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NEW QUESTION: 1
Subscription1という名前のAzureサブスクリプションがあります。
VM1という名前のLinux仮想マシンをSubscription1にデプロイします。
VM1のメトリックとログを監視する必要があります。
何を使うべきですか？
A. Azure Analysis Services
B. AzurePerformanceDiagnostics拡張機能
C. LAD 3.0
D. Azure HDInsight
Answer: B
Explanation:
拡張機能を使用してVMの診断を構成し、追加のメトリックデータを収集できます。
基本的なホストメトリックは使用可能ですが、より詳細でVM固有のメトリックを表示するには、Azure診断拡張機能をVMにインストールする必要があります。 Azure診断拡張機能により、追加の監視および診断データをVMから取得できます。
参照：https://docs.microsoft.com/en-us/azure/virtual-machines/linux/tutorial-monitoring

NEW QUESTION: 2
Change control typically includes procedures for separate libraries for production programs and for test versions of programs. The reason for this practice is to:
A. Permit unrestricted a access to programs.
B. Facilitate user input on proposed changes.
C. Promote efficiency of system development
D. Segregate incompatible duties.
Answer: D
Explanation:
Separating production and test versions of programs facilitates restricting access to production programs to the individuals, such as computer operators, who need access. The effect is to separate the incompatible functions of operators and programmers.

NEW QUESTION: 3
Where can a user disable the automatic login of a user account?
A. System Preferences > Security & Privacy > Privacy
B. System Preferences > Users & Groups > Login Options
C. System Preferences > Security & Privacy > General
D. System Preferences > Users & Groups > Login Items
Answer: B

NEW QUESTION: 4
An Machine Learning Specialist discover the following statistics while experimenting on a model.

What can the Specialist from the experiments?
A. The model In Experiment 1 had a high variance error lhat was reduced in Experiment 3 by regularization Experiment 2 shows that there is minimal bias error in Experiment 1
B. The model in Experiment 1 had a high bias error and a high variance error that were reduced in Experiment 3 by regularization Experiment 2 shows thai high bias cannot be reduced by increasing layers and neurons in the model
C. The model in Experiment 1 had a high random noise error that was reduced in Expenment 3 by regularization Expenment 2 shows that random noise cannot be reduced by increasing layers and neurons in the model
D. The model in Experiment 1 had a high bias error that was reduced in Experiment 3 by regularization Experiment 2 shows that there is minimal variance error in Experiment 1
Answer: B