AWS CloudWatch SDK(boto3)를 사용하여 ML 기반 이상 탐지 대역이 포함된 복합 알람을 생성합니다. 알림을 위해 AWS SNS와, 자동화된 수정 트리거를 위해 EventBridge와 통합됩니다.
이 스킬은 AWS CloudWatch SDK(boto3)를 활용하여 머신러닝 기반 이상 탐지 대역(Anomaly Detection Bands)이 적용된 복합 알람(Composite Alarms)을 생성합니다. 특정 메트릭과 통계에 대해 학습된 ML 모델을 사용하여 정상적인 동작 범위를 예측하고, 이 범위를 벗어나는 지표를 감지하여 알람을 발생시킵니다. 예를 들어 EC2 인스턴스의 MemoryUtilization은 0~100 사이의 논리적 범위를 벗어나지 않는 대역을 생성하며, CPU 사용량이나 요청 지연 시간 등 float 값을 반환하는 모든 메트릭에 적용 가능합니다. AWS SNS와 통합되어 알림을 전송하고, Amazon EventBridge를 통해 자동화된 수정 작업(예: Lambda 함수 호출, Auto Scaling 등)을 트리거할 수 있어 운영 효율성을 크게 향상시킵니다. 지원 플랫폼은 Claude Code, Cursor, Codex 등 주요 AI 에이전트 도구와 호환되며, 자세한 내용은 [Agent Skill Exchange](https://agentskillexchange.com/skills/cloudwatch-intelligent-alarms/)에서 확인할 수 있습니다.
npx skills add https://github.com/agentskillexchange/skills/tree/main/skills/cloudwatch-intelligent-alarmsAWS CloudWatch SDK(boto3)를 사용하여 ML 기반 이상 탐지 대역이 포함된 복합 알람을 생성합니다. 알림을 위해 AWS SNS와, 자동화된 수정 트리거를 위해 EventBridge와 통합됩니다.
기본 사용법 또는 시작하기 노트:
머신러닝 모델은 특정 메트릭과 통계에 종속됩니다. 예를 들어,
논리적 값을 벗어나지 않습니다. 예를 들어 EC2 인스턴스의 MemoryUtilization 대역은 0과 100 사이에 유지되며,
이는 CPU 사용량, 요청 지연 시간 등 float 값을 반환하는 모든 메트릭에 대해 작동합니다.
출처: https://docs.aws.amazon.com/AmazonCloudWatch/latest/monitoring/CloudWatch_Anomaly_Detection.html
This repo contains 20 individual skills — each has its own dedicated page.
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