Your Name
479f8d8971
refactor(tests): 技術債清零 — 移除 FakeRepo/FakeSession Mock DB 違規
...
CD Pipeline / build-and-deploy (push) Failing after 35s
## ai_router.py
- 抽取 _aggregate_feedback_stats() 純函數，feedback_from_aider_events 呼叫它
## aider_event_processor.py
- _process_one 加 _session_factory=None DI 參數（預設 get_session_factory()）
- 可注入測試 factory，不改既有生產邏輯
## test_ai_router_feedback.py（完全重寫）
- 移除 FakeRepo/FakeSession，改為直接測試 _aggregate_feedback_stats 純函數
- 新增 test_feedback_skips_missing_model 邊界條件
- DB 失敗降級行為 test 保留（只 patch get_session_factory，無 FakeRepo）
## test_aider_event_processor.py（完全重寫）
- 移除 FakeRepo/FakeSession，改用真實 PostgreSQL（real_factory fixture）
- Redis xack + IncidentEngine 保留 mock（外部 broker/AI 服務，符合例外）
- 每個測試後 rollback，不污染 dev DB
## setup_test_schema.sql
- 補入 aider_events_payload_gin GIN index（與 adr091 生產 migration 一致）
## integration/conftest.py
- 補注解說明密碼名稱 awoooi_prod_2026 的歷史混淆
- 修正 assert 邏輯：檢查 DB 名稱而非 URL 字串，避免密碼含 prod 觸發誤判
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com >
2026-04-22 01:33:30 +08:00
Your Name
d0591c54b0
fix(security): 體健修復 — 7項 Critical/Major 安全問題全修
...
CD Pipeline / build-and-deploy (push) Failing after 35s
## Critical 修復 (C1-C5)
- C1: git rm --cached 03-secrets.yaml（CHANGE_ME 模板不再追蹤）
- C2: git rm --cached awoooi.db + .gitignore 加 *.db（SQLite HARD_RULES 違規）
- C3: sentry-tunnel SENTRY_HOST 改為 process.env fallback
- C4: config.py DATABASE_URL 移除 changeme default，改為必填
- C5: run_migration.py 改為 os.environ["DATABASE_URL"]
## Major 修復 (M1-M4)
- M1: auto_repair /execute 加 CSRF 保護 + AutoRepairPanel.tsx 同步
- M2: drift /rollback /adopt 加 CSRF 保護（/internal/scan 保持無 CSRF）
- M3: terminal /intent 加 CSRF 保護 + terminal.store.ts 同步
- M4: live-dashboard HOST_IPS + host-grid VIP 改為 env var
## 其他
- 新增 apps/web/.env.example（6 個 env var 說明）
- K8s deployment-web 補入 3 個新 env var
- 整合測試：新增 aider_event_repository + ai_router_feedback 真實 DB 測試
- test_terminal.py CSRF dependency override 修復
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com >
2026-04-22 01:27:39 +08:00
Your Name
4fc1f49dca
fix(pipeline): 三斷點修復 — SLO公式+NO_ACTION堆積+幻覺降級風險
...
CD Pipeline / build-and-deploy (push) Successful in 14m3s
D1 flywheel_stats_service: execution_count 欄位不存在 → 改讀
success_count+failure_count；消除飛輪執行成功率永遠 0.0% 假象
D2 openclaw._validate_deployment_inventory: 幻覺 deployment 降級後
原 HIGH/CRITICAL risk 未清零 → 加 result.risk_level = AIRiskLevel.LOW
D3 webhooks.py (兩處 alert path): NO_ACTION/INVESTIGATE/OBSERVE 三類
非破壞性動作強制 risk_level = LOW，跳過 Telegram 批准直接 auto-approve
→ approval_execution.py 的 NO_ACTION handler 立即標 EXECUTION_SUCCESS
Root cause 鏈：BUTTON_DATA_INVALID 修復後 TG 按鈕可發，但 NO_ACTION
積壓的 35 筆 PENDING 是因 HIGH risk 無法走 auto-approve 路徑導致。
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com >
2026-04-21 22:26:07 +08:00
Your Name
8fd31eca66
fix(telegram): nonce UUID base64url 壓縮 — 徹底解決 BUTTON_DATA_INVALID
...
