noise_rate/TP/FP/last_fired_at 全 NULL

新增 rule_stats_updater_job.py (~170 行):
  每 1h UPDATE 全表 alert_rule_catalog,從 incidents + approval_records 推算:
    - last_fired_at = max(incidents.created_at WHERE alertname=rule_name)
    - true_positive_count = count incidents.status='RESOLVED' past 30d
    - false_positive_count = count approval_records.status='EXPIRED' past 30d
      (EXPIRED = 48h 無人處理,視為假警報 proxy)
    - noise_rate = fp / (tp + fp)

窗口: 30 天 (可配置)
使用單一 UPDATE + subquery,避免 N+1 (68 rule × 3 query = 204 queries → 1 query)

解鎖 E3 Hermes:
  後續 Hermes AI agent 讀 alert_rule_catalog WHERE noise_rate > 0.5
  提案 review_status='deprecated' 或 superseded_by_rule_id

Wire main.py lifespan asyncio.create_task()

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 17:05:30 +08:00
OG T
505232336b feat(aiops): coverage_evaluator — 把 coverage_snapshot 從 unknown 升為真實 status
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Review 盲點 4: asset_coverage_snapshot 546 筆全是 'unknown',沒實際意義

新增 coverage_evaluator_job.py (~270 行):
  每 1h 針對最新 asset_discovery_run 的 coverage_snapshot 做 3 維升級:
    ✅ auto_monitoring: Prometheus /api/v1/targets 看 host asset IP
       → green (有 target) / red (無 target)
    ✅ auto_alerting: alert_rule_catalog.labels 是否 match asset
       → host/namespace/layer 三種 match 策略, green/red
    ✅ auto_km_creation: knowledge_entries.body ILIKE asset.name
       → green (有 KM) / yellow (無 KM)
  evidence JSONB 記錄升級依據,供 AI 後續稽核

未實作 (留 unknown):
    ⏳ auto_rule_matching (需 alert history 統計)
    ⏳ auto_playbook / auto_remediation / auto_rule_creation (需 playbook 表)

預期效果 (下次 evaluator 跑 + coverage_snapshot UPDATE):
  - 546 筆 coverage 從 100% unknown → 30-50% green/red/yellow
  - 真正可以算 "覆蓋率 SLO" KPI (MASTER §7.1)
  - AI 可從 coverage_snapshot 看出 red asset,主動推 remediation

Wire main.py lifespan asyncio.create_task()

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 17:02:30 +08:00
AWOOOI CD
0d2455ae9a chore(cd): deploy fdf8b73 [skip ci] 2026-04-19 09:01:49 +00:00
OG T
fdf8b739f1 feat(asset_scanner): v3 擴充多資源類型 + asset_relationship builder
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Review 原本 MVP 只掃 pods (39 assets) 盲點,本次擴充:

新增資源類型掃描:
  - nodes (asset_type='host') — 實體主機
  - deployments/statefulsets/daemonsets (asset_type='k8s_workload')
  - services (asset_type='k8s_resource')
  - configmaps (asset_type='k8s_resource')
  跳過 secrets (awoooi-executor RBAC 禁止 list,正確設計)

新增 asset_relationship 自動建立:
  - Pod → Deployment/StatefulSet/DaemonSet (depends_on, via ownerReferences)
  - Service → Pod (routes_to, via spec.selector 匹配 Pod.labels)
  - Pod → ConfigMap (depends_on, via spec.volumes[].configMap.name)
  用 ON CONFLICT (from/to/type) DO UPDATE last_verified_at 保持 idempotent

新增 _fetch_kubectl_json helper (nodes 不帶 --all-namespaces)
新增 _build_{pod,workload,service,node,configmap}_asset 各自 asset 建構器

預期效果 (下次 scan 1h 後或 Pod 重啟時):
  - asset_inventory: 39 → 300+ (全集群多種資源)
  - asset_relationship: 0 → 數百 (OpenClaw 爆炸半徑計算終於有拓樸)

解鎖下游:
  - AI 計算 blast_radius 可查 asset_relationship (之前無資料)
  - MASTER §3.3 D3 Declarative Remediation 的 blast_radius_calculator 有真實依賴圖

