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NEW QUESTION: 1
You need to deploy Azure Kubernetes Service (AKS) to host an application. The solution must meet the following requirements:
* Containers must only be published internally.
* AKS clusters must be able to create and manage containers in Azure.
What should you use for each requirement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Azure Container Registry
Azure services like Azure Container Registry (ACR) and Azure Container Instances (ACI) can be used and connected from independent container orchestrators like kubernetes (k8s). You can set up a custom ACR and connect it to an existing k8s cluster to ensure images will be pulled from the private container registry instead of the public docker hub.
Box 2: An Azure service principal
When you're using Azure Container Registry (ACR) with Azure Kubernetes Service (AKS), an authentication mechanism needs to be established. You can set up AKS and ACR integration during the initial creation of your AKS cluster. To allow an AKS cluster to interact with ACR, an Azure Active Directory service principal is used.
References:
https://thorsten-hans.com/how-to-use-private-azure-container-registry-with-kubernetes
https://docs.microsoft.com/en-us/azure/aks/cluster-container-registry-integration
NEW QUESTION: 2
ADMサイクルの開始をトリガーするために、スポンサー組織からアーキテクチャ組織に送信されるドキュメントは何ですか？
A. アーキテクチャビジョン
B. アーキテクチャ契約
C. 建築作業報告書
D. アーキテクチャ定義ドキュメント
E. 建築作業の依頼
Answer: E
NEW QUESTION: 3
You need to build an A) solution that will be shared between several developers and customers.
You plan to write code, host code, and document the runtime all within a single user experience.
You build the environment to host the solution.
Which three actions should you perform in sequence next? 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: Create an Azure Machine Learning Studio workspace
Step 2: Create a notebook
You can manage notebooks using the UI, the CLI, and by invoking the Workspace API.
To create a notebook
* Click the Workspace button Workspace Icon or the Home button Home Icon in the sidebar. Do one of the following:
Next to any folder, click the Menu Dropdown on the right side of the text and select Create > Notebook.
Create Notebook
In the Workspace or a user folder, click Down Caret and select Create > Notebook.
2. In the Create Notebook dialog, enter a name and select the notebook's primary language.
3. If there are running clusters, the Cluster drop-down displays. Select the cluster to attach the notebook to.
4. Click Create.
Step 3: Create a new experiment
Create a new experiment by clicking +NEW at the bottom of the Machine Learning Studio window. Select EXPERIMENT > Blank Experiment.
References:
https://docs.azuredatabricks.net/user-guide/notebooks/notebook-manage.html
https://docs.microsoft.com/en-us/azure/machine-learning/service/quickstart-run-cloud-notebook
NEW QUESTION: 4
A. Option C
B. Option B
C. Option A
D. Option D
Answer: D
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Feedbacks
Aalk - 2014-05-05 16:45:18
Plato - 2014-05-05 16:45:51
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Eleanore - 2014-09-28 16:36:48