CD Pipeline / build-and-deploy (push) Successful in 9m45s
前次修法（truncate random）不完整：host_restart_service(20 chars) 即使去掉 random
仍 68 bytes > 64 限制。
根本修法：UUID (36 chars) → base64url encode UUID bytes → 22 chars
nonce 格式：{action}:{b64url_uuid}:{timestamp}:{random}
最長 case: host_restart_service(20)+22+10+8+3 colons = 63 bytes
generate_callback_nonce: UUID → base64url 22 chars
parse_callback_data: 22-char b64url → 還原完整 UUID，handler 不需改動
全 action 驗證：approve/silence/reject/docker_restart/host_restart_service/renew_cert
全部 ≤ 63 bytes，UUID round-trip 正確。
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com >
2026-04-21 21:30:20 +08:00
Your Name
bd735482f7
fix(telegram): BUTTON_DATA_INVALID — nonce 超過 64 bytes 根因修復
...
CD Pipeline / build-and-deploy (push) Has been cancelled
根因：Telegram callback_data 上限 64 bytes。
5 個長 action 名（docker_restart/host_restart_service 等）+ UUID approval_id
= 71-77 bytes → BUTTON_DATA_INVALID。
修復：
1. security_interceptor.generate_callback_nonce：若 nonce > 63 bytes，
改用 3-part 格式（捨棄 random）— timestamp 仍保時間唯一性。
2. security_interceptor.parse_callback_data：接受 3-part 或 4-part 格式。
3. telegram_gateway：移除 debug payload logging（診斷完成）。
影響 action：docker_restart / host_restart_service / host_clear_log /
reload_nginx / renew_cert（全部 > 7 chars + UUID = 64 bytes 以上）。
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com >
2026-04-21 21:17:49 +08:00
Your Name
685f5c684f
debug(telegram): log full payload on 4xx to diagnose BUTTON_DATA_INVALID
...
CD Pipeline / build-and-deploy (push) Successful in 13m29s
前次 response_body 已確認錯誤碼，這次記錄完整 payload（payload_preview 前
1000 bytes）以找出觸發 BUTTON_DATA_INVALID 的確切欄位。
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com >
2026-04-21 20:56:28 +08:00
Your Name
acab1cd95e
fix(gitea-review): PR/push AI analysis always failing — 兩個根因修復
...
CD Pipeline / build-and-deploy (push) Successful in 17m26s
Root cause 1 (push review): local_code_review_service.review_push() 回傳
dict，但呼叫端直接存取 analysis.issues → AttributeError。
修復：_call_openclaw_push_review 將 dict 轉成 CodeReviewResult。
Root cause 2 (PR review): openclaw_http_service 呼叫
/api/v1/analyze/code-review 但 OpenClaw 從未實作此 endpoint（404）。
修復：_call_openclaw_code_review 改走 local_code_review_service.review_pr()
（Ollama qwen2.5-coder + Gemini fallback）。
Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com >
2026-04-21 15:19:14 +08:00
Your Name
3323a9052c
debug: log telegram 400 response body to diagnose card send failure
CD Pipeline / build-and-deploy (push) Successful in 12m38s
2026-04-21 01:05:21 +08:00
Your Name
9e9bd8679f
fix(aider-watch): code-review fixes (4 issues)
...
CD Pipeline / build-and-deploy (push) Has been cancelled
1. aiderw: session_end 補 model+cwd (AI Router feedback loop 修通)
2. repository: model_stats_since SQL 改 COALESCE(session_end, session_start) model
3. aider_event_service: classify_severity 移除 error_count 觸發告警（防假陽性）
4. worker: run_aider_event_processor_loop 包 proc.start() try/except（防靜默崩潰）
2026-04-20 @ Asia/Taipei
2026-04-21 00:59:21 +08:00
Your Name
9a44516bf8
fix(aider-processor): init_worker_redis_pool before XREADGROUP
...
CD Pipeline / build-and-deploy (push) Successful in 9m35s
Worker pool 在 main.py lifespan 未初始化（signal_worker 同問題）。
在 AiderEventProcessor.start() 冪等呼叫 init_worker_redis_pool()，
確保 _consume_loop() 的 get_worker_redis() 不拋 RuntimeError。
2026-04-20 @ Asia/Taipei
2026-04-20 20:21:15 +08:00
Your Name
de2d34d4cd
fix(playbook): C1-C4 全流程串接 — evolver保護+seeder復活+規則即時建立+watchdog W-4
...
CD Pipeline / build-and-deploy (push) Has been cancelled
C1: playbook_evolver — yaml_rule source playbooks 加 YAML_RULE guard，
evolver 不再封存 seeder 建立的 APPROVED playbook，保護自動修復鏈路
C2: playbook_seed_service — idempotency SQL 排除 DEPRECATED 記錄，
evolver 封存後重啟可復活 yaml_rule playbooks
C3: alert_rule_engine — AI 自動生成規則成功後立即呼叫 seed_playbooks_from_rules()，
不等下次重啟即可建立對應 APPROVED Playbook
C4: ai_slo_watchdog_job — 新增 W-4 APPROVED playbook 數量為 0 告警，
鏈路斷裂立即 TYPE-8M；total checks 由 3 升為 4
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com >
2026-04-20 20:18:11 +08:00
Your Name
7ca6d12ce2
fix(aider): remove dead get_aider_event_repository factory (resource leak)
...
get_db_context import unused after removing broken factory function.
Worker manages its own session via get_session_factory(). 2026-04-20 @ Asia/Taipei
2026-04-20 20:18:11 +08:00
Your Name
156a52f807
fix(aiops): ADR-092 三修 — Playbook enum崩潰 + Telegram永久靜默 + 採納失敗 + AI自健診
...
CD Pipeline / build-and-deploy (push) Successful in 13m33s
B1 playbook_service.py: evolver setattr傳str而非PlaybookStatus enum
→ _pg_upsert playbook.status.value炸（163次/48h），修：update_with_validation強制enum轉型
B2 approval_db.py + webhooks.py: find_by_fingerprint PENDING誤收斂
→ PENDING≠Telegram已發；修：成功push後mark tg_sent:{fingerprint} Redis(24h TTL)
→ find_by_fingerprint debounce窗外PENDING必須Redis確認才收斂
drift_adopt_service.py: telegram_gateway呼叫adopt_drift(report_id)但方法不存在
→ 新增adopt_drift()包裝：從DB載入DriftReport後委派adopt()，修復採納失敗
B3 ai_slo_watchdog_job.py + main.py: AI無法感知自身故障（MASTER §1.1盲區）
→ 新增每15分鐘自健診：W-1 SLO違反 W-2 TG靜默偵測 W-3 飛輪成功率
→ 任一異常→TYPE-8M send_meta_alert；Redis去重1h
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com >
2026-04-20 20:00:06 +08:00
Your Name
1744b1e923
fix(aider): stdlib logging → structlog + typing-extensions dep (E2E修復)
...
CD Pipeline / build-and-deploy (push) Has been cancelled
- aider_events.py: logging.getLogger → structlog.get_logger (keyword args compatible)
- pyproject.toml: add typing-extensions>=4.0 (python-ulid 3.x requires Self)
2026-04-20 @ Asia/Taipei
2026-04-20 19:59:35 +08:00
Your Name
e1539a813e
feat(config+main): aider-watch v2 settings + router + lifespan register
...
- Add 4 settings to config.py: AIDER_WEBHOOK_SECRET, AIDER_EVENTS_STREAM_KEY, AIDER_PATTERN_EXTRACT_INTERVAL_HOURS, USE_AIDER_FEEDBACK (ADR-091)
- Import aider_events_v1 router in main.py imports (alphabetical after ai_slo_v1)
- Register aider_events_v1.router in include_router block (after alert_operation_logs_v1)
- Register run_aider_event_processor_loop() in lifespan (after compliance_scanner_loop)
- All 65 tests pass (24 action_parsing + 41 aider-watch tests)
Co-Authored-By: Claude Haiku 4.5 (1M context) <noreply@anthropic.com >
2026-04-20 19:40:02 +08:00
Your Name
40771cda6d
feat(ai_router): feedback_from_aider_events read-only hook (Phase 24 A8)
2026-04-20 19:40:01 +08:00
Your Name
df72da69e2
feat(worker): AiderEventProcessor — Redis stream consumer + incident + DB write
...
- Implement Task A7: background worker consuming signals:aider:events stream
- Parse AiderEventIn from Redis XREADGROUP messages
- Call IncidentEngine.process_signal for incident-worthy events
- Persist aider_events to PostgreSQL with optional incident_id FK
- XACK on success, preserve in pending list on DB failure (retry)
- ACK on parse failure (bad JSON avoids pending list jam)
- Match signal_worker.py pattern: no Active Sweeper (MVP)
- Unit tests: 4 tests covering incident creation, non-incident events, malformed payloads, engine failures
Tests: 37 passed (4 new + 33 existing regression)
2026-04-20 19:40:01 +08:00
Your Name
cd894310dc
feat(api): POST /api/v1/aider/events HMAC webhook + Redis stream push
...
- Router layer: HTTP validation + HMAC-SHA256 signature verification
- Service layer: Redis stream push (aider_event_service.push_aider_batch_to_stream)
- leWOOOgo積木化遵循: Router → Service → Redis
- All 6 tests passing (signature validation, batch limits, edge cases)
2026-04-20 19:40:01 +08:00
Your Name
964427c5d4
feat(service): aider_event_service — classify + signal_data builder (uses existing debounce)
2026-04-20 19:40:01 +08:00
Your Name
6bcbd12f6c
feat(repo): AiderEventRepository CRUD + model_stats + pattern candidates
2026-04-20 19:40:01 +08:00
Your Name
14fb08bcfe
revert(models): restore src.* imports in __init__.py + incident.py
...
Task A3 implementer 誤把既有 `from src.models.*` 改成 `from apps.api.src.models.*`
導致 tests/test_action_parsing.py 等既有測試 collect 失敗
(ModuleNotFoundError: No module named 'apps.api.src.models').
pytest rootdir=apps/api（由 pyproject.toml testpaths=["tests"]），
所以 awoooi 慣例為 `from src.*` 絕對路徑，切勿改。
A3 test file (test_aider_event_models.py) 已用正確 src.models.aider，
無需動。
15 tests (A2+A3) 過，existing tests 恢復（test_action_parsing: 24 collected）。
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com >
2026-04-20 04:11:59 +08:00
Your Name
5daae76147
feat(models): AiderEventIn + AiderBatchIn pydantic schemas
...
- Implement aider-watch v2 event schema with 7 event types
- Enforce timezone-aware timestamps via field_validator
- Batch schema supports up to 50 events per request
- Frozen + forbid extra fields (defensive engineering)
- Fix broken src.* imports in models package (incident.py, __init__.py)
Task A3 complete: 7/7 tests passing
2026-04-20 04:06:26 +08:00
Your Name
0db4534133
feat(utils): generic secret_redactor (7 patterns)
run-migration / migrate (push) Failing after 12s
CD Pipeline / build-and-deploy (push) Failing after 1m36s
2026-04-20 04:04:13 +08:00
Your Name
54d60d04f5
feat(drift+target): P0.1+P0.2+P0.3 三修 — drift 分頁分類 + AI 推薦 + target 追 trace
...
統帥三問決議：全做；AI 推薦 0.85 門檻純顯示不自動；先查 aol 再修
## RCA: awoooi-service 失敗來源
- /api/v1/aiops/kpi 顯示過去 24h 有 1 筆 playbook_executed actor=approval_execution status=failed
- grep codebase: 無任何程式碼寫死 awoooi-service（只有歷史 comment）
- 最可能源: alert_rule_engine._extract_vars 從 labels.service 取值當 Deployment 名
- cf5050c/4f2e122（2026-04-18）已修 NEMOTRON 幻覺雙路徑；本次修第三條路徑
## 修復
### P0.3a alert_rule_engine._extract_vars
- labels.service 降級：-service 結尾先剝 suffix 視為 base name
- match_rule 回傳新增 target_source 欄位追 trace
- 下次 awoooi-service 復發可直接看來源（label.service(stripped) 等）
### P0.3c approval_execution._log_aol_started.input
- 補 parsed_target/operation/namespace 欄位
- 未來 aol 查 failed 可直接看 target，無需推敲
### P0.1 telegram_gateway._send_drift_diff_detail
- 分頁（10 項/頁）取代一次洗版 30 項
- header 3 桶分類計數: 人工高風險 / 一般修改 / K8s 自動
- 底部 ⬅️ /➡️ 分頁按鈕（callback: drift_view_page:{report_id}_{page}）
- security_interceptor INFO_ACTIONS 加 drift_view_page 白名單
### P0.2 drift_narrator recommendation
- LLM prompt 加 recommendation 欄位（action/confidence/reason）
- action ∈ {adopt, revert, ignore, investigate}
- 卡片頂部顯示「🎯 AI 建議：⏪ 回滾 (85%) — reason」
- LLM 失敗走 _fallback_recommendation（規則式依 intent 對應）
- 卡片 diff_summary 上限 500 → 1500 字容納推薦 + narrative + items
- 統帥指令：純顯示不自動執行（門檻 0.85 保留未來）
## 驗證
- 90 個 pytest test 全過（drift + rule_engine + approval_execution）
- 5 檔 AST syntax check 過
## 下次驗收
1. 下次 drift 觸發 → 卡片頂部有「🎯 AI 建議」
2. drift_view 按下 → 3 桶分類 header + ⬅️ /➡️
3. awoooi-service 若復發 → automation_operation_log.input.parsed_target 直接查
Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com >
2026-04-20 04:04:13 +08:00
Your Name
f572561467
feat(ai_advisory): P0 修 leader lock + inline keyboard + callback handler
...
CD Pipeline / build-and-deploy (push) Successful in 8m31s
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
Your Name
fa643ebdc7
refactor(p1): LLM JSON parse helper 抽出 + coverage 閾值雙條件 (架構師 Review P1)
...
CD Pipeline / build-and-deploy (push) Successful in 8m52s
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
37b6c9ba56
chore: remove empty ai_orchestrator.py (意外進 commit 的空檔)
...
CD Pipeline / build-and-deploy (push) Successful in 13m6s
上個 commit (86d9b22noreply@anthropic.com >
2026-04-19 22:22:53 +08:00
Your Name
86d9b22125
docs(logbook): Session 結尾 — Gap Review + AI 自主化 1/9→4/9 全景記錄
...
CD Pipeline / build-and-deploy (push) Has been cancelled
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
Your Name
2f5cab2e45
feat(coverage_evaluator): Gap 3.3 LLM 升級 — 缺口分析 + 補覆蓋建議
...
CD Pipeline / build-and-deploy (push) Successful in 10m14s
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
...
CD Pipeline / build-and-deploy (push) Has been cancelled
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
Your Name
d6b854a25e
feat(capacity_forecaster): Gap 3 LLM 升級 — 從 threshold 到 AI 決策
...
CD Pipeline / build-and-deploy (push) Has been cancelled
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
...
CD Pipeline / build-and-deploy (push) Has been cancelled
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
OG T
0004554bc6
feat(api): AIOps KPI Dashboard — AI 自主化成熟度全景 (積木化重構)
...
CD Pipeline / build-and-deploy (push) Successful in 8m47s
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
OG T
7db8845cbb
fix(asset_scanner+coverage): host_service→monitoring_target (CHECK violation 修) + log 補 4 維
...
CD Pipeline / build-and-deploy (push) Successful in 12m59s
2 個 bug 修復 + 實證驗證:
1. asset_scanner: host_service 不在 asset_inventory CHECK 允許列表
ceb61c3c1f23cfnoreply@anthropic.com >
2026-04-19 20:27:48 +08:00
OG T
ceb61c3c8e
feat(asset_scanner): Gap 1 修 — Prometheus targets 補齊 host-install services
...
CD Pipeline / build-and-deploy (push) Successful in 13m32s
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)
...
CD Pipeline / build-and-deploy (push) Has been cancelled
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
c1f23cfabe
feat(coverage_evaluator): 擴充 4 維 — playbook/remediation/rule_matching/rule_creation
...
CD Pipeline / build-and-deploy (push) Has been cancelled
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
OG T
ba18ad2ef8
feat(hermes+rules): LLM 升級 Hermes + 統帥決策 deprecate PostgreSQLDiskGrowthRate
...
Deploy Alert Rules / Deploy Prometheus Alert Rules (push) Successful in 40s
CD Pipeline / build-and-deploy (push) Successful in 8m37s
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
6ab0ce9c75
feat(aiops): Hermes rule quality advisor — E3 AI 規則品質建議 (保守版)
...
CD Pipeline / build-and-deploy (push) Successful in 8m22s
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
OG T
e677773e39
fix(asset_scanner): Pod→Deployment via ReplicaSet 橋樑 (relationship 漏掉修復)
...
CD Pipeline / build-and-deploy (push) Successful in 9m31s
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
...
CD Pipeline / build-and-deploy (push) Has been cancelled
實測 df71c9anoreply@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
...
CD Pipeline / build-and-deploy (push) Has been cancelled
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
OG T
df71c9a37b
feat(aiops): rule_stats_updater — 計算 noise_rate + true/false positive
...
CD Pipeline / build-and-deploy (push) Successful in 8m26s
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
...
CD Pipeline / build-and-deploy (push) Has been cancelled
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
OG T
fdf8b739f1
feat(asset_scanner): v3 擴充多資源類型 + asset_relationship builder
...
CD Pipeline / build-and-deploy (push) Has been cancelled
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
OG T
02263445c2
fix(asset_scanner): kubectl 改 subprocess — K8sProvider 不支援 --all-namespaces
...
CD Pipeline / build-and-deploy (push) Successful in 9m9s
5b9b36fnoreply@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)
...
CD Pipeline / build-and-deploy (push) Has been cancelled
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
OG T
5b9b36f30d
fix(ci)+feat(aiops): cd.yaml shared network + rule_catalog_sync (ADR-090 E3)
...
CD Pipeline / build-and-deploy (push) Successful in 14m31s
CI 修復 (c0f3509c0f3509noreply@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
...
CD Pipeline / build-and-deploy (push) Failing after 2m0s
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 < 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)
...
CD Pipeline / build-and-deploy (push) Has been cancelled
CI 修復 (b636d3be7ba8cbnoreply@anthropic.com >
2026-04-19 14:15:45 +08:00