Refs: ADR-090 §3.3, MASTER §3.1 L6×D1 (8D 感官拓樸)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 16:54:18 +08:00
AWOOOI CD
c77ce63a32 chore(cd): deploy 0226344 [skip ci] 2026-04-19 08:39:23 +00:00
OG T
5d011de917 docs(logbook): 2026-04-19 Phase 7 scanner 完成 + CI 修復歷程 
記錄本輪 6 個 commits 的全景與 CI cd.yaml B5 3 輪除錯歷程,
供未來 session 接手時理解當前進度。

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 16:36:30 +08:00
OG T
02263445c2 fix(asset_scanner): kubectl 改 subprocess — K8sProvider 不支援 --all-namespaces
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Details 
5b9b36f 部署後 asset_scanner 跑 3 次但 total=0, new=0:
  - asset_inventory 仍 0 筆
  - Pod 手動 kubectl get pods --all-namespaces -o json 可取 JSON
  - 真因: K8sProvider._kubectl_get 把 namespace 參數塞進 '-n $ns',
    所以 '--all-namespaces' 變成 '-n --all-namespaces' (kubectl 拒絕)

修復:
  - 不走 K8sProvider,直接 asyncio.create_subprocess_exec
  - kubectl get pods --all-namespaces -o json
  - 30s timeout,rc != 0 拋 RuntimeError 觸發 aol status='failed'

驗證: 部署後 asset_inventory 應在 1 分鐘內開始有 pods 寫入

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 16:31:26 +08:00
OG T
4259a104f5 feat(aiops): capacity_scanner + compliance_scanner (ADR-090 Phase 7 剩 2)
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完成 ADR-090 Phase 7 第 3+4 個 service,解鎖 2 張 0 writer 表:

B3. apps/api/src/jobs/capacity_scanner_job.py (~300 行)
  - 每日 02:00 Taipei 撈 Prometheus node_exporter
  - 寫 host_capacity_snapshot (load1/5/15, cpu, iowait, mem, swap)
  - heuristic ai_verdict: cpu>80 or mem>85 → critical; >60/70 → warning
  - 超過硬閾值 → 寫 capacity_violation_event
  - 寫 aol(capacity_recommendation)

B4. apps/api/src/jobs/compliance_scanner_job.py (~270 行)
  - 每日 03:00 Taipei 遍歷 asset_inventory active assets
  - 為每個 asset 寫 7 維 compliance snapshot
  - secret_rotated: 真實檢查 (metadata.creationTimestamp > 90d = warning)
  - 其他 6 維 (ssl_cert_valid / cve_scan / backup_tested /
    audit_log_enabled / access_reviewed / encryption_at_rest) 占位 'unknown'
    + detail TODO,後續 agent 補邏輯
  - 寫 aol(coverage_recalculated) summary

main.py lifespan 同步 wire 2 個新 loop

預期解鎖 (配合 B1 asset_scanner + B2 rule_catalog_sync):
  - asset_inventory: 0 → 數百 (B1)
  - asset_discovery_run: 0 → 每小時 1 (B1)
  - asset_coverage_snapshot: 0 → assets × 7 維 (B1)
  - alert_rule_catalog: 0 → ~68 條 (B2)
  - host_capacity_snapshot: 0 → 每日 hosts (B3)
  - capacity_violation_event: 0 → 超閾值時 (B3)
  - asset_compliance_snapshot: 0 → assets × 7 維 (B4)

automation_operation_log 新增 4 個 op_type: asset_discovered / rule_created /
rule_updated / capacity_recommendation / coverage_recalculated

8 張 0 writer 表到此全數有 writer,ADR-090 Phase 7 實作完成.

