Citation and refusal rates changed after a model update.
Separate input change from model regression.
Choose two monitoring practices.
Track quality by model, prompt, and input category and compare production samples with a fixed evaluation set.
Detailed explanation
The responsible change or condition can be isolated.
The responsible change or condition can be isolated.
Model regression and input-distribution change can be distinguished.
Model regression and input-distribution change can be distinguished.
Quality and safety changes are missed.
Quality and safety changes are missed.
Reproduction and diagnosis are lost.
Reproduction and diagnosis are lost.
Try it yourself
An example you can run in a temporary verification environment.
AWS公式AIF-C01 Domain 3.4の監視、品質退行、モデル更新を確認する。Expected result
本番入力変化とモデル・プロンプト変更の影響を切り分けられる。Key points
- Quality drift
- Fixed set
- Isolation
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.