aws-cloudwatch-investigation

仓库创建 2025年6月12日最近提交 6 小时前SkillHot 收录 20 天前

▸ 精选理由

将常见排查模式模板化，显著节省运维诊断时间。

▸ 风险提示

需要 AWS 访问权限以查看日志和指标。

这个 Skill 做什么

提供 CloudWatch 日志、指标与告警的调查模板和决策树，便于故障定位。

提供一套用于 CloudWatch 的故障调查模式：Logs Insights 查询模板、报警到部署的关联方法、收缩影响范围的决策树以及类 PromQL 的指标查询模式。用在生产故障排查、事件分流和快速定位根因时，把常用查询和流程模块化组合起来。特别之处是把日志、指标和告警的排查流程标准化，减少现场摸索时间。

▸ 展开 SKILL.md 英文原文

Reusable investigation patterns for AWS CloudWatch: Logs Insights query templates, alarm-to-deployment correlation, blast-radius narrowing decision tree, and PromQL-style metric query patterns for structured incident triage.

开发编程CloudWatch故障排查日志查询SRE通用

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# AWS CloudWatch Investigation Skill

Reusable patterns for investigating production incidents using CloudWatch Logs, Metrics, and Alarms. These patterns are designed to be composed together during incident triage.

---

## Pattern 1: Logs Insights Query Templates

### Error Spike Detection

Find the top errors in a time window, grouped by error type:

```
fields @timestamp, @message, @logStream
| filter @message like /(?i)(error|exception|fatal|critical)/
| stats count(*) as errorCount by bin(5m), @logStream
| sort errorCount desc
| limit 20
```

### P99 Latency Breakdown by Operation

Identify which operations are driving latency spikes:

```
fields @timestamp, @duration, operation
| filte

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