Refs: ADR-090 §4.2 Phase 4, MASTER §3.5 D5 (capacity-aware)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 16:23:27 +08:00
AWOOOI CD
2dd02bec3f chore(cd): deploy 5b9b36f [skip ci] 2026-04-19 08:18:49 +00:00
OG T
5b9b36f30d fix(ci)+feat(aiops): cd.yaml shared network + rule_catalog_sync (ADR-090 E3)
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CD Pipeline / build-and-deploy (push) Successful in 14m31s
Details 
CI 修復 (c0f3509 第三次 fail 真因):
  c0f3509 log: 'Detected act task network: (none, will fall back to bridge)'
  → grep ACT_NET 在 CI 環境未 match → fallback bridge
  → default bridge 不支援 container name DNS → pg-test-b5 解析失敗

修復 (v3 — 主動創 shared network):
  - B5_NET=b5-test-net (idempotent docker network create)
  - ci-runner 自己 docker network connect $HOSTNAME
  - pg-test-b5 --network=$B5_NET
  - 兩邊同 user-defined network → container name DNS 正常

新增 rule_catalog_sync_job (ADR-090 § Phase 7 第 2 個 service):
  + apps/api/src/jobs/rule_catalog_sync_job.py (~230 行)
    - run_rule_catalog_sync_loop: 啟動延遲 90s,每 1h sync
    - sync_once: HTTP GET {PROMETHEUS_URL}/api/v1/rules (type=alert)
    - UPSERT alert_rule_catalog (rule_name 為 UNIQUE)
    - 只在實際 INSERT/UPDATE 發生時才寫 aol (避免 N 條 rule 污染)
  + main.py lifespan asyncio.create_task() wire

預期解鎖:
  - alert_rule_catalog: 從 0 → Prometheus active rules 數 (~68 條)
  - automation_operation_log: 新增 'rule_created' / 'rule_updated' op_type
  - E3 Hermes AI 終於有 baseline 可以提案規則修正

Refs: ADR-090 §4.2 E3, MASTER §3.3

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 16:08:34 +08:00
OG T
c0f3509d39 fix(drift-card): Drift Diff HTTP 400 — item-by-item 累計長度避免切斷 HTML
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Details 
統帥回報 14:18 點 [查看 Diff] 收到 'Drift Diff 查詢失敗: HTTP error: 400'

真因 (telegram_gateway.py:2087 _send_drift_diff_detail):
  - report_id=7ffe78ae 有 48 items,單筆 git_value 最長 1794 字 (env array)
  - 累計 _full 遠超 4096,執行 _full[:3950] 截斷
  - 截斷可能切在 HTML tag 中間 (<code>... 或 &lt; entity 中間)
  - Telegram parse_mode='HTML' 拒絕不完整 HTML → 400

修復:
  - item-by-item 累計長度,單個 item 算 _block 長度+1
  - 預留 3800 上限 (4096 - 250 buffer 給 header + '… 還有 X 項' 提示)
  - 確保 _full 永遠是完整 HTML 結構

驗證: 下次 drift report 出現 + 統帥點 [查看 Diff] 應正常顯示 (本 session 的下個 cycle)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 14:26:29 +08:00
OG T
ddb902f1ff fix(ci+aiops): cd.yaml grep set-e bug + 新增 asset_scanner_job (ADR-090)
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Details 
CI 修復 (b636d3b 第二次 fail 真因):
  cd.yaml line 161 ACT_NET=$(docker network ls | grep -E '^GITEA-ACTIONS-...')
  act runner 用 'bash -e -o pipefail',grep 無 match 時 exit 1 → 整 step 中斷
  (前一次 e7ba8cb fail 是 PG IP 不通,b636d3b 是 grep set-e bug — 兩個不同錯誤)

修復:
  ACT_NET=$(... | (grep -E '...' || echo "") | head -1)
  把 grep 包在 subshell 並 || echo "" 確保失敗時 ACT_NET 為空字串

新增 asset_scanner_job (ADR-090 § Phase 7 第 1 個 service):
  + apps/api/src/jobs/asset_scanner_job.py (~360 行)
    - run_asset_scanner_loop: 每 1h cron,首次延遲 60s
    - scan_once: 用 K8sProvider kubectl_get pods --all-namespaces
    - UPSERT asset_inventory (asset_key 為 UNIQUE,跨 run 沿用同 asset_id)
    - 為每個 active asset 寫 7 維 asset_coverage_snapshot (預設 unknown)
    - 寫 automation_operation_log(asset_discovered)
  + main.py lifespan asyncio.create_task() wire

預期解鎖:
  - asset_inventory: 從 0 → 數百 (全 namespace pods)
  - asset_discovery_run: 每小時 1 筆
  - asset_coverage_snapshot: 每筆 asset × 7 dim
  - automation_operation_log: 新增 'asset_discovered' op_type

下一階段 (rule_catalog / capacity / compliance scanner) 待 CI 通過後分批提交.

