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NEW QUESTION: 1
現在、アプリケーションはロードバランサーの背後にあるAmazon EC2インスタンスで実行されています。管理者は、ブルー/グリーン展開戦略の使用を決定しました。展開ごとにこれをどのように実装する必要がありますか？
A. 高可用性を確保するために、より多くのAmazon EC2インスタンスを起動し、ロードバランサーから各Amazon EC2インスタンスを登録解除し、アップグレードしてテストし、ロードバランサーに再登録します。
B. Amazon Route 53ヘルスチェックを設定して、現在デプロイされているAmazon EC2インスタンスからフェイルオーバーします。
C. AWS CloudFormationを使用して、コードを検証するためのテストスタックを作成してから、各本番Amazon EC2インスタンスにコードをデプロイします。
D. 新しいAmazon EC2インスタンスで新しいロードバランサーを作成し、展開を実行し、テスト後にAmazon Route 53を使用して新しいロードバランサーにDNSを切り替えます。
Answer: D
Explanation:
説明
以下の図は、これを行う方法を示しています

1）最初に、新しい生産変更を指すために使用される新しいELBを作成します。
2）Route53の加重ルートポリシーを使用して、80〜20％のトラフィックシナリオに基づいて2つのELBにトラフィックを分散します。これは通常の場合で、％は要件に基づいて変更できます。
3）最後に、すべての変更がテストされたら、新しいELBに対してRoute53を100％に設定できます。
これはフェールオーバーシナリオであり、ブルーグリーン展開には使用できないため、オプションAは正しくありません。 Blue Greenデプロイメントでは、2つの環境を並行して実行する必要があります。
オプションBは正しくありません。これは、並行して実行される変更を含む実稼働スタックが必要なためです。
これは青緑の展開シナリオではないため、オプションDは正しくありません。どのユーザーが新しいEC2インスタンスにアクセスするかを制御することはできません。
ブルーグリーンのデプロイの詳細については、以下のドキュメントリンクを参照してください：AWSから
* https://dOawsstatic.com/whitepapers/AWS_Blue_Green_Deployments.pdf

NEW QUESTION: 2
You need to correct the model fit issue.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Answer:
Explanation:

Explanation:
Step 1: Augment the data
Scenario: Columns in each dataset contain missing and null values. The datasets also contain many outliers.
Step 2: Add the Bayesian Linear Regression module.
Scenario: You produce a regression model to predict property prices by using the Linear Regression and Bayesian Linear Regression modules.
Step 3: Configure the regularization weight.
Regularization typically is used to avoid overfitting. For example, in L2 regularization weight, type the value to use as the weight for L2 regularization. We recommend that you use a non-zero value to avoid overfitting.
Scenario:
Model fit: The model shows signs of overfitting. You need to produce a more refined regression model that reduces the overfitting.
Incorrect Answers:
Multiclass Decision Jungle module:
Decision jungles are a recent extension to decision forests. A decision jungle consists of an ensemble of decision directed acyclic graphs (DAGs).
L-BFGS:
L-BFGS stands for "limited memory Broyden-Fletcher-Goldfarb-Shanno". It can be found in the wwo-Class Logistic Regression module, which is used to create a logistic regression model that can be used to predict two (and only two) outcomes.
References:
<https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/linear-regr ession>

NEW QUESTION: 3
Refer to the exhibit.

When is this policy setting required?
A. when EV Search is required in OWA 2007 or 2010
B. when the Restore function is required in OWA 2007 or 2010
C. when Enterprise Vault shortcuts are required in OWA 2007 or 2010
D. when the Archive function is required in OWA 2007 or 2010
Answer: A

NEW QUESTION: 4
Which guide ensures that the NetApp hardware and software components are supported with the version of Data ONTAP that you plan to install?
A. KB Articles
B. CVD Documents
C. System Configuration Guides
D. Storage Partition Guide
Answer: C
Explanation:
Explanation/Reference:
Explanation:

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