Release a new model gradually.
Return to the current version if quality or safety declines.
Choose two triggers or procedures.
Set versioned thresholds for latency, errors, quality, refusal, safety, and cost, and document data, cache, notice, and reevaluation steps after rollback.
Detailed explanation
Abnormal behavior can be detected.
Abnormal behavior can be detected.
Recovery inconsistencies are managed.
Recovery inconsistencies are managed.
Impact can expand.
Impact can expand.
Investigation evidence is lost.
Investigation evidence is lost.
Try it yourself
An example you can run in a temporary verification environment.
AWS公式AIF-C01 Domain 1.3のロールバック、段階展開、モデル監視を確認する。Expected result
新モデルの異常を定量条件で検知し、安全に旧版へ戻せる。Key points
- Rollback
- Threshold
- Recovery
Notes
- Environment: AWS公式AIF-C01試験ガイドとAWS公式ドキュメントの確認
- Command output formatting can vary slightly by distribution or tool version.
- Run the example in a temporary directory or process when possible.
Foundation review
Read the scope first
Check whether the command acts on the current shell, a new process, an existing process, or a file.
Verify the observable result
Use the supplied command and compare the output with the expected result.