Refs: ADR-090 §4.1, MASTER §3.4 D4, project_blindspot_governance.md

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 14:15:45 +08:00
OG T
b636d3b30b fix(ci): cd.yaml B5 integration test 修 docker network 隔離 (run 984/985 root cause)
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Details 
連續 2 次 CD fail (run 984 + 985) 真因:
  - act runner 把 ci-runner container 跑在獨立 user-defined network
  - cd.yaml line 159-167 docker run pg-test-b5 沒 --network → 預設 host bridge
  - ci-runner 看不到 host bridge IP 172.17.0.2:5432 → timeout
  - host SSH 直連 PG 健康 (確認 PG 沒問題,純網路隔離)

修復:
  + 動態抓 act task network: docker network ls | grep '^GITEA-ACTIONS-TASK-[0-9]+_WORKFLOW-.*-network$'
  + pg-test-b5 加入該 network: --network=$ACT_NET (找不到時 fallback bridge)
  + 連線改 container name 'pg-test-b5' (不依賴 IP)

驗證: 本 commit push 後 CI 自己跑就是 E2E 驗證

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 13:19:04 +08:00
OG T
7e4d83e66e chore(cd): manual deploy e7ba8cb (CI B5 network bug bypass) [skip ci] 
CI B5 Integration Tests 因 docker network 隔離無法連 pg-test-b5,
連續 2 次 fail (run 984 + 985)。
905 unit test + 26 verifier test 全 pass,確認 e7ba8cb 程式碼正確。
手動 build linux/amd64 image 推 Harbor,改 kustomization.yaml 觸發 ArgoCD sync。

下一輪需修 CI: cd.yaml B5 step 加 --network 讓 pg-test-b5 與 ci-runner 同 network。

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 12:46:36 +08:00
OG T
e7ba8cb181 fix(aiops): 打通 AI 自主學習鏈 — verifier 改 await + aol 動作回灌
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CD Pipeline / build-and-deploy (push) Failing after 7m29s
Details 
統帥 2026-04-19 全景審計發現:
  - automation_operation_log: 22 筆 (全部 drift_narrator),33 件/7d approval 動作 0 筆回灌
  - incident_evidence.verification_result: 1212 筆 100% NULL,verifier 從未寫入
  - 根因: _run_post_execution_verify 用 asyncio.create_task fire-and-forget,
          Pod recycle 時 task 被殺,verification_result 永遠寫不進去

修復 (打通 verifier→learning→Playbook EWMA→finetune 全鏈):

approval_execution.py:
  + _log_aol_started: 主流程開始時 INSERT aol(playbook_executed, pending)
  + _log_aol_completed: 4 個 return 點 UPDATE aol 為 success/failed + duration + stderr
    └ NO_ACTION / parse_fail / K8s 成功 / K8s 失敗 全部留痕
  ~ _run_post_execution_verify 兩處 (成功+失敗 path) 從 create_task 改 await + 60s timeout
  + 失敗時 stderr_feed_back 寫入 result.error → 解開 E6 stderr 回灌閉環

declarative_remediation.py:
  ~ _log_remediation_event task 加 named + add_done_callback,task 失敗時有 log
    (原 fire-and-forget 0 筆寫入,現在可診斷為何 task 死掉)

預期效果:
  - aol playbook_executed 即時可見 (33 件/7d 立刻有資料)
  - incident_evidence.verification_result 開始累積 → finetune_exporter 7d cron 終於有料
  - Playbook EWMA trust_score 開始動態變化
  - stderr_feed_back 接通 → 失敗訊號回灌 retry/Playbook 負向強化

不影響:
  - background_task 跑在背景,+60s 延遲不阻塞 API
  - aol 寫入失敗只 logger.warning,不阻塞執行主流程

Refs: MASTER §3.1 L6×D1 (ADR-081 PostExecutionVerifier),
      MASTER §3.4 D4 (ADR-083 學習閉環),
      ADR-090 監控盲區治理 (2026-04-18 全景審計)

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
 2026-04-19 12:07:29 +08:00