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NEW QUESTION: 1
According to ITIL@ v3 framework, which type of service operational management process involves root-cause analysis to identify and resolve the cause of events and incidents that impact the managed network environment?
A. problem
B. incident
C. configuration
D. event
Answer: A
NEW QUESTION: 2
Which two statements about Signature 1104 are true? (Choose two.)
A. This signature has triggered as indicated by the red severity icon.
B. This signature is enabled, but inactive, as indicated bythe/0 to that follows the signature number.
C. The severity level is High.
D. Produce Alert is the only action defined.
E. This is a custom signature.
Answer: C,D
Explanation:
This can be seen here where signature 1004 is the 5th one down:
NEW QUESTION: 3
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. 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。
B. 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。
C. 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。
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. 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。
Answer: B
Explanation:
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).