Ingestion volume is much higher during weekday daytime than overnight.
A fixed threshold creates too many alerts, so detect deviation from the normal pattern.
Which monitoring approach is most appropriate?
Apply CloudWatch anomaly detection and combine it with fixed thresholds and operational context.
Detailed explanation
A single value ignores normal day-night variation and causes false alerts or misses.
A single value ignores normal day-night variation and causes false alerts or misses.
API activity does not necessarily follow the data-processing pattern.
API activity does not necessarily follow the data-processing pattern.
Retention rules are separate from anomaly detection.
Retention rules are separate from anomaly detection.
A learned band can account for historical patterns and alarm on unusual deviations.
A learned band can account for historical patterns and alarm on unusual deviations.
Check official documentation
Compare the following points with the official documentation.
Amazon CloudWatch anomaly detection、metric math、alarmsの公式説明を確認する。
What to confirm
固定値と季節性を考慮した異常検知の適用範囲を説明できる。
Key points
- Anomaly detection
- Seasonality
- Metric math
- False positive
Notes
- Environment: AWS公式DEA-C01試験ガイドと各サービスの公式ドキュメントの確認
- Confirm current AWS service behavior in the official DEA-C01 documentation.
Foundation review
Training period
Exclude deployments and unusual campaigns from the normal-pattern learning window.
Detection is not diagnosis
Use logs, execution IDs, and dependency metrics to find the cause after an anomaly.