39 lines
1.5 KiB
Markdown
39 lines
1.5 KiB
Markdown
# AIOps Alert Acceptance Case
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## Goal
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Validate that the legacy AIOps endpoint can act as a traceable alert-triggered diagnosis entry.
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## Input
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- Session id: `mvp-demo-aiops-payment-cpu-001`
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- Endpoint: `POST /api/ai_ops`
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- Profile: `mvp-demo`
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- Alert:
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```json
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{
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"sessionId": "mvp-demo-aiops-payment-cpu-001",
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"alertName": "HighCPUUsage",
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"service": "payment-service",
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"severity": "P1",
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"description": "服务 payment-service 的 CPU 使用率持续超过 80%，当前值为 92%。实例: pod-payment-service-7d8f9c6b5-x2k4m。",
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"timeRange": "last_15m",
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"userRequest": "请结合 Prometheus 活动告警、system-metrics 日志和知识库生成告警分析报告。"
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}
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```
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## Acceptance Criteria
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1. The SSE stream emits a `session` message containing the requested session id.
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2. The AIOps run creates or updates `diagnosis_session` with `agent_flow = AI_OPS`.
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3. The persisted session query contains the alert name, service, severity, time range, and description.
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4. If a final report is generated, `diagnosis_session.answer` contains that report.
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5. `GET /api/diagnosis/{sessionId}/trace` returns the AIOps session, ordered agent steps, and ordered tool invocations.
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6. In payload mode, the report focuses on `HighCPUUsage/payment-service`; unrelated active alerts may appear only as related risk or context, not as separate full root-cause sections.
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## Known Limits
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- This slice does not add a Verifier Agent to AIOps.
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- Full runtime verification still depends on valid DB, Redis, Milvus/Zilliz, model, and embedding configuration.
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