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NEW QUESTION: 1
Which technique involves replacing values within a specific data field to protect sensitive data?
A. Anonymization
B. Obfuscation
C. Tokenization
D. Masking
Answer: D
Explanation:
Explanation
Masking involves replacing specific data within a data set with new values. For example, with credit card fields, as most who have ever purchased anything online can attest, nearly the entire credit card number is masked with a character such as an asterisk, with the last four digits left visible for identification and confirmation.

NEW QUESTION: 2
モデルをトレーニングして、Azure Machine Learningワークスペースに登録します。これで、モデルをリアルタイムWebサービスとしてデプロイする準備が整いました。
モデルをAzure Kubernetes Service（AKS）推論クラスターにデプロイしますが、サービスがモデルのデプロイメントに関連付けられているエントリスクリプトを実行するとエラーが発生するため、デプロイメントは失敗します。
コードを更新するたびにサービスを再デプロイすることなく、コードを繰り返し変更してサービスをリロードすることにより、エラーをデバッグする必要があります。
あなたは何をするべきか？
A. エントリスクリプトの最初の行にブレークポイントを追加し、サービスをAKSに再デプロイします。
B. AKSサービスの展開構成を変更して、アプリケーションの洞察を有効にし、AKSに再展開します。
C. ローカルWebサービスデプロイメント構成を作成し、モデルをローカルDockerコンテナーにデプロイします。
D. モデルの新しいバージョンを登録し、エントリースクリプトを更新して、登録されたパスからモデルの新しいバージョンをロードします。
E. Azureコンテナーインスタンス（ACI）Webサービスデプロイメント構成を作成し、ACIにモデルをデプロイします。
Answer: E
Explanation:
How to work around or solve common Docker deployment errors with Azure Container Instances (ACI) and Azure Kubernetes Service (AKS) using Azure Machine Learning.
The recommended and the most up to date approach for model deployment is via the Model.deploy() API using an Environment object as an input parameter. In this case our service will create a base docker image for you during deployment stage and mount the required models all in one call. The basic deployment tasks are:
1. Register the model in the workspace model registry.
2. Define Inference Configuration:
a. Create an Environment object based on the dependencies you specify in the environment yaml file or use one of our procured environments.
b. Create an inference configuration (InferenceConfig object) based on the environment and the scoring script.
3. Deploy the model to Azure Container Instance (ACI) service or to Azure Kubernetes Service (AKS).

NEW QUESTION: 3




A. Option A
B. Option B
C. Option C
D. Option D
Answer: D
Explanation:
Explanation
This can be seen on the Globabl Correlation - Inspection/Reputation tab show below:

NEW QUESTION: 4
開発者は、最低限の処理が可能な3層Webアプリケーションを構築しています
1分あたり5000件のリクエスト。要件では、アプリケーションがユーザーのセッション状態を維持する間、Web層は完全にステートレスである必要があると記載されています。
レイテンシを可能な限り低い値に保ちながら、セッションデータをどのように外部化できますか？
A. 基盤となるAmazon EC2インスタンス全体に共有ファイルシステムソリューションを実装し、アプリケーションレベルでセッション処理を実装して、共有データシステムをセッションデータストレージに活用します
B. Amazon RDSインスタンスを作成し、アプリケーションレベルでセッション処理を実装して、RDSデータベースインスタンス内のデータベースをセッションデータストレージに活用します
C. Amazon DynamoDBテーブルを作成し、アプリケーションレベルでセッション処理を実装して、テーブルをセッションデータストレージに活用します
D. Amazon ElastiCache Memcachedクラスターを作成してから、アプリケーションレベルでセッション処理を実装して、セッションデータストレージにクラスターを活用します
Answer: B
Explanation:
Explanation
https://aws.amazon.com/caching/session